Tag: Artificial Intelligence
How the insurance industry delivers service has evolved significantly in the last decade.
Regardless of what form of insurance sales or policy management your organization is engaged in, you can attest that face-to-face interactions are no longer routine and are, in fact, an oddity.
As the insurance industry’s new normal, more and more interactions between customers, industry experts, other organizations, and adjustments claims occur digitally. Though phone-based communications will continue to be a part of the customer service process for the foreseeable future, customers, care providers, other insurers, and virtually anyone else with whom an insurance company interacts have come to expect a largely digitized experience.
For any organization to thrive in the insurance industry of tomorrow, it must take steps to evolve its processes today. That means creating a cohesive modernization strategy and investing in leading-edge technology solutions.
Read more: Answering the Burning Questions of Business Leaders on Digital Transformation!
Top Challenges Facing the Insurance Industry
To understand what a modernized strategy looks like in the insurance industry, it’s vital to examine some of the top challenges businesses will face in the coming years.
1. Staffing Shortages
Historically, the insurance sector has contended with turnover rates somewhere in the range of 8-9%, according to Insurance Business America, but that span climbed to 12-15% by September 2022.
That additional turnover significantly impacts business continuity and diminishes the customer experience. It can also negatively influence insurers’ ability to replace members of leadership that are retiring or stepping away from the industry.
2. Skyrocketing Costs
Inflation and numerous other factors have contributed to rising costs of everything from healthcare to vehicles higher than ever before. Naturally, some of these cost increases are passed onto insurers and their customers, so insurance companies must find ways to absorb some of these expenses while mitigating rate increases for their clients.
Insurers should also explore ways to reduce their operating costs to keep coverage prices lower. Otherwise, businesses may find it challenging to retain customer accounts, particularly in sectors like automotive insurance, where consumers can freely shop around and change policies in six-month intervals.
3. Antiquated Legacy Systems
Some legacy systems hinder the ability of many businesses to embrace digital transformation. These aging platforms can make it challenging to comply with relevant regulatory requirements and increase an organization’s overall operating costs.
The longer that insurance companies cling to antiquated systems, the harder it will be for them to streamline traditionally tedious practices, such as claim management. Therefore, insurance companies must replace these inefficient, disjointed platforms with modern, unified alternatives.
The Role of Digital Transformation in Solving These Challenges
Digital transformation can bring modern technologies to any business process to improve its operation. Fast-growing digital transformation technologies include machine learning, artificial intelligence (like ChatGPT), customer relationship management platforms, and intelligent document processing software.
Digital transformation holds the key to solving the insurance industry’s most significant problems, and it appears that many in the industry realize this, as recent projections estimate that insurance technology spending will increase by 25% between 2022 and 2026 in the US and UK.
A cohesive digital transformation strategy will lay out a roadmap for replacing aging technologies with modern alternatives, and once these technologies have been replaced, the cost savings are almost immediate.
In one example of how a digital transformation strategy led to practical innovation, Fingent joined forces with the California law firm of Sapra & Navarra, LLP to develop Ambit, an AI and ML program that simplifies and enhances the management of workers’ compensation claims. Claims may include hundreds of pages consisting of a variety of letters, affidavits, forms, and other documents from claimants, doctors, lawyers, investigators, employers, and witnesses, among others. Utilizing both artificial intelligence and machine learning, the Ambit system streamlines the claims management process, reducing claim costs, and helps break the old practices of:
- Taking too long to assess claims
- Treating similar claims inconsistently
- Not equipping claim adjusters with modern tools
Instead, Ambit improves the efficiency of all parties — insurance carriers, self-insured companies, lawyers, and claim adjusters — while reducing costs for insurers by 57%.
The Ambit solution was designed to:
- Easily ingest the many documents in the claims process
- Quickly identify missing, processed & corrupted pages
- Review structured and unstructured documents automatically
- Identify areas of concern
- Suggest potential legal defenses
- Automate calculations and reminders for important legal deadlines
- Generate case summaries, with action plans
These automation capabilities not only make life easier for claims managers but enable organizational leaders to offset productivity issues created by ongoing labor shortages by reducing onboarding time for new hires. These capabilities result in more uniform handling of the claims while speeding their resolution and lowering their overall costs.
In general, automation technologies, such as those implemented during a digital transformation initiative, will also decrease operating costs, enabling insurance companies to increase their profitability and offer their customers more competitive premiums.
Read more: How AI Drives Digital Transformation In The Insurance Industry
The Essential Components of Digital Transformation
The technology trend in insurance is clearly moving from the strictly paper-based methods of the past to the digital. Beyond static websites to mobile apps. Beyond email to text and chat. Beyond processes driven by people to more and more intelligent automation that speeds up and uniformly handles all kinds of processes from marketing, and operations, to customer service.
Every organization’s digital transformation roadmap should be as unique as the business itself, but every digital transformation strategy must include a few core elements:
- Clear objectives
- An integrated plan
- A leadership-driven approach
- Investments in the right technology
When creating your organization’s digital transformation strategy, you should start by defining your “why.” In other words, you must identify the reasons you are undertaking this initiative in the first place.
From there, work with a digital transformation partner who can help you create an integrated plan that includes everyone from executive members to line-level employees.
Digital transformation efforts — even small ones — require the active support of top management. Change is the hardest thing to achieve in the organization and without the sponsorship of the corporate leaders, the effort is unlikely to succeed.
Finally, you will need to replace outdated, inefficient technology with modern, robust solutions. When appropriate,
partner with a custom software development firm that can provide you with a purpose-built solution you need for your business. They are equipped with the personnel and experience to generate a solution in the minimum timeframe and without the need to increase in-house headcounts.
If your organization has been exploring ways to improve the customer service experience, increase productivity, improve profitability, and streamline its operations, it is more than ready to embrace digital transformation.
Successfully facilitating digital transformation requires a cohesive strategy, some cutting-edge technologies, a commitment to doing things better, and the right development approach.
Read more: Digital Twin Improving Predictability and Risk Management in Insurance!
How Fingent Can Accelerate Your Process
Naturally, the cornerstone of any digital transformation initiative is technology choices. These may be an off-the-shelf system for standard processes, the integration of existing systems or, your transformation may demand a custom solution that can accommodate your business needs unlike systems available to anyone else.
At Fingent, we specialize in creating resilient custom software solutions that are able to change and adapt according to your requirements. We work with insurance industry clients to help them streamline mission-critical business processes, and – as in all our projects – we accomplish this by providing dynamic, unique software that incorporates the most appropriate technology, such as the latest in machine learning and artificial intelligence technologies.
Connect with Fingent today to accelerate your digital transformation with the help of an experienced software development partner.
No longer the stuff of science fiction, artificial intelligence (AI) and machine learning (ML) are revolutionizing the way customers interact with brands. Businesses that have embraced these technologies can reshape the customer experience, curate one-of-a-kind buyer journeys, and strengthen bonds with their target audiences.
As your organization works to remain competitive in the modern business ecosystem, it must tap into the power of AI and ML technologies to provide a superior customer experience.
How Are AI and ML Enhancing Customer Experience?
Artificial intelligence and machine learning solutions can profoundly impact every facet of the customer experience. By leveraging these technologies, your business can:
1. Facilitate Hyper-Personalization
Customers who interact with your brand are looking for a personalized experience. As such, brands that put their products and services at the center of attention instead of prioritizing experience will miss the mark. Likewise, blasting your customers with generic advertising content or sending them broad, basic messages simply won’t cut it anymore. Instead, you must personalize every interaction to deliver timely and relevant content to each user.
Artificial intelligence and machine learning technologies facilitate a level of hyper-personalization that was thought to be unachievable just a few years ago. In a 2022 Salesforce survey, 88% of consumers reported that an experience provided by a company is almost as important as the product. Using AI and ML technologies, you can personalize customer experiences by utilizing real-time data, like their browsing history, purchasing habits, etc.
Artificial intelligence and machine learning solutions can also eliminate friction from the customer journey. For instance, AI- and ML-powered chatbots can leverage information from past interactions to create personalized messages for each consumer. This will minimize customer frustration by reducing how often consumers are asked to repeat information they have previously provided.
2. Allow Customers to Stay Connected 24/7
Customers expect access to timely and relevant support around the clock. However, staffing your customer support department 24/7 is financially infeasible. So how do you bridge the gap between customer expectations and the fiscal limitations of your business? AI and ML solutions are the clear answer.
With artificial intelligence and machine learning technologies, you can provide your customers with access to automated support like chatbots. These bots can respond immediately to customers and resolve many basic product- or service-related issues without tying up your customer support staff. This capability will not only allow you to reduce the workload on your team but also help you provide more timely and omnichannel service to customers, no matter when they reach out for assistance.
3. Conduct Predictive Behavior Analyses
The sooner you can identify consumer behavior trends, the better your chances of capitalizing on emerging opportunities. Unfortunately, traditional analytics solutions do not facilitate real-time decision-making because they often rely on data that is days (or even weeks) old.
The good news is that artificial intelligence and machine learning technologies enable you to conduct predictive behavioral analyses using real-time data, guiding your decision-making processes and enabling you to adapt to emerging trends like never before.
4. Enhance Your Understanding of Target Audiences
Artificial intelligence and machine learning technologies allow you to step into your target audience’s mind. You can use these newfound insights to guide your digital marketing strategies, refine products and services, and enhance the customer experience.
Due to how AI and ML learn and evolve, these technologies will only become more effective over time as they get access to more data, better helping you anticipate how your target audiences are likely to behave in the future. This enables you to proactively eliminate friction points from the buyer’s journey and paves the way for increased sales and better profitability.
Read more: Is AI-powered mobile app what you need for your business now?
Use Cases: Major Industries that Have Embraced AI and ML
Artificial intelligence and machine learning technologies are going mainstream, and many industries are taking advantage of these powerful tools for both B2C and B2B interactions. Business leaders in these sectors understand that these technologies will significantly impact their organizations’ ability to compete, both now and in the future.
Some of the industries that are using AI and ML technologies on a broad scale include:
- Software development
- Language processing and transcription
- Retail
- Customer service
- Marketing
- Manufacturing
- Finance
- Agriculture
- Logistics and transportation
- Healthcare
The healthcare and logistics sectors were some of the earliest adopters of artificial intelligence and machine learning technologies, whether by predicting the likelihood of patients developing certain diseases or by providing customers with more accurate shipping estimates. These industries (and every other on this list) utilize AI and ML technologies to enhance the customer experience.
These technologies also provide meaningful insights into the efficiency of business operations. Organizational leaders can use the information gleaned from these technologies to proactively address critical organizational growth hurdles and promote business continuity.
How Your Business Can Optimize Customer Experience with AI and ML
Artificial intelligence and machine learning technologies will empower your business to revolutionize the customer experience along every meaningful touchpoint. First and foremost, these technologies will help your business truly understand the customer journey and its impact on organizational profitability. And once you understand the state of your business and how well it is currently managing the customer experience, you can begin using your AI and ML tools to refine the customer experience.
If you want to maximize your return on investment, consider incorporating artificial intelligence and machine learning technologies into as many business processes as possible. You can use these solutions to automate redundant processes, hyper-personalize advertising content, and refine the customer experience from top to bottom.
Read more: Use cases and business benefits of deploying Machine Learning!
Tap into the Power of AI and ML with Fingent
Are you ready to harness the power of artificial intelligence and machine learning so that you can provide your clients with the experience they deserve? If so, then it is time to explore a partnership with Fingent.
At Fingent top custom software development company, we provide customized artificial intelligence applications and machine learning solutions. Cumulatively, these technologies will differentiate your brand in the competitive digital marketplace and enable you to modernize the customer experience.
To learn more about Fingent’s suite of services and solutions, contact our team today. Together, we can reshape your customer experience and set the stage for the growth of your business.
We currently live in the eon of Artificial Intelligence. Whether we like to admit it or not, AI has suffused its way into every industry in all of its beautiful ingenuity.
Did You Know?
“The global artificial intelligence market size was valued at USD 93.5 billion in 2021.” – Grand View Research
“AI could contribute up to $15.7 trillion1 to the global economy in 2030.” – Sizing the Prize, PwC Report
What is Artificial Intelligence?
Artificial intelligence (AI) is a simulation of human intelligence processed by electronic gadgets that enables the execution of an array of advanced functions, like seeing, understanding, and translating spoken and written language, data analysis, and many more.
From robots that can navigate a warehouse by themselves to virtual assistants that understand what people are saying and act upon that information, we can see Artificial Intelligence in play everywhere.
Read more: Reimagine Your Business with AI. Here’s How!
Artificial Intelligence-Based Code Generation Tools
Let’s take a look at code-generation tools that are based on AI technologies. This article will discuss three such tools – Codex, Co-pilot, and ChatGPT.
1. Codex
As announced by the Artificial Intelligence Research Company OpenAI, the Codex model series is a successor of the GPT-3 series and is trained with both natural language and billions of lines of code. It is most competent in Python and is proficient in many more languages, including C#, JavaScript, Ruby, Swift, TypeScript, SQL, and even Shell.
Due to its understanding of many languages, Codex can transcribe simple commands in natural language and execute them according to the user’s preference. This makes building a natural language interface into existing applications possible. It also helps speed up the work of professional programmers and helps amateurs get started with coding.
2. Copilot
GitHub Copilot, fabricated by GitHub and OpenAI, is a cloud-based AI tool that assists users of Visual Studio Code, Visual Studio, Neovim, and JetBrains integrated development environments (IDEs) with auto-completing code.
GitHub Copilot is trained on billions of lines of code and uses this knowledge to turn natural language prompts into deft coding suggestions. It is famous for evaluating and suggesting improvements for social media profiles, facilitating online presence across various digital channels.
Copilot uses AI technology to engage with potential leads through messages and categorizes them based on responses. It is trending with a whopping 4.67-star rating and is widely praised for its enormous support.
3. ChatGPT
OpenAI released yet another ingenious model called ChatGPT. It is a long-form question-answering AI that addresses complex questions conversationally. This is a revolutionary technology because it not only understands human language but is also trained to learn what humans mean when they ask a question.
The New York Times headlined, “ChatGPT and other chatbots is a ‘code red’ for Google search engine.”
While The Indian Express, in an article, stated that “When it was introduced, ChatGPT’s ability to break down complex problems and explain everything in a human-like manner led many to proclaim that Google’s days as the numero uno search engine are numbered.”
ChatGPT is undeniably a hot topic, and its reasons stand strong. Its dialogue format makes it possible to provide answers to any follow-up questions, accept its mistakes, challenge incorrect premises, and reject inappropriate requests.
Its specifically trained ability to understand the human intent behind every question and provide helpful, harmless answers while discarding parts of the question that do not make sense only adds to its special nature.
Read more: Is AI-powered Mobile App What Your Business Needs Now?
Benefits Of These AI Tools
1. Codex –
“You just ask the computer to do something, and it just does it,” said OpenAI CTO Greg Brockman in the video demo of Codex.
Codex is good at co-referencing resolutions. It also links nouns in the prompt/input to their proper variables and functions in the code. Codex can also execute mundane tasks, like rendering web pages, launching web servers, and sending emails.
As AI technology takes over all the tedious parts, the programming process is prone to become more efficient. OpenAI shows Codex has a 37% accuracy rate in effectuating coding tasks.
2. Copilot –
A new study by GitHub revealed that Copilot works as an AI code programming assistant, significantly increasing developer productivity and happiness.
This particular AI-based code generation tool stands out because of its simplicity. You can describe the task you desire, outcome, or suggestion in the comments, and Copilot can come up with what it thinks are the proper lines of code. On the other hand, you can infer just your intentions with an incomplete prompt, and Co-pilot will do the code generation according to the same prompts.
3. ChatGPT –
Firstly, it reflects its efficiency by handling large volumes of conversation without needing breaks, which is undoubtedly helpful for customer service or other applications with a high demand for conversation. It also personalizes these conversations allowing them to feel unique for different users.
Using ChatGPT is highly cost-effective because it eradicates the need to hire human employees to handle conversation tasks. It is also available 24 hours a day throughout the week and has a great language support system.
How It Enables Reduced Costs
Embracing Artificial Intelligence is a deft, cost-effective decision that most businesses and industries need to make. AI helps companies progress on many fronts, but the most imperative is its impact on the company’s pocket.
Implementing AI-based code generation tools such as Codex, Copilot, and ChatGPT reduces the need to hire miscellaneous employees to perform repetitive, tedious tasks. This, in turn, reduces the chances of any mishaps that may cost the company money to fix. Using these tools as assistants also greatly helps employees with their workload.
Using a more personalized, accurate, and compactable AI technology in your business can attract many potential clients and customers. This ultimately creates a profit for your business while also helping you establish your roots in the industry.
35% of consumers feel the desire to see more companies using chatbots. This is the perfect time to build the software you “ever needed” at a reduced cost.
Read more: Artificial Intelligence and Machine Learning for Faster and Accurate Project Cost Estimation
Myths Around The Use Of AI Tools
The long-standing fear of technology taking over mankind has always had its chokehold on innovation. It is time to debunk the myths that surround AI and let technology progress.
Myth #1 – AI Is Going To Take Over Every Job Sector
One thing to remember is that no matter what, Artificial Intelligence tools will not replace the developers but increase developer productivity. It is reasonable to believe that AI has the potential to disrupt labor, but to compare labor from humans to machines directly is an unnecessary simplification. AI tools exist solely to enable humans to work in a newer and smarter way.
Myth #2 – AI Is Magic
The idea that AI tools can magically make sense of any and all of your messy data is completely erroneous. AI does not work on the principle of “load and go,” and the quality of input data is more important than the AI algorithm. This implies that the data being prompted has to be relevant to the problem being solved and specific to a set of use cases and a domain of knowledge.
What The Future Holds For The Industry With AI Tools
AI has consistently altered the course of the world multiple times and will continue to do so in the future. Although it is not a mainstream technology, billions of dollars are spent annually on AI research and development.
Did You Know?
As of the latest 2022 data, the global AI market is worth $136.6 billion. By 2030, the global AI market is expected to reach $1.81 trillion.
Some other industries that are largely affected by AI tools include –
- Software Development Companies
- Information Technology
- Finance
- Manufacturing
- Customer Service
- Education
Get Future-Ready With The Best of AI
Using AI-based code generation tools can give you the upper hand you have been waiting for. Unlock your business’s potential with Fingent, the top custom software development company. Get in touch with our experts for a power boost and to get ahead of the competition.
The strategic significance of advanced technologies as a critical business component is recognized by enterprises like never before. Besides business modernization and cost reduction, advanced technologies allow you to compensate for labor shortages, improve brand value and competency, and expedite research and innovation processes. However, several companies jump onto the bandwagon without properly understanding the practical applications and benefits of advanced technologies. The World Economic Forum indicates that only 23% of small and medium-sized enterprises (SMEs) worldwide can invest in and grow with new digital tools. This data proves why businesses should crucially analyze advanced technologies before adopting digital tools.
To streamline things, here’s a quick rundown of five advanced technologies we believe will help you cope with the new business and economic environment.
- Simplifying Workflows With Cloud
- Low-code Applications
- Robotic Process Automation (RPA)
- Document Data Extraction
- AI Assistants
As these technologies become more affordable and handy, businesses are ardently pursuing them to automate customer service, streamline workflows, differentiate products and services, and reach new markets. Depending on your budget, implementation timeline, priorities, and unique business requirements, our team at Fingent helps you build the roadmap for technology adoption.
Read more: How to gain maximum value from your technology investments?
Let’s take a closer look at the five inevitable technologies for business transformation today:
1. Simplifying Workflows with Cloud
Workflow management is a highly overlooked enterprise strategy that directly impacts productivity. Managing different stakeholders, heaps of confidential data, and a series of preset and conditional tasks manually can lead to several errors, such as employees missing key steps, policy violations, compliance issues, and monetary losses. By taking your workflows online, cloud-based workflow management applications increase your productivity.
Cloud-powered workflows or workflow management tools:
- Are scalable, centralized, customizable to your needs, easy to integrate, secure, reliable, and hassle-free.
- Offer a seamless and unified collaboration interface by preventing users from toggling between different messaging apps or communication channels.
- Reduce your dependency on the in-house IT team by passing on the software maintenance responsibilities to the third-party software vendor.
- Can be accessed via any authorized network (with approved access credentials), on any device, from anywhere, 24/7. This has been a huge game-changer for several companies that switched to remote operations during the pandemic.
Example of a Cloud-based Workflow Tool
Finding a cloud workflow management tool that can be customized to your company’s requirements is daunting. The platform should integrate well with your organizational processes without disrupting your workflow. This is where digital workplace applications like InfinCE make the difference.
With InfinCE Digital Workplace, Fingent has improved its productivity by 20% through real-time, effective, and easy collaboration. Data-powered dashboards, dedicated servers, collaboration apps, productivity tools, virtual desktops, private mobile apps, and a host of exceptional business management features enabled us to achieve a significant operational breakthrough in streamlining workflows.
Read the full case study here.
2. Low-code Applications
Gartner estimates that by 2025, 70% of enterprise applications will use low-code or no-code technologies. Digital business transformation requires pushing custom software solutions to the market at lightning speed. This demand has given rise to low-code applications that will break the technological and organizational silos of application development, automation, integration, and governance. Low-code development enables business users to bring innovative ideas to life by dragging and dropping low-code elements through a graphical user interface.
Simply put, low-code development enables “citizen” developers or non-tech users (such as business analysts or marketers) to build dashboards and survey or contact forms faster. On the other hand, professional developers can leverage low-code techniques to perform more efficient tasks, such as legacy application modernization or back-end integrations, with improved agility and velocity.
Use Cases for Low-code Applications
- Customer engagement applications and portals
- Mission-critical applications such as ERP software, payments manager, etc.
- Data analysis applications, BI dashboards, and data management software
- Mobile apps for customer engagement
- Order processing, inventory, order fulfillment, supply chain, and accounting apps
Salesforce Lightning, Microsoft Power Apps, and Zoho Creator are some of the leading low-code applications today. SAP users can leverage the unified low-code/no-code (LCNC) solutions on the SAP Business Technology Platform (BTP) to rapidly build and extend applications and automate tasks and processes.
Read more: Low Code/No Code Development with SAP BTP: How It Is Turning the Future of Enterprise Resilience
3. Robotic Process Automation (RPA)
Robotic Process Automation (RPA), often called software robotics, is an easy-to-use software technology that allows anyone to automate digital tasks within their business processes. RPA allows users to create software robots or “bots” to learn, emulate, and execute rules-based business processes. According to Forrester Research, RPA software revenue is expected to reach $6.5 billion by 2025, while RPA-related services revenue could hit $16 billion in the same year.
Potential Use Cases for RPA
We offer free proof of concepts to help you understand how RPA can improve your business efficiency and customer experience. Some of our top use cases include:
- Automating discharge protocols and data management to increase HR productivity in healthcare.
- Daily retail processes automation, such as order processing, inventory and warehouse management, etc., to save time and resources.
- Reducing customer wait times through RPA-enabled chatbots that answer customer queries in real time.
- Error-free, automated billing and invoices to keep your financial systems and reports up-to-date.
- HR teams can automate personnel data and records maintenance, streamline onboarding, and seamlessly manage payroll.
4. Document Data Extraction
Extracting quality data from unstructured or poorly structured data sources and documents for further processing, migration, and storing has been the biggest obstacle in automating back-office operations. If you enter structured invoices into a robust ERP tool like SAP, your payments can be automated, and system records can be generated automatically. Due to the high costs of data extraction, several businesses extract only critical information fields, for example, the payment field within an invoice. Businesses are compelled to manually extract data from other important fields, such as validating the invoice’s compliance with VAT.
AI-integrated OCR Software for Document Extraction
Optical Character Recognition (OCR) is an affordable, game-changing technology that automatically extracts data from the digital images (photos) of large files, scanned documents, and sub-titles or captions superimposed on an image. It reduces the time spent in manual data entry and extraction by automatically converting typed, handwritten, or printed text into machine-readable text. AI-powered automated data extraction tools like DocuSign, Docsumo, Kofax Capture, and Amazon Textract leverage OCR technology to reduce the chaos involved in document data extraction and enable businesses to create an efficient workplace.
Our team helps customize document data extraction software that can save you time and money by eliminating transcription and transposing mistakes.
5. AI Assistants
One of the most common examples of small business automation today is using AI-powered virtual assistants. They can save your employees’ productivity by automating the most repeatable customer interactions, such as technical support, appointment scheduling, lead qualification, and order management. AI virtual assistants like Google Assistant and Alexa can understand and act according to your voice commands and customize responses to your queries. Understanding customer intent through natural language processing and recognition allows AI assistants to maintain a human-like conversation.
Chatbots are a popular category of AI assistants designed specifically for text-based channels like SMS, email, and live chat. Recent years have witnessed a rise in chatbot adoption among several business verticals, product and service lines, websites, mobile apps, customer portals, etc. Data shows that 58% of B2B companies and 42% of B2C websites use chatbots to make their websites and mobile apps more interactive. More than 56% of businesses believe chatbots to be driving digital disruption in their industry.
Case Study: AI Virtual Assistant for HR
Fingent’s HR team was pressed to transform their service delivery model as routine, transactional tasks affected their performance and efficiency. To solve their struggle, Fingent developed MUSA, an AI-powered virtual assistant (a chatbot), and integrated it with Fingent Hub, Fingent’s internal employee management system. MUSA is short for Multi Utility Assistant. Employees can ask MUSA any queries related to HR and IT DevOps processes at Fingent, and they’ll get answered instantly. MUSA has improved our HR team’s response time by minimizing their workload and allowing them to focus on areas requiring more attention.
Business and Technology Are Inseparable!
Gartner writes that businesses with technology employ advanced tech to boost customer experience and revenue growth, clearly understand their priorities, goals, and strategies, and invest in solutions tailored to their needs. Technology allows businesses to lower the walls within and between their organizations, customers, providers, suppliers, etc. Organizations perceiving technology as a key business consideration will be able to match the pace of business change and stay relevant and competitive.
How can your business embrace growth in a new era of transformation and technology trends?
If you’re getting caught in the technology maze, take a quick break to contact us. Our consultants can simplify your technology adoption strategy based on your priorities, customer needs, financial resources, and technical requirements.
Machine learning is changing the face of everyday life, science, and business. It is revolutionizing all industries, from advancing medicine to powering various cutting-edge technologies. Though Machine learning (ML) was a part of AI’s evolution until the 1970s, it evolved independently. It has become a chief response tool for cloud computing and eCommerce.
The goal of machine learning in business is to adapt to new data independently and make decisions and recommendations based on thousands of analyses. Machine learning enables systems to learn, identify patterns and make informed decisions with minimal human intervention.
Today, ML is a necessary aspect of modern business. It uses algorithms and neural network models to improve the performance of computer systems. Machine learning in business and manufacturing is enabling organizations to achieve notable strides. These strides include increased performance and efficiencies, improved processes, and enhanced security.
This article will discuss the benefits of machine learning in business and its use cases.
Remarkable Benefits of Machine Learning for Businesses
According to Fortune Business Insights, the global market size for machine learning in business is expected to grow to USD 209.91 billion by 2029, exhibiting a CAGR of 38.8% during the forecast period. ML has been and continues to scale operations tremendously. Across industries, ML has led to a boom in affordable data storage and faster and more reliable computational processing.
Here are six remarkable benefits of machine learning in business:
1. Automation for better decision-making
Most businesses find themselves wasting precious time sorting through duplicate and inaccurate data. Such businesses benefit from using the predictive modeling algorithms of ML in their processes. Such a process will understand duplicate inaccurate data and distinguish the anomalies. It enables the organization to avoid inaccurate reporting that can result in poor customer retention.
Instead, this will allow businesses to use their accurate database to detect wasted costs, missed opportunities for sales, and revenue capital. In addition, organizations can overcome challenges and risks that arise due to miscommunication or poor performance metrics. Thus, businesses can streamline their operations and improve decision-making which could be translated into better ROI.
2. Increased scalability with minimum expense
Semi-supervised machine learning algorithms can help organizations leverage useful insights from customer profiles and enable them to view their brands from customers’ perspectives. Doing so will equip organizations with relevant insights to build their brand by improving their products and services.
3. Predictive maintenance
Predictive maintenance that ML aids manufacturing firms’ power to follow best practices that lead to efficient and cost-effective operations. The historical and real-time data predict problems and stipulate strategies to solve those problems. Plus, workflow visualization tools can eliminate issues and unwanted expenses incurred due to those issues.
4. Financial analysis
ML can greatly assist as it gathers and analyzes large volumes of quantitative and accurate historical data. It is used for portfolio management, loan underwriting, fraud detection, and more.
5. Personalization
Using machine learning in business will allow organizations to know their customers better and provide them with a more personalized customer experience. Organizations no longer need to rely on guesswork because ML models can process different types of information collected from numerous sources and provide relevant data about their customers.
6. Cybersecurity
ML technologies can improve cybersecurity to solve cyberattacks once and for all. Empowered by ML, intelligent security programs can gather and process data about cyber threats and respond to them in real time. ML models can detect the slightest deviations in patterns and flag them. Or destroy an attack in its nascent stage.
Read more: Can Machine Learning Predict And Prevent Fraudsters?
Top Use Cases
Machine Language has made its mark across industries and found a place in many different applications. Here are some top use cases:
1. Enhanced social media features
Businesses can use machine learning algorithms to create attractive and effective social media features. For example, ML algorithms in Facebook enable it to identify and record a person’s activities. These activities include records of chats and the amount of time that person spends on each post. It uses this data to determine what kind of friends and topics may interest that person and accordingly make suggestions.
Read more: Why Time Series Forecasting Is A Crucial Part Of Machine Learning
2. Product recommendation
Product recommendation is an advanced application of machine learning techniques. It has been the most popular application of almost every eCommerce website today. This technique allows websites to track a consumer’s behavior based on their previous purchases, search patterns, and cart history. It enables the website to make apt product recommendations to that consumer.
3. Recognition
Image recognition is one of the most significant and notable ML and AI techniques. It is adopted further for pattern recognition, face detection, and face recognition.
4. Sentiment analysis
Sentiment analysis is a real-time ML application. It determines the emotion or opinion of the speaker or the writer. For example, a sentiment analyzer can detect the thought and tone of a written review or an email. It can analyze the review-based website, decision-making applications, and more.
5. Access control
Most large businesses are actively implementing ML models to determine the level of access an employee should be granted. This application of machine learning can ensure the security of the organization.
6. Bank Domain
Banks are using ML to prevent fraud and protect accounts from hackers. Machine learning algorithms determine what factors to consider in creating a filter to prevent an attack.
Read more: Machine Learning – Deciphering the most Disruptive Innovation
How Fingent Can Help with Deploying the Best of ML
Leveraging the capabilities of machine learning in business can open the door to many opportunities. It is wise for any organization to take advantage of ML rather than lag behind competitors. However, we understand if you have questions. That’s why Fingent software development experts are here to help you. We can deploy the best machine-learning models efficiently and smoothly.
As a partner, Fingent can work with your team as you take on digital initiatives for sustainable business growth. We enable our clients to make data-driven decisions by efficiently deploying machine learning in business. Our cost-effective services will save you a considerable amount of time and money.
Furthermore, we do not follow a one-size-fits-all strategy. We provide custom software development services that cater to your needs. Therefore, look no further if you are looking for a reliable, efficient IT partner to deploy the best machine-learning models.
From the mundane to breathtaking, AI is disrupting virtually every business process in all sectors. People are ceasing to associate Artificial Intelligence with science-fiction dystopias as Artificial Intelligence (AI) is taking more commonplace in our daily lives. While such acceptance in mainstream society is a new phenomenon, it is not a new concept in business. Today, AI has become imperative to maintain a competitive edge.
This guide will help business owners who are serious about maintaining a competitive edge in their business sector by adopting AI.
Rising Need for Adopting AI In Business
Did you know that 52% of companies accelerated their AI adoption plans after the pandemic? Why?
Artificial Intelligence in business is seen as a supporting tool. It is adept at processing and analyzing a trove of data much faster and more efficiently than a human brain can. Since AI can synthesize courses of action and present them to the human user, businesses can use AI to help investigate the probable consequences of each action. That way, businesses can streamline the decision-making process. This is what makes AI valuable throughout many industries.
Artificial Intelligence is a form of software that can make decisions independently. It can act even in situations not foreseen by programmers. AI has a wider latitude of decision-making capabilities than traditional software – whether it is simply helping visitors or performing a task as complex as monitoring a wind turbine to predict its maintenance.
Read more: Conversational AI: Reimagining Customer Experiences
How To Identify If Your Business Needs AI?
AI software and tools can make business processes much simpler and more effective. Besides, implementing AI in business ensures cybersecurity defense, powers customer service, and more. But how do you know when you must adopt AI in business? Here are a few scenarios:
Scenario 1: Do you need to enhance your customer experience?
Are you struggling to provide your consumers with quick, easy, and personalized solutions? AI-powered digital assistants can help your business resolve customer queries by imitating human conversation. Chatbots are among the most promising trends in customer engagement and customer experience. Perhaps most business owners realize how imperative this AI technology is to their business. Perhaps that is why the chatbot market is set to reach 1.25 billion USD by 2025.
Scenario 2: You know the value of sentimental analysis but do not know how to leverage it.
Businesses use sentimental analysis to monitor and analyze customers’ opinions and emotions from various texts on a website, social media, and product or service comments. Skimming through large amounts of data to churn out customers’ sentiments can be daunting. All thanks to AI-assisted sentiment analysis, you can now quickly understand how your customers feel about your services or products.
Scenario 3: Your business has suffered due to inaccurate forecasting.
Accurate sales forecasting helps businesses predict future sales for long-term business growth. It can also enable the detection of potential problems to avoid them. Implementing AI-based CRM software can help detect how each data element relates to sales performance.
Scenario 4: You have a great online presence but an awful in-store experience.
If that describes your business, it is time to adopt AI to provide the next level of a personalized in-store experience. AI can enable instant access to products or services and contribute to smarter buying decisions.
A Quick Guide to Implementing AI For Your Business
AI applications can be used in many ways depending on organizational needs and the business intelligence (BI) insights derived from the data collected. Here are some tips to explain the steps businesses can take to ensure their implementation is a success:
1. Know your options.
Find out your options and what AI can and cannot do. This will help you decide if you want to add specific AI technology or change the entire app.
2. What is your business goal?
Working on an ‘end-first’ process will help refine the list to select specific features or capabilities that best suit your business goals.
3. Find out how AI can benefit the end-users
This is crucial as it gives you the two main objectives for a successful implementation. Then, choose the software and hardware you need to make this process a reality.
4. Evaluate your internal capabilities
You need to consider if you have enough skilled employees in-house who can manage the process and if you have the budget to outsource it.
5. Choose between building or integrating the system
Remember building an AI system from scratch can take several months. On the other hand, if you choose to use a premade system, your AI partner will help install the software app, train your staff, and fulfill your business needs.
6. Test system
Testing the system for a predetermined time will help you understand if the clients are more satisfied, and if the employees work more efficiently.
7. Choose the right partner
A good AI partner will be clear about the offer, value, and terms of cooperation.
8. Make refinements
After you gather a reasonable amount of data evidencing the success of an AI solution, you can start making refinement changes to the solution.
Watch more: How Artificial Intelligence Can Enhance Your Customer Experience!
Avoid 4 Common Mistakes While Implementing AI
A well-considered plan can lead to success, but a mistake can cost you considerably in terms of time and resources. Here are four common mistakes to watch out for when implementing AI:
- Not applying AI to the right use cases: If AI is incongruous with your business goals, your time and resources will be wasted
- Not diligent in hiring the right talent: Hiring the right AI team is like putting together the right football team that can win. Hire candidates with specialized skill sets and experience that match your business needs.
- Ignoring data: Ensure all teams are responsible for organizing, vetting, and maintaining data.
- Inadequate intervention: Inadequate intervention could result in AI recommendations that hinder business objectives. Hence, ensure interventions are scalable and repeatable.
How Fingent Can Help You With Personalized AI Software Development
Artificial Intelligence is for every future-oriented business. How exactly you will use AI depends on your business goal and how well it was implemented. At Fingent top custom software development company, the AI developers are equipped to design intelligent solutions to help solve your business problems, automate tasks, and improve customer experience.
Our suite of AI solutions includes data capture and processing. Our AI developers are also proficient in analytics, multi-platform integration, and ML solutions.
Let us help you reach your business goal with intelligent AI-driven solutions. Give us a call today.
Customer Experience – Two words that could make or break your business.
Today, customers expect businesses to provide nothing short of an excellent customer experience whenever and however they shop. This is going to be the main differentiator between you and your competitors. The race to own customer experience is on!
Some businesses are learning this the hard way, but you don’t have to. The solution is right here – Technology. Through this article, we want to help you understand how technology can improve customer experience. We will also discuss top technology trends to help your brand beat the competition.
But first, let us explain why customer experience matters.
Does Customer Experience Matter?
Did you know that 66% of customers expect companies to understand their needs and expectations?
Gone are the days when an unhappy customer used to complain directly to the brand. Today, they choose to complain to the rest of the world through social channels such as Twitter, Facebook, Instagram, and more. Creating a powerful and memorable customer experience is more complicated than ever in such a scenario.
While that is true, it is also true that these customers share positive customer experiences on these platforms as well. 71% of customers recommend a product or service just because they received a “great” customer experience.
As a brand, you may define your brand’s promises. However, the customer decides whether or not your brand delivers on its promises. According to market research by Gartner, customer experience drives over 60% of brand loyalty.
To satisfy customers, most businesses hire and train good people. But that is not sufficient. They need tools that will help them deliver a top-notch customer experience and make them want to come back to you. Using technology for customer experience can build your brand through satisfied customers.
That takes us to the next intriguing question: How does technology improve customer experience?
How Does Technology Improve Customer Experience?
Technology for customer experience gives customers unlimited access to information, allowing them to demand products and services whenever they want. As the speed of technology to enhance customer experience accelerates, businesses must evolve quickly. Brands that use technology to enhance customer experience will thrive, but you can be sure that those that are slow to react will not survive.
Here are three key ways in which technology enhances customer experience:
1. Increased opportunities
Using smartphones, customers can research products, raise queries, and purchase products or services no matter where they are and what they are doing. A study revealed that consumers in the UK spend over 22.8 billion pounds per year on online shopping while using public transport.
With consumers becoming hyper-connected, businesses need to leverage increasing opportunities to engage new and existing customers. Technology can help companies integrate all marketing channels to deliver a cohesive customer experience irrespective of their channel. Technology can help you use customer data effectively to deliver seamless experiences.
2. Reach every audience segment
According to a Google report, 90% of online shoppers use more than one device to shop. A shopper may use one device to search for a product and another to check the pricing and complete the purchase.
Businesses need to be available with the right messaging at the right time. Technology for customer experience will help you reach your customers on any device. Technology can enable you to provide contextually relevant experiences that engage customers in the right place, at the right time, and with the right message.
3. Communicate better
Most customers switch brands because the purchasing process is too difficult. Technology offers solutions to reach customer demands. AI-powered chatbots enable your brand to communicate better with your customers.
Since chatbots provide detailed records of conversations with customers, you can use that data to analyze to reveal insights on consumer pain points. You can use these insights to improve products and services.
Top Technology Trends That Improve Customer Experience
1. AI chatbot
AI chatbot is restructuring the way brands communicate with their customers. These conversational AI chatbots are responsible for creating a personalized customer experience, making sentiment analyses, and more. Consider a use case:
Fingent helped one of the oldest state universities to develop an AI-driven ecosystem that allows students to interact with an AI chatbot (teaching assistant). These are built to be trained and allow instructors to upload the content that students need. These chatbots can manage student queries and allow for keyword and tag searches of teaching material.
2. Virtual reality
Virtual reality is a game-changer enabling customers to educate themselves about your company. Plus, VR redefines how your sales reps understand customers, increasing their empathy and enabling them to suggest better solutions to their issues.
Fingent recently built a highly interactive visual medium to enable medical students to quickly gain efficiency in stand medical procedures.
3. Augmented reality and 3D configuration
Augmented reality is considered a boon to improving the digital customer experience. It gives customers a clear picture of your product, helping in quicker purchasing decisions.
Fingent helps build interactive mobile apps that enable 3D purchase decisions. It also develops agnostic web solutions for eCommerce to better use AR capabilities.
Fingent- A Perfect Partner to Create Custom Technology Solutions To Enhance Customer Experience.
The impact of technology is a powerful catalyst for change, and the speed of that change is getting faster and faster. Fingent can help you identify technology trends and capitalize before it is too late.
You must acknowledge and meet consumer demands for your business to increase market share and stay relevant. Marrying customer service and technology can drive customer delight.
Fingent brings you deep expertise in experience strategy and design, harnessing best-in-class solutions. We can help you drive transformation across the customer lifecycle, sales, marketing, and more.
Fingent top custom software development company is equipped to provide support across channels. Our quick and easy setup allows you to cut time and lower costs. With the help of AI and automation, we can route your tickets to the right agent and boost customer satisfaction. Find out more about us and chat with our experts to see how this can be done.
5 Advanced Business Technologies You Should’nt Miss Out When Strategizing Brand Value and Competency!
The strategic significance of advanced technologies as a critical business component is recognized by enterprises like never before. Besides business modernization and cost reduction, advanced technologies allow you to compensate for labor shortages, improve brand value and competency, and expedite research and innovation processes. However, several companies jump onto the bandwagon without properly understanding the practical applications and benefits of advanced technology in their business. Only 23% of small and medium-sized enterprises (SMEs) worldwide can invest in and grow with new digital tools, indicates the World Economic Forum. This data proves why companies should analyze advanced business technology examples before adopting digital tools.
Read more: Using technology to build customer trust: Your business plan for 2022
To simplify your understanding, here’s a quick rundown of five advanced business technologies we believe will help you cope with the new business and economic environment.
- Simplifying Workflows With Cloud
- Low-code Applications
- Robotic Process Automation (RPA)
- Document Data Extraction
- AI Assistants
As these business technologies become more affordable and handy, businesses are ardently pursuing them to automate customer service, streamline workflows, differentiate products and services, and reach new markets. Depending on your budget, implementation timeline, priorities, and unique business requirements, our team at Fingent helps you build the roadmap for technology adoption.
Let’s take a closer look at the five inevitable technologies for business transformation today:
Read more: How to gain maximum value from your technology investments?
1. Simplifying Workflows with Cloud
Workflow management is a highly overlooked enterprise strategy that directly impacts productivity. Managing different stakeholders, heaps of confidential data, and a series of preset and conditional tasks manually can lead to several errors such as employees missing key steps, policy violations, compliance issues, and monetary losses. By taking your workflows online, cloud-based workflow management applications increase your productivity.
Cloud-powered workflows or workflow management tools:
- Are scalable, centralized, customizable to your needs, easy to integrate, secure, reliable, and hassle-free.
- Offer a seamless and unified collaboration interface by preventing users from toggling between different messaging apps or communication channels.
- Reduce your dependency on in-house IT team by passing on the software maintenance responsibilities to the third-party software vendor.
- Can be accessed via any authorized network (with approved access credentials), on any device, from anywhere, 24/7. This has been a huge game-changer for several companies that switched to remote operations during the pandemic.
Example of a Cloud-based Workflow Tool
Finding a cloud workflow management tool that can be customized to your company’s requirements is daunting. The platform should integrate well with your organizational processes without disrupting your existing workflow. This is where digital workplace applications like InfinCE make the difference.
With InfinCE Digital Workplace, Fingent has improved its productivity by 20% through real-time, effective, and easy collaboration. Data-powered dashboards, dedicated servers, collaboration apps, productivity tools, virtual desktops, private mobile apps, and a host of exceptional business management features enabled us to achieve a significant operational breakthrough in streamlining workflows.
Read the full case study here.
2. Low-code Applications
Gartner estimates that by 2025, 70% of enterprise applications will use low-code or no-code technologies. Digital business transformation requires pushing custom software solutions to the market at lightning speed. This demand has given rise to low-code applications that will break the technological and organizational silos of application development, automation, integration, and governance. Low-code development enables business users to bring innovative ideas to life by just dragging and dropping low-code elements through a graphical user interface.
In simple words, low-code development enables “citizen” developers or non-tech users (such as business analysts or marketers) to build dashboards and survey or contact forms faster. Professional developers, on the other hand, can leverage low-code techniques to perform more efficient tasks such as legacy application modernization or back-end integrations with improved agility and velocity.
Use Cases for Low-code Applications
- Customer engagement applications and portals
- Mission-critical applications such as ERP software, payments manager, etc.
- Data analysis applications, BI dashboards, and data management software
- Mobile apps for customer engagement
- Order processing, inventory, order fulfillment, supply chain, and accounting apps
Salesforce Lightning, Microsoft Power Apps, and Zoho Creator are some of the leading low-code applications today. SAP users can leverage the unified low-code/no-code (LCNC) solutions on SAP Business Technology Platform (BTP) to rapidly build and extend applications, and automate tasks and processes.
3. Robotic Process Automation (RPA)
Robotic Process Automation (RPA), often referred to as software robotics, is an easy-to-use software technology that allows anyone to automate digital tasks within their business processes. RPA allows users to create software robots or “bots” that can learn, emulate, and then execute rules-based business processes. According to Forrester Research, RPA software revenue is expected to reach $6.5 billion by 2025, while RPA-related services revenue could hit $16 billion in the same year.
Potential Use Cases for RPA
We offer free proof of concepts to help you understand how RPA can improve your business efficiency and customer experience. Some of our top use cases include:
- Automating discharge protocols and data management to increase HR productivity in healthcare.
- Daily retail process automation such as order processing, inventory and warehouse management, etc. to save time and resources.
- Reducing customer wait times through RPA-enabled chatbots that answer customer queries in real-time.
- Error-free, automated billing and invoices to keep your financial systems and reports up-to-date.
- HR teams can automate the maintenance of personnel data and records, streamline onboarding, and manage payroll seamlessly.
Download our white paper to learn more about how Robotic Process Automation can simplify your business operations
4. Document Data Extraction
Extracting quality data out of unstructured or poorly structured data sources and documents for further processing, migration, and storing has been a biggest obstacle in automating back office operations. If you are entering structured invoices to a robust ERP tool like SAP, your payments can be automated and system records can be generated automatically. Due to the high costs of data extraction, several businesses extract only critical information fields, for example, the payment field within an invoice. Businesses are compelled to manually extract data from other important fields, such as validating the invoice’s compliance with VAT.
AI-integrated OCR Software for Document Extraction
Optical Character Recognition (OCR) is an affordable, game-changing technology that automatically extracts data from the digital images (photos) of large files, scanned documents, and sub-titles or captions superimposed on an image. It reduces the time spent in manual data entry and extraction by automatically converting typed, handwritten or printed text into machine-readable text. AI-powered automated data extraction tools like DocuSign, Docsumo, Kofax Capture, and Amazon Textract leverage OCR technology to reduce the chaos involved in document data extraction and enable businesses to create an efficient workplace.
Our team helps customize document data extraction software that can save your time and money by eliminating transcription and transposing mistakes.
5. AI Assistants
One of the most common examples of small business automation today is the use of AI-powered virtual assistants. They can save your employees’ productivity by automating the most repeatable customer interactions, such as technical support, appointment scheduling, lead qualification, and order management. AI virtual assistants like Google Assistant and Alexa can understand and act according to your voice commands and customize responses to your queries. Understanding customer intent through natural language processing and recognition allows AI assistants to maintain a human-like conversation.
Chatbots are a popular category of AI assistants that are designed specifically for text-based channels like SMS, email, and live chat. Recent years have witnessed a rise in chatbot adoption among several business verticals, product and service lines, websites, mobile apps, customer portals, and so on. Data shows that 58% of B2B companies and 42% of B2C websites are using chatbots to make their websites and mobile apps more interactive. More than 56% of businesses believe chatbots to be driving digital disruption in their industry.
Case Study: AI Virtual Assistant for HR
Fingent’s HR team was pressed to transform their service delivery model as routine, transactional tasks affected their performance and efficiency. To solve their struggle, Fingent developed MUSA, an AI-powered virtual assistant (a chatbot) and integrated it with Fingent Hub, Fingent’s internal employee management system. MUSA is short for Multi Utility Assistant. Employees can ask MUSA any queries related to HR and IT DevOps processes at Fingent, and they’ll get answered instantly. MUSA has improved our HR team’s response time by minimizing their workload and allowing them to focus on areas requiring more attention.
Read the full case study here.
Business and Technology Are Inseparable
Gartner writes that businesses leading with technology employ advanced tech to boost their customer experience and revenue growth, have a clear understanding of their priorities, goals, and strategies, and invest in solutions tailored to their needs. Technology allows businesses to lower the walls within and between their organizations, customers, providers, suppliers, and so on. Organizations perceiving technology as a key business consideration will be able to match the pace of business change and stay relevant and competitive.
How can your company embrace growth in a new era of transformation and business technology trends? If you feel you’re getting caught in the technology maze, take a quick break to contact us.
Our consultants can simplify your technology adoption strategy based on your priorities, customer needs, financial resources, and technical requirements.
Old is gold … but is it? There are some things that get better with age of course, but when it comes to software, it’s a hard NO.
Business after Covid is not the same as when you started it. So, using legacy software to run your business is like using bullock carts for transportation even when bullet trains are available.
True, there are some systems that are hard to be replaced. On the other hand, there are some that need to be modernized or even completely scrapped. One of these is legacy software. Nevertheless, the modernization or replacement of legacy software is not always defined by its age. It might be that it is no longer relevant to the current business strategy and goals. When such software becomes difficult to maintain and improve, it is time to pivot to the platform ecosystem.
This article discusses the benefits of pivoting your legacy software into a platform ecosystem. Before that let’s understand when and how a company should consider pivoting to the platform ecosystem.
Let’s start by understanding what a platform ecosystem is.
Read more: 5 Ways Application Modernization Enables Your Business to Grow and Reap ROI During a Pandemic
What Is Platform Ecosystem?
A platform ecosystem is a connected system of companies that share large amounts of data with a common goal. When executed well, it has a massive impact on solving societal challenges successfully establishing and launching a viable ecosystem.
When Should a Company Consider Pivoting to AI-enabled Platform Ecosystem?
Legacy software may have been useful in the past. Today, you no longer see enough ROI. The longer you allow it to interfere with your business, the more resources you will have to devote to keep your current system functioning.
After all, any company would expect to profit while ensuring to invest in the right places. Recognizing the obvious downsides will help you understand when and why you must pivot to the platform ecosystem. Here are three examples that increase the cost of running legacy software:
1. Maintenance cost
Overhead cost: When your legacy software needs constant patching and repairs, your overhead costs can increase exponentially.
Human resource: If your team spends most of their time on maintenance, they will be distracted from higher-value projects that can contribute to increased ROI.
2. Cost of Integration
Integrations: You may feel tempted to look for workarounds that allow your system to work with current software and hardware. This can lead to reinventing your entire system. Essentially, you will be left with a lot of new patches on the old system that can increase your integration cost and maintenance costs.
Equipment: You will have to retain some of the old software and hardware because of compatibility issues. Maintaining such old equipment also can increase your cost in terms of money and human resources.
3. Cost of brand image
Customer retention: Because legacy software may become cumbersome and slow for today’s fast-paced customers, they may move on to your competition. These customers may include some of your loyal customers who lose patience. Gradually, such loss of customers will diminish your market share.
Brand reputation: Cumbersome legacy software can change the way your existing customers and the general public view your brand. Remember, if it costs your reputation, it will cost your business!
Read more: Why modernize your legacy systems. What is the best approach?
Steps to Pivot Your Legacy Software
Steps to pivot legacy software to a platform ecosystem vary from business to business. But there are common threads in how they can approach this journey. The companies wishing to grow with AI-enabled platforms must carefully assess and plan the transition. Doing so will ensure long-term success.
1. Assess and document your current software
Analyze and document how your current software fails to meet your business needs. Such analysis will help you understand what you need.
Create a journey map to visualize the UX and CX of your legacy system. Find out how your partners, customers, and stakeholders are using your current system.
This is a preliminary step so do not rush through your assessment. A thorough review now can provide you with a clearer picture of your journey and save you much time and resources during the journey.
2. Find out the right strategy for your organization
Some of the strategies you could consider are replace, rebuild, rehost, and re-platform. The right strategy depends on various factors including the expected ROI, the timeline, and more. It is important to get your stakeholders involved in this step.
3. Access to partners’ data
Access to partners’ data plays a huge part in driving value. Ensure to include access to partners’ data. Also, ensure this relationship comes with the ability to use AI models like customer matches and recommendations.
4. Create an interface and a timeline
Ecosystem partners need access to AI data and decisions. This is made possible by creating an API architecture. API network allows providers to interface with the company.
When mapping out your journey, factor in the time you will need to locate any other resources and the current projects your team is working on.
5. Identify and gather
Most decisions are made by AI. Hence, Identify the key decisions that you would want AI to make and then use that data to train the models.
6. Design and implement a smooth process
The frictionless platform model can simplify the process for your customers. Work with your partners to design and implement a seamless process that meets your customer needs.
7. Data is power use it wisely
The machine learning process will continue to improve as they make decisions, and they will get better at predicting or recommending. Retrain them as soon as you source new data. You can also train them when you notice that they are not doing their job very effectively.
8. Begin implementing your project plan
Once you start implementing your project plan, ensure to keep all lines of communication open and clear. Sharing information across the team about changes will help prevent problems.
Advantages Of Pivoting to Platform Ecosystem
The primary value of the platform is to grow your business. It is also useful for gathering data to train AI models. Each new member of the ecosystem provides more value to the network and more data. As result, you will have better AI models.
Data powers AI-enabled decisions in order to quickly and efficiently process claims for your customer. In a platform ecosystem, companies work together towards a common goal. They create value for each other and their customers. Clearly, new technology delivers a bigger return than keeping the existing software. At Fingent, we work with our clients to make this transformation smooth and seamless.
Give us a call and allow us to help you effortlessly pivot your legacy software into a platform ecosystem.
The popularity of edge computing and artificial intelligence (AI) has risen in recent years due to the widespread adoption of mobile technology and the Internet of Things (IoT) by various industries. The Linux Foundation’s State of the Edge Report 2021 predicts that the global market capitalization of edge computing infrastructure would reach $800 billion by 2028. If edge computing garners a wider attention span, the number of enterprises investing in AI is also growing year over year. According to the State of AI 2021 Report, the global AI funding witnessed a whopping 108% increase in 2021. More than 54% of the organizations surveyed by McKinsey in 2021 said that they have adopted AI in at least one function.
Individually, both AI and edge computing help businesses in incredible ways and hold immense potential for future development. Many forward-looking organizations are investing in these two technologies as part of their digital transformation journey. “Two heads are better than one”, goes the saying. True to this, many enterprises and technology champions are discovering new opportunities by combining edge computing and AI, or Edge AI. In this blog, we’ll see how edge computing and AI are being put to work together and discuss some use cases that will take AI applications to the edge.
Read more: Future-proof your business with 5G, edge computing and cloud
What is Edge Computing?
Edge computing refers to a distributed computing framework that brings the deployment of computing and storage resources closer to the data sources, such as local edge servers or IoT devices. By bringing enterprise applications closer to the data sources, edge computing offers a multitude of business benefits; including faster data processing and insights generation, better response times, and enhanced bandwidth availability.
In edge computing, all your device-generated data is processed and analyzed close to the source where it’s created. By preventing your data from traveling over a network to a centralized or cloud data center, edge computing reduces latency and improves bandwidth availability.
Example: Electric vehicles (EVs) leverage edge computing for data aggregation and insights generation, which help optimize charging stations and monitor the health of EV batteries.
Read more: 9 examples of artificial intelligence transforming business today
What is AI?
Artificial Intelligence or AI refers to machine intelligence, where a computer-controlled (software-programmed) machine simulates human intelligence to perceive its environment and take corresponding actions that help the machine achieve its goals. AI uses machine learning and deep learning techniques to churn robust input datasets (labeled training data) and enable rapid problem-solving.
The content recommendation systems used by Amazon, Netflix, or YouTube and Google’s advanced web search engine are some of the leading examples of AI today. The growth of artificial neural networks and deep learning technologies enable AI systems to process massive amounts of data at an incredible pace and predict future states with exceptional accuracy.
AI-powered applications command a larger share in today’s enterprise landscape. AI helps banks, insurance companies, and financial institutions with fraud detection. AI is being used by conversational bots to enhance customer service. Smart assistants like Siri and Alexa leverage AI to improve customer experience. Hospitals and healthcare providers use AI-embedded applications for making clinical decisions and delivering remote patient care.
Case Study: MUSA, Fingent’s AI-powered virtual assistant minimizes day-to-day workplaces struggles related to PeopleOps and DevOps. Read Now!
Edge AI: The Next Wave of Enterprise Digital Transformation
AI applications give the intended results by relying on seamless data transmission and computation of complex ML algorithms. Edge computing helps move AI systems close to the source where the data is generated. When AI computation is done at the edge of the network, next to the data source, it gives more accurate and desired results. This process has given rise to a new computing paradigm: Edge AI.
In edge AI, both data generation and computation take place at the network’s edge, instead of sending and processing data in a faraway cloud computing center. Here, “edge” of the network could connote anything – mobile devices, retail stores, factories, hospitals, medical equipment, traffic lights, autonomous vehicles, and so on.
Read more: Quantum vs. Neuromorphic Computing: What Will the Future of AI Look Like?
Here’s how your business can benefit from the adoption of edge AI:
1. Low-power, offline capabilities
Traditional AI applications require enormous amount of processing and computational power to operate some of the complex ML algorithms. Distance from the cloud servers often affects the deployment of AI systems in remote locations. Edge computing helps overcome this challenge as the technology is designed to operate in low-power, offline environment. For instance, blockchain and smart contracts that rely on decentralized ledger technology (requiring no central broker or mediator) can independently run on computation-heavy AI algorithms within the edge devices.
2. Faster computing and real-time insights
Edge AI enables your applications to respond to users’ requirements in real-time. This is because edge computing analyzes data locally, close to the source where it’s generated, instead of a remote cloud data center, which usually delays responses due to long-distance communications.
3. Better data security
If AI ensures the privacy of data that needs to be analyzed by securing if from getting exposed to cyber miscreants, edge AI adds an additional layer of privacy by containing that data locally. Edge AI uploads only the insights and analysis to the cloud and even anonymizes the data uploaded for training purposes to protect user identities. Thus, edge AI enables businesses to ensure data regulatory compliance.
4. Constant improvement
AI models can improve their accuracy when they get access to more training data. When an edge AI application confronts data that it is unable of processing, the application will upload the data so that it can retrain and learn from it. Since the new data set is captured right at the production edge (without any transmission delays), the edge AI application will quickly learn from the new data, ensuring constant improvement through learning.
5. Cost reduction
Offline capabilities and decentralization enable Edge AI to process data without larger internet bandwidths. This reduces your networking costs significantly. Enhanced performance of AI-enabled applications keeps your operating costs down.
Potential Use Cases of Edge AI
The rapid growth of intelligent applications and the increasing enterprise workloads on cloud are driving the adoption of edge AI. The edge AI software market is estimated to be worth $1,835 million by 2026, states a recent study. The amalgamation of edge computing and AI has led to many breakthrough advancements in recent years. Here’re a few potential uses cases of edge AI:
Healthcare
AI-powered medical devices and instruments at the edge deliver on-demand insights for clinicians to make crucial and faster decisions about patients. During surgical procedures, surgeons can rely on the ultra-low latency surgical videos streamed into AI-powered medical data processing applications to quickly detect abnormalities and identify chances of excessive bleeding. Devices out of the operating room, such as CT and MRI imaging scanners, DNA sequencers, cryo-electron microscopy, and other life science instruments also benefit from edge AI.
Energy and utilities
Edge AI models can leverage past insights, weather patterns, grid conditions, and other crucial meteorological information to create advanced simulations that help define new ways to improve the generation, distribution, and management of energy resources. This facilitates intelligent forecasting in the energy sector, which helps prevent discontinuous power and energy supply affecting the day-to-day lives of people.
Manufacturing
Edge AI applications can collect data from sensor-enabled devices installed across the factory floor and process the same in real-time, with ultra-low latency. This advantage gives rise to new use cases in manufacturing and distribution, where real-time and rapid data processing is required. Examples include detecting workplace hazards, finding product defects in assembly lines, flagging machines that require attention or human intervention, and more.
The list of edge AI use cases keeps growing every day. Smart virtual assistants, voice commands that replace text-based searches, autonomous vehicles, self-driving cars, video surveillance, motion detectors, and industrial IoT security are a few typical use cases that could be enhanced through the integration of edge AI. Fingent helps build faster, reliable, and cost-effective enterprise applications powered by edge and AI.
Are you ready to explore the possibilities of Edge AI in your business operations? Contact us today!