Tag: Artificial Intelligence

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.

Watch more: Take a look at how Fingent helps leading businesses thrive with 3d Web Configurator and other AR/VR 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.

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!   

There couldn’t be any better empirical evidence than COVID-19 to prove the transformational impact of AI on healthcare. Had AI not been there, it would be unviable to develop and distribute vaccines at record speed, empower public health officials and front-line workers, support equipment manufacturers, take critical life-saving actions, and respond to these abnormal times. 

Leading pharmaceutical company Moderna relied on automated processes and AI algorithms to rapidly bring out their covid vaccine nominee for its first clinical trial. From an anticipated 15% chance of success, AI helped the pharmaceutical company lift their success rate to a whopping 50%, placing the vaccine efficacy levels close to 94.5%. AI’s role in healthcare isn’t limited to pharmaceuticals alone.

In this piece, we’ll see what AI holds in store for healthcare now and in the coming years.   

Read more: AI in Medicine – Yesterday, Today, and Tomorrow

Top Applications of AI in Healthcare

Over these years, AI has brought more sophistication into what humans do, particularly in segments like healthcare. Here’re a few AI healthcare transformations currently underway:

1. Allows People to Stay Fit

AI and the Internet of Medical Things (IoMT) have helped launch several consumer health applications and self-health monitoring devices such as wireless-enabled wearables, activity trackers, pedometers, smartwatches, and other physical fitness monitoring gadgets. These healthcare technology applications encourage people to take proactive measures for maintaining a healthy lifestyle and allow consumers to be in control of their health and well-being. Similarly, healthcare professionals can rely on AI to better understand what their patients need. With insightful patient data, caregivers can provide the necessary guidance and support, thereby enabling people to stay healthy.  

Read more: 5 Healthcare Digitalization Trends Crucial in 2022 and Beyond 

2. Early Disease Detection

It’s well established that the early detection, screening, and treatment of cancer can improve outcomes. American Cancer Society is successfully using cloud ML engine on Google Cloud Platform to analyze breast cancer images with 12x improved speed. Advanced deep learning models are being used to detect Diabetic Retinopathy (DR) during the early and asymptomatic stages. This helps save diabetic patients from the daunting issue of irreversible blindness caused by lesions on the retina. The proliferation of consumer wearables and self-health monitoring devices, combined with AI allows doctors and caregivers to detect potentially life-threatening ailments at more treatable stages. 

3. Medical diagnosis 

The market value of global AI in medical diagnostics is estimated to be worth $3988.0 million by 2026. Leading AI platforms such as IBM Watson Health and Google DeepMind Health enable a large number of healthcare organizations to unlock massive amounts of clinical data to boost medical diagnosis. 

Combining machine learning and neuroscience, AI helps build powerful neural networks that are capable of imitating human abilities. Watson can review and store huge volumes of medical data scattered across journals, seminars, conferences, treatment case studies, and umpteen other sources. AI’s ability to ingest enormous amounts of data, decipher images, and discover hidden patterns escaping even the most-canny human eye are expected to significantly transform healthcare in the near future. 

Read more: Deploying Digital Twins in Healthcare

4. Clinical Decision-making

In the past, clinical decision support systems (CDSS) were fed by inaccurate datasets that led healthcare professionals to make flawed assumptions. Diagnostic errors are one of the top reasons behind higher mortality rates and prolonged hospital stays. Thanks to AI, ML, and the growing volumes of real-time clinical data gathered from numerous healthcare apps and devices. Clinical decision-making is now more precise and efficient with the emergence of AI-powered CDSS. 

Sepsis Watch, a deep learning tool installed in the emergency department of the Duke University Health System has considerably lowered sepsis-induced patient deaths. The tool flags sepsis patients who are at medium to high risk, allowing doctors to identify early signs of sepsis. Not only does AI reduce diagnostic errors, it also suggests the best practices for post-surgical care and patient discharge, as well as recommends medications and follow-up checks to optimize patient care.  

5. Medical Research and Training

The average cost of bringing a pharma product to the market is exploding year over year. Manual R&D processes and the time taken to conceive, design, and conduct clinical trials slow down drug production and increase the costs involved. The latest advances in AI help streamline drug research and discovery and reduces the time to market for new drugs. Researchers can use AI-enabled simulations on their devices to explore the impact of new therapies or medicines, thereby reducing the risk of testing in live conditions. 

AI allows training and quick catch-up sessions to be held from anywhere, even after a medical resident leaves the campus post a tricky clinical case. AI-powered chatbots can answer queries on the fly, at any hour of the day. With instinctive AI diagnostic support and a low level of supervision, the next generation of medical students will definitely rely on automated self-learning platforms. 

Read more: How Virtual Reality Improves the Standard of Medical Education and Training

Most-anticipated AI Innovations in Healthcare!

Real-time data, technological advancements, and innovation are driving the industry forerunners to discover new AI opportunities in healthcare. Here’re a few healthcare AI innovations to behold in the coming days.

1. Address the Shortage of Physicians

Google is running experiments to develop transformative AI imaging and diagnostic tools that can assist clinicians and even address the dearth of talent in a possibly grueling situation (like the global pandemic). Further research is being held to improve the detection of breast and lung cancer, sight-threatening eye conditions as well as skin diseases.   

2. Genomic Analysis

Research proves that 30% of individual health effects are congenital. All of us carry 4 to 5 million genetic variants, each of which can influence our health traits. The cost to sequence a genome and poor sequencing data have marred genomic analysis in the past, preventing clinicians from identifying genetic disorders and high-risk diseases at an early stage. Deep neural networks such as DeepVariant exhibits top-class accuracy in analyzing genetic variants and sequencing genome data. 

3. Decentralized Clinical Trials

The advent of AI is helping medical researchers and pharma companies worldwide to reduce in-person assessments in clinics. Various digital endpoints, such as smartphones, healthcare software, wearable sensors, EHRs, video conferencing, and numerous physical fitness monitoring devices are being used to gather data with the patient’s consent. This has drastically shifted medical trials from clinics, thereby reducing the risk of compromised immunity, exposure to fatal viruses, respiratory or cardiac malfunction, and other lethal health risks. Decentralized clinical trials allow institutional and federal health boards to review existing processes, implement new regulations quickly, listen to feedback and concerns, take proactive steps, and make healthcare more accessible to everyone.    

AI is Pivotal to Healthcare New Normal

Necessity commands invention. Over the past two years, we saw how healthcare stakeholders around the globe took efforts to harness AI technologies – for discovering new drugs, extending the capability of existing drugs, reducing the time to distribution, screening for COVID-19 symptoms, supporting clinical decisions, automating hospital operations, and so on. Key U.S. healthcare decision-makers surveyed by Intel stated that their trust in AI in processing medical records has increased by 67%. As AI gets infused into more crucial areas of healthcare, it’s important to earn customer confidence and comfort, and support from various stakeholders in the ecosystem.   

Fingent helps develop innovative, AI-integrated, custom healthcare software applications to improve your competitive advantage, time-to-market, ROI, and clinical precision. As the world enters a new era of health, it’s important to choose the right technology partner that helps adopt the right technology at the right time. We have an eminent list of healthcare clients, including NHS, Novita Healthcare, Mundipharma, and Casenet, LLC among others.

Contact us to understand how we’re helping businesses build trust and deliver sustained outcomes by making the most of our experience and technology. 

Language gives power. Using NLP (Natural Language Processing), conversational AI gives businesses the power to stay on top of the game.

Why can we say that?

Today, digital-first marketing is a growing trend and conversation is the defining element of a digital-first customer experience.

Is your mind racing with questions like what is Conversational AI? How does it work? What are its benefits? Can my business benefit from Conversational AI?

Well, this article answers each of those questions. By the end of this article, you will understand all you need to know about conversational AI.  

What Is Conversational AI

Conversational AI is a subset of Artificial Intelligence. It uses Machine Learning (ML), Natural Language Processing (NLP), neural networks, and speech recognition technologies to mimic human conversation. Conversational AI can empower businesses to automate highly personalized customer service resolutions at scale. This makes the customer’s experience unique and relevant while reducing the effort and resolution time of the company. As a result, you have happy customers who stay loyal to your brand. 

Conversational AI is becoming one of the most popular technologies. The global conversational AI market size is expected to grow at a CAGR (Compound Annual Growth Rate) of 21.8% by 2026.

This unique technology is used to engage customers in services such as support, marketing, helping a prospect enter a funnel, and even sales. Conversational AI will make brands more human and help engage with customers more personally. 

The most common use of conversation AI experience is through voice assistants. This allows brands to participate in direct and uninterrupted conversations at scale.

Read more: Capitalizing on AI Chatbots Will Redefine Your Business: Here’s How!

How Does It Work?  

As mentioned earlier, NLP is one component that enables conversational AI. It is an umbrella term that includes NLU (Natural Language Understanding) and NLG (Natural Language Generation).

Human language is complex. People can say the same thing in many different ways. However, a computer can decipher customers’ intent with the help of natural language understanding technology. It looks at the context of what a customer said to accurately understand what a person needs. Leveraging NLU can enable conversational AI to understand grammatical mistakes, abbreviations, slang, and misspellings just like a human would.

Once it understands what a customer wants, ML is used to determine the appropriate response. Over time, conversational AI learns which response is the best and improves its accuracy. 

Finally, NLG creates an easy-to-understand reply that’s as human-like as possible. Advanced conversational AI can use contextual awareness to remember bits of information to facilitate more natural conversation. 

How Does Conversational AI Benefit Different Industries?

Conversational AI technology has substantial benefits for businesses across industries. Here are the most important benefits:

1. More engaging and easy interactions

Reading dry FAQs can be boring and may drive your potential customers to your competition.  On the other hand, having the choice to take part in a conversation can be more engaging and has the potential to convert your leads. 

Because conversational AI can use past interaction history or other relevant data, it can personalize each customer interaction. It spares the customer the trouble of searching through multiple pages to find answers to his questions.

2. Higher customer satisfaction

Conversational AI allows industries such as healthcare and hospitality to provide real-time information to their end-users. AI-powered chatbots can be accessed more readily than live support. Such quick support helps avoid long waiting times improving customer experience. Improved customer satisfaction can impact customer loyalty and referrals. 

Read more: 5 Leading Chatbot Use Cases Explained with Real-life Examples

3. Greater support with minimum cost

Customer care costs have a high impact benefit on finance industries. Conversational AI can help keep customer care expenditures in check. It can improve overall efficiency and productivity by handling routine issues much faster. These bots can also reduce customer support tickets.

They can deflect the number of routine tickets sent to human agents and boost team productivity. Chatbot templates can be used to collect information and help resolve clients’ queries faster. AI-powered bots provide relevant information faster and boost the accuracy rate over time. They can learn from past interactions and continuously evolve. 

4. Improved lead generation

Lead generation is the foremost goal of sales and marketing teams in industries such as insurance. Virtual assistants can engage visitors who browse the site and improve lead generation.

5. Increased operational and customer support efficiency

Conversational AI can come to the rescue when a business experiences a sudden rise in the volume of chats. Plus, these chatbots are cheaper and faster than hiring new agents. With automated operations, businesses can focus on other important functions. 

Additionally, conversational AI can determine a customer’s emotional needs and communication preferences from previous interactions. Hence, deploying a conversational chatbot is a wise decision during the holiday season.

6. Increased reach

Conversational AI enables your brand to reach a wider audience as it can understand both verbal and written speech. For example, you can reach elderly and hearing or vision impaired customers who find it difficult to navigate the web.

7. Boost revenue

Conversational AI can considerably reduce website costs.  When properly implemented, a conversational AI chatbot provides live support and assistance 24/7. They can qualify leads by asking predefined sales queries to nurture the lead.

Once the lead fills a form or signs up for a newsletter, the chatbot can analyze the text of the lead and find the most appropriate response. This is especially useful for banking services and increases their revenue. 

Conversational AI chatbots can quickly act on positive user intent and present a service or product that meets their preferences. 

Use Cases

1. eCommerce

Conversational AI helps businesses form customer relationships that last and ultimately sell more products. It can help in cross-selling and upselling products, finding specific products, and placing orders. It can also answer FAQs, make suggestions about the size, and even help with returns.

2. Banking

Conversational AI can be used to provide a simplified and intuitive customer experience. It can facilitate transactions, help with account services, and assist customers to apply for loans.

Among the best use cases of banking are helping find a nearby ATM, assisting with mobile deposits, and sending billing reminders and notifications. 

3. Insurance

Conversational AI can help distribute products, resolve claims, and increase customer awareness and education. It can also manage renewals, and gather customer feedback and reviews. 

4. Healthcare

In many ways, conversational AI can make things easier for patients, doctors, nurses, and other healthcare staff.

It can improve operational efficiency by answering common health questions, booking appointments, and checking up on patients. It can even escalate emergency cases.

Read more: MUSA: Fingent’s AI-powered Virtual Assistant Helps Employees With HR & DevOps Queries

Quick Resolutions, Seamless Conversations

Today, customers expect a quick resolution and seamless conversations when interacting with your business. Conversational AI will assuredly provide personalized assistants that both serve and predict customer needs. 

There is no doubt that conversational AI will continue to evolve into a sophisticated technology. Given that, your organization needs to clearly understand what conversational AI is so you can leverage it and build customer experience around it.

Give us a call, get your business set up with Conversational AI, and get set to reap the rewards.

The COVID-19 pandemic has accentuated the need for resilient supply chains and human-machine collaboration at work. Full or partial shutdowns, as well as social distancing regulations, impose factories and workspaces to operate with the minimal onsite crew. Despite labor shortages, supply chain disruptions, and other production challenges, manufacturers are under constant pressure to respond to the evolving market needs. The demands for mass customization, quality expectations, faster product cycles, and product variability are at an all-time high. Tackling these persistent challenges requires combining human skill and ingenuity with the strength and speed of robots. To bring the best of both worlds – human creativity and robotic precision – manufacturers should adopt cobots (collaborative robots) that can reduce human interaction in feasible situations and accelerate production cycles.
Cobots allow manufacturers to maximize production and address the changing demands while ensuring the safety of their employees, clients, and partners. Why are cobots the future of manufacturing? How do they help build manufacturing resilience? Let’s explore further in this blog.
Read more: What are cobots and how can they benefit industries

Cobots Enhance Manufacturing Efficiency

Collaborative robots or cobots are designed to safely work alongside humans in tedious, dull, and hazardous environments. Unlike the traditional industrial robots that work in fenced premises to avoid close proximity with people, cobots operate in a shared workspace alongside human labor. For instance, a robot that helps humans sort foam chips in a lab is a cobot, while a robot welding a sharp cutting tool in a restricted factory area is a typical industrial robot.
Conventional industrial robots have long enabled manufacturers to leverage automation and compensate for labor shortages, but they are typically designed to execute one specific task. Moreover, they lack the cognitive capabilities possessed by humans to reprogram their operations based on new circumstances. In contrast, cobots don’t require heavy, pre-programmed actuators to drive them. Cobot motions are steered by computer-controlled manipulators, such as robotic arms, which are supervised by humans. Thus, cobots facilitate effective human-machine collaboration at work.
Cobots can be programmed to perform a wide range of tasks in a factory setting such as handling materials, assembling items, palletizing, packaging, and labeling, inspecting product quality, welding, press-fitting, driving screws and nuts, and tending machines. While cobots attend these mind-numbing jobs, human workers can focus on tasks that require immense resourcefulness and reasoning.
Read more: Digital Transformation in Manufacturing 

Benefits of Cobots in Manufacturing 

Modern manufacturing requires effective human-machine collaboration to cut expenses, reduce time-to-market, and address growing customer demands. Here’s how cobots empower manufacturing enterprises.
1. Easy to Deploy and Program
It takes days and weeks to install and program a traditional industrial robot. A cobot, on the other hand, can be set up in less than an hour. They are lighter than conventional robots. With user-friendly mobile applications and customized software, you can swiftly program the cobot to get started. Right software configurations enable cobots to learn new actions, without any specialized training. Using intuitive 3D visualizations or simple graphical representations, you can move the robot arm to preferred waypoints. Your employees can focus on more critical tasks while the cobot takes care of mundane jobs.
2. Flexible to Perform Different Tasks
Cobots can be easily shifted from one workstation to another due to their flexible hardware. With minimal software customizations, cobots can be re-deployed or repurposed to perform different functions across various departments. For example, a cobot that performs picking and packing can be re-programmed as a filler by replacing its robotic arm with a tube and nozzle.
Read more: Challenges, Opportunities, and Technologies That Will Revolutionize Manufacturing 

3. Save Production Cost and Time
A study conducted by the World Economic Forum in association with Advanced Robotics for Manufacturing found that collaborative robots can cut nearly two-thirds of the cycle time required to pack boxes onto pallets. Because cobots are designed to work without any breaks, they reduce the idle time between cycles. The International Society of Automation reports that cobots can save production costs by reducing 75% of manual labor. Traditional robots increase the installation costs for manufacturers as they need to set up additional safety measures around the deployment area. Cobots don’t incur such extra expenses as they can be set up in close proximity to humans.
4. Improve Employee Engagement and Productivity
Cobots work in collaboration with people to refine and process the tasks better. They can never replace the human touch in production. When cobots take care of repetitive tasks such as screwing a bottle or packing medical equipment, employees can focus on more important functions such as running quality checks or inspecting a worksite. It allows manufacturers to optimize their productivity and boost employee morale. Businesses can also prepare their workforces to learn new skills.
5. Maintain Consistency and Accuracy
From the first to the hundredth task, cobots maintain the same level of accuracy and consistency. Humans can get drained easily, whereas a cobot never deviates from the actions for which it is set up. This helps ensure high product quality and uniformity. With the right software and hardware configurations, cobots can produce more finished goods at an incredible pace, faster than handcrafting.

Cobots and The Future of Manufacturing

Industry 4.0 paved the way for automation and smart manufacturing powered by data-driven technologies such as IoT, cyber-physical systems, wearables, AR, cloud computing, artificial intelligence, cognitive computing, and so on. Though the sole focus of Industry 4.0 is to improve process efficiency through physical and digital integration, it accidentally ignores the significance of human value in process optimization. Industry 5.0 re-shifts its focus on human value by fusing the roles of mechanical components and human workers in production. This makes cobots the very foundation of the next wave of the industrial revolution, that is, Industry 5.0.
Denmark-based Universal Robots reports that cobots are at the heart of Industry 5.0. Cobots democratize robotic capabilities, thereby serving as a personal tool that can be leveraged by any member of the workforce to apply creative skills and generate more value. Cobots can be used as a plug-and-play solution across a variety of manufacturing and industrial operations such as automotive production, food processing, chemical plants, medical devices, and kits, among others.
Since they collaborate well with humans in a safe environment, cobots will:

• augment intelligent decision-making,
• drive high-quality products to the market,
• enable mass customization and personalization,
• optimize manufacturing costs,
• generate new job roles (eg: Chief Robotics Officer), and
• boost virtual education to make the most of collaborative robotics.

Read more: How Custom Software Development Helps Manufacturing Industry 

How We Help Manufacturers Leverage Cobots and Other Emerging Technologies

As technology matures, manufacturing enterprises need to build use cases that prove the inevitability of human-robot collaboration. We help develop POCs and use cases that demonstrate how your business can benefit from cobots. Our experts can develop your cobot management software or mobile app from scratch or customize your existing software to address the evolving market demands. Fingent can work along with your cobot hardware manufacturers to develop a robust software orchestration layer that can control the movement of your cobots. We also simplify the training process to help you get started in no time.

Better businesses need better cyber security.
Regrettably, threats to cyber security have become the new norm across public and private sectors. The pandemic affected all types of businesses. If anything, uncertainties around remote working amplified cybercrime. As a result, cyber security’s importance has become more clear now than ever before.
As cyberattacks become more sophisticated, businesses will have to stay one step ahead. Security professionals need strong support from advanced technologies like Artificial Intelligence (AI) to protect their companies from cyber threats.
AI can enable security teams to handle greater and more complex threats than ever before. More specifically, it has proven to identify and prioritize threats. In some cases, AI has even taken automated action to quickly remediate security issues. This article considers how AI can redefine the cyber security needs of an organization.
Before we discuss further, let’s find out the impact cyberattacks can have on businesses.

How Cyberattacks Affect a Company’s Performance and Value 

Protecting a company against cyber threats is costly. It can impact the relationship between your company and your customers.
Unfortunately, cyber threats are never static. Millions are created each year and are becoming more and more potent.
In a survey conducted by Hiscox-Cyber Readiness Report, 28% of the businesses that suffered attacks were targeted on more than five occasions in 2020. Companies have lost millions to such cyber security breaches. Companies like financial services, technology, and energy were hit the hardest.
That is not all. Cyber security breaches have caused several other damages including:

• Outlays such as insurance premiums and public relations support.
• Operational disruption.
• Altered business practices.
• Business’s standing and customer trust.
• Stolen intellectual property including product designs, technologies, and go-to-market strategies.
• Legal consequences.

Read more: Quantum Vs Neuromorphic Computing – What Will the Future of AI Look Like!

How AI Contributes to Cyber Security 

Cyber threats are real and certainly worrisome to businesses. It is important to protect critical digital assets.
However, it takes planning and commitment of resources. With good security operations, you can stay on top of most of the most serious cyber threats. True, there may be smart thieves, but Artificial Intelligence can provide smarter security.
Here are 5 specific ways AI can contribute to cyber security:

1. Robust Zero-Day Malware Detection

Malware is unpredictable. And signature-based tools will not detect attacks that have never occurred before. Given that, is it possible to defend against something unpredictable? Yes!
AI is cable of grasping all the possibilities and finding relationships that traditional security tools would miss. While traditional security strategies have their place in cyber security, they are insufficient to detect and prevent zero-day attacks.
Zero-day attacks are best detected by automatically identifying aberrant behavior and alerting administrators immediately. AI can enable organizations to be more proactive and predictive with their security strategies.
Artificial Intelligence provides visibility and security for an organization’s entire data flow. AI helps organizations gain such visibility by dismantling each incoming file to search for any malicious elements. Simultaneously, it also looks at the user and network behavior and anomalies from expected activities.
Together with ML, AI adapts its behavior to new network conditions, constantly adapting to evolving security conditions. Even those hackers who use modern ML penetration methods cannot be fool AI-enabled cyber security.
We cannot stop security breaches from happening. But Artificial Intelligence helps organizations avoid potential disruptions before attackers wreak havoc.

2. AI Can Safeguard Large Amounts of Data

Whether a company is small or mid-sized, there is a lot of data exchanged between customers and the company every day. This information must be safeguarded from potential cyber threats. Cyber security experts cannot always inspect all the data for potential threats.
AI is the best option to detect threats to routine activities. Because of its automated nature, AI can sift through large amounts of data in real-time and identify any hazards lurking amid the chaos.
Read more: Artificial Intelligence and Machine Learning – The Cyber Security Heroes Of FinTech!

3. AI Takes Care of Redundant Cyber Security Operations

Hackers constantly modify their methods but the fundamental security practices do not change. Plus, they may weary your cyber security worker.
Artificial Intelligence takes care of redundant cyber security operations while imitating the best of human traits. It also does a thorough analysis of the network to locate security flaws that may harm your network.

4. AI can boost response time 

Ideal security is the one that can detect security threats in real-time. The principle of ‘a stitch in time saves nine’ applies here.
Integrating AI with cyber security measures is a sure way to detect and respond to attacks immediately. Unlike humans, AI does not miss a spot when examining your system for risks. Besides, it can detect risks early, thereby boosting response time.

5. Authenticity Protection

Most websites allow users to log in and access services or make purchases. You will need greater protection as such a site contains private information and sensitive material. To maintain customer trust, it is important to ensure all data about your guests remains safe while accessing your site.
Artificial Intelligence can provide an enhanced security layer. AI can secure authentication when a user wishes to connect their account. Login measures like CAPTCHA, fingerprint, and facial recognition are used to determine if the attempt is legitimate or not.
Read more: Safeguarding IT Infrastructure from Cyber Attacks – Best  Practices

Do Not Be Afraid!

Fingent is your reliable security partner. We provide professional security with reliable service. As a proactive security partner, we look ahead to ensure your business is successful far into the future.
Using AI’s real-time monitoring capabilities, we can spot potential issues before they become a major problem. Security experts Fingent are aware that cyber security threats are not limited to work hours. Our professionals here at Fingent will be there for your business whenever you need us.
We are in business today because of the reputation we built with our customers. We offer a unique level of enterprise IT support, and our clients can rest easy knowing that their business is always protected.
Give us a call and let’s discuss your security needs.

AI is not just a technology; it has become part of daily lives. Thanks to AI, we witness new kinds of development in each sphere of life every day. We can access many points with AI now more than we could ever before. From the research that we do on the internet to the goods that come to our doors, AI is directing our lives and business. It has solved many problems faced by humanity. And, revolutionized technology in all industries.
Coined at Dartmouth College in 1956, Artificial Intelligence (AI) gave succeeding generations a potential for information technology that can benefit humans in a profound way. Apart from bringing efficiencies, AI is also bringing new possibilities. These possibilities continue to create new models and opportunities for businesses that tap into them. Quantum and neuromorphic computing is the way forward.
This blog takes a deeper look into quantum and neuromorphic computing and explores which companies can benefit from these technologies.

A Look at The Future Of AI

The possibilities Artificial Intelligence can create are seemingly endless. Innovations are constantly taking place in the AI world. Given that, many business and information technology leaders are looking to better understand how it will affect their business now and in the future.
Taking a look at the future scenarios for how AI could evolve can help IT leaders demystify this emerging technology.  Two such technologies are called neuromorphic or quantum computing. They offer us a new way forward by fulfilling our AI-related dreams. The quantum computing market alone is expected to reach $2.2 billion by 2026, so it’s definitely worth looking into.
The future of AI also depends on improving the capacity of intelligent systems by using powerful hardware. Hardware such as neuromorphic computing and quantum computing will allow companies to build AI solutions that are extremely fast and can encapsulate more data and knowledge.
For example, a virtual assistant may now have the computing capacity to handle one or two products. But with more powerful hardware, it could cover more products. Advantages in this area are ongoing.
Let’s examine these in detail.
Read more: Answering The Top Burning Questions On AI Implementation For Businesses!

A Deeper Look into Quantum and Neuromorphic Computing 

Neuromorphic computation and quantum computing always seemed that they were years away. The fact is commercial neuromorphic chips and quantum computers are in use today. These two new technologies are going to change what looked like a straight path to Artificial Intelligence.

1. Neuromorphic computation

Neuromorphic computation attempts to imitate the way a human brain works. In simple terms, hardware and software elements of a computer are wired to mimic the human nervous system and cerebral system.
The goal of neuromorphic computation is to create devices that can learn, retain information, and make logical deductions just like a human brain does. It also attempts to imitate the human brain by searching for new information.
However, unlike quantum computing neuromorphic computing does is not that demanding. Where quantum computers need temperatures close to absolute zero, neuromorphic computers can easily work in normal conditions.
This increases its practicality and potential to integrate this technology in all kinds of devices.

2. Quantum computing 

Quantum computing deals with the world of atoms and subatomic particles inside those atoms. Unlike neuromorphic computation, quantum computing works on the principle of quantum entanglement.
So, the smaller the computer gets, the more powerful they seem to become. Quantum computing provided powerful new possibilities.
Though it is more complex than traditional computing, quantum computing opens the door to potentially solving very large and complex computational problems. It can potentially deliver a big computational upgrade for ML and AI computing.
Quantum computers will not replace traditional computers. Instead, they will require the support of traditional computers for their specialized abilities.
Read more: Driving Business Innovation and Success Through Sustainability

Industries That Can Leverage Quantum Computing and Neuromorphic Computation

1. Industries That Can Leverage Neuromorphic Computation

a) Aerospace and defense: Neuromorphic computing architecture can help in pattern recognition, event reasoning, and robust decision-making. It can also aid in adaptive learning and autonomous tasking for energy-efficient agile Air Force platforms.
b) Self-driving cars: Similar to space communications, neuromorphic computing enhances self-driving. In imitation of the human brain, neuromorphic chips attempt to think and learn on their own and then adapt their learning to unexpected scenarios on the road.
While conventional computers run commands sequentially, neuromorphic computers process and store data almost at the same time. This makes self-driving cars more energy efficient. It can also help autonomous vehicles learn skills and execute tasks more efficiently.
c) Healthcare: Neuromorphic platforms can be used for the hardware-based implementation of ML methods in treating Chronic Obstructive Pulmonary Disease (COPD) in home-care environments. Real-time analysis of data can be obtained by bringing data from the backend onto a neuromorphic chip.
Furthermore, securing sensitive medical data on a single chip complies better with patient privacy regulations. Since neuromorphic platforms process data near a patient, it offers a large fault tolerance for medical applications.
Moreover, hardware-based neuromorphic systems require less computational power making them perfect for PoC medical devices.

2. Industries That Can Leverage Quantum Computing

a) Aerospace: By considering an exponential number of variables, quantum computing could help determine the optimal alternative for each route. It can also help find the best way to allocate resources so that the crew and passengers are impacted as little as possible.
b) Healthcare and Pharmaceuticals: Harnessing the power of quantum computing can significantly accelerate the timelines of various stages of the pharmaceutical research and development process. It can help life science companies by accelerating the speed of the pre-clinical phase and reducing the cost of drug development.
c) Finance: Quantum computing will be able to help solve the problems of customers in finance institutes. It can optimize investment portfolios and financial derivatives. It can also enable the institutions to accurately characterize anomalous transactions and rapidly detect fraud.
d) Chemistry: It is likely that quantum computing can be applied to simulate the properties and behavior of new molecular structures in chemistry. It can address the probabilistic challenges of quantum mechanics. In the future, quantum computing is expected to predict molecular properties for new molecules.
Read more: Data and AI: How It Has Transformed Over The Years And Trends To Watch out For!

Conclusion

In the coming years, advances in Artificial Intelligence will reach the superintelligence stage. However, the transition to new technology has already begun.
Most businesses are incorporating this unique fixture as it has helped with better sales and forecasts. It has also given businesses growth opportunities. We are sure you want to get started with this too.
Give us a call and let’s discuss what is best for your business.

Businesses are always on the lookout for ways to optimize processes and gain greater visualization. When processes work efficiently, the output of the product is higher. This leads to workflows that run smoothly with minimum errors and higher capacity. A good reason for the growing popularity of process automation and visualization.
Automation and visualization are the future of the business strategy. Gone are the days of carefully filling in graph paper by hand. Today, process automation and visualization help enterprises up their game by allowing access to real-time models capable of accurately capturing the nuanced data sets.
In this blog, we will expand on how enterprises can up their game with process automation and visualization.

How Enterprises Can Up Their Game with Process Automation and Visualization

Data visualization enables human operators to manage vast sets of data, glean insights from different information sources, and perform operations more intuitively and strategically.
In the current data-immersed world, data visualization can significantly add value by conveying large datasets visually. What does this mean for your business? This means a better grasp of critical customer data.
According to the IDC, the collective sum of the world’s data is predicted to grow to 175 zettabytes by 2025. Processing such large amounts of data can become a problem.
By allowing automation and the right programs to sort out your business data, you can generate graphs. You will be able to use these graphs to up your game in business competition.
Data visualization offers businesses the hope of getting a grasp on data. Fortunately, the human brain can process and recognize trends, identify potential issues, and forecast future development from clear visual displays.
Read more: How Powerful Is Data Visualization With Tableau

Look Out for Upcoming Powerful Trends in Automation and Visualization

1. AI and ML

Artificial Intelligence and Machine Learning render visualization more accurate and efficient. These technologies enable businesses to handle customer feedback without bias. Process automation allows you to sort the feedback in real-time and according to your specifications.

2. Unlock Big Data with Data Democratization

Large amounts of data are hard to understand. It requires data scientists and other experts to unlock its treasures. Not anymore. Advanced no-code data analysis platforms can automate your data process. This is called the democratization of data.
Democratization of data leaves it malleable and easy to display allowing your employees any level of tech support. When this is paired with the data visualization type, it can unlock big data results for teams at all levels of your organization.

3. Video Visualization Is Here to Stay

Young and old alike tend to retain the information they see over what they hear.  This would mean that video infographics will be the future.
Video applications for business strategy and customer retention are key areas for future strategic data visualization implementation.

4. Real-time Visualization for Early detection

Knowing a problem at the exact moment it arises can assist businesses in customer retention and brand presence. Early detection can have a dramatic impact on the bottom line.
Process automation can help run a dashboard that allows users to submit their error reports to your customer support. Then the reviews can be tagged and analyzed using sentiment analysis.

5. Mobile Optimized Visualization

An increased number of people access the internet on their mobile devices. Your business needs mobile-optimized data visualization to stop customer churn.
It enables you to know if your potential customers are learning about your services through social media or an online review board. Though mobile-optimized visualization is an easy step, it is critical to keep your business on top of the game.
Read more: 7 Awesome Data Visualization Tools

Business Applications of Process Automation and Data Visualization

1. Financial Service and Insurance 

The finance service industry is a prime candidate for process automation and data visualization. Two top requirements of this industry are customer response time and compliance with strict regulations.
When automated, quick decisions can be made based on pre-defined rules like loan applications, claims processes. businesses can use data visualization to make reliable predictions or risk calculations in the financial industry.
Insurance fraud can cost billions of dollars damage.  Process automation and data visualization can improve fraud detection.
Read more: Deploying RPA for Finance, Healthcare, and IT Operations.

2. Distribution and Logistics

Process automation and data visualization can minimize costs by planning transport promptly, reducing costs of downtimes and maintenance.

3. Sales

Data visualization can greatly improve relationships with your customers. It helps you know the needs of your customers better, and address each of them directly in real-time.

4. Marketing

Data visualization and process automation can reduce marketing costs substantially.  These technologies can help evaluate the demographics, location, transactions, and interests of your customers. Visualizing these details can help you understand their purchase patterns.
Thus, data visualization can be used to create and target new customer segments. Cross-selling is another advantage. At the same time, data visualization may reveal that customers are dissatisfied. Identifying this and responding quickly can counteract the situation to retain your customer base.

5. Healthcare 

Process automation and data visualization enable cheaper healthcare. It can help predict disease occurrence and proactively propose countermeasures.

6. Science and research

Visualization enables the evaluation of the data of an experiment. Process automation and visualization can be advantageous especially when an experiment generates large amounts of data within seconds.

7. Production

Large amounts of data are generated during production. Using process automation and visualization can help plan preventive maintenance and prevent production delays or downtimes.

Prepare Your Business For The Future With Fingent 

Fingent helps enterprises automate document-based processes. We can help you create safer sharing and collaboration. Our platform allows you to create teams, assign roles and privileges, and streamline communication.
Fingent’s partner integrations allow you to use it together with your existing software. Our top-level measures protect our users’ data. The encryption we provide ensures content integrity and prevents alteration.
Fingent can help your organization reach the goal of paperwork elimination. Doing so can lead to efficient resource distribution throughout the organization.
What’s more, it reduces carbon footprint. Our experts bring along specializations supported by scientific rigor and in-depth knowledge of advanced techniques to design, develop, and deploy solutions for process automation and visualization.
Give us a call today and let’s get talking.