Tag: Artifical Intelligence

Patient-Generated Health Data – A Powerful Tool To Enhance Healthcare

Remember a time when patients would queue up in line with a big dossier in hand, waiting for their time to be examined by the doctor? Lengthy queues, paper-heavy records to be maintained, time wasted as doctors reacquaint themselves with the patient’s entire history – no more of all of that. Today, a patient wants to be involved in his care and he doesn’t want to be waiting around wasting precious time. With innovative health technologies, patient-generated health data is making that possible by enabling patient-centered, citizen-engaging care. 

Let us consider how improving patient care through technology is possible. We will also see how the use of information technology in healthcare is allowing the healthcare industry to deal with patients as valued customers, improving their experience. But, first of all, what is patient-generated health data?

Patient-Generated Health Data

Any valuable information a patient can garner about their health status is referred to as Patient-Generated Health Data [PGHD]. PGHD is much more than just a person’s health history with information on his symptoms, medication and treatment information. It also includes his biometric data, as well as information about his lifestyle choices. These records will provide a clearer picture of a patient’s actual health status, better than the patient can describe in his own words. 

The use of information technology in healthcare is making it possible for healthcare providers to understand their patients better and in making better medical decisions. It also aids patients in receiving an increased understanding of their health condition. The importance of health information technology in healthcare today cannot be over-emphasized.

How Does The Use Of Information Technology In Healthcare Help Healthcare Organizations?

Patient-generated health data can improve the quality of patient care. When integrated into clinical care, patient-generated health data enhance shared decision making and patient engagement. The use of information technology in healthcare can provide an assessment of the patient’s symptoms and well-being, preferences and values, and goals for healthcare. Here are a few specific benefits of the use of IT in healthcare:

1. Improves nurse-patient relationship

Low health literacy can strain the nurse-patient relationship. When a patient comes to appointments armed with their health research, the nurse-patient relationship improves. 

2. Clinical benefits 

PGHD plays an important role in assessing a person’s health and monitoring treatment effects. It connects patients and healthcare providers during a care encounter. PGHD can be used to monitor a person’s overall health and allows healthcare professionals to detect potential health dangers.

3. High-risk patients

Keeping a track of PGHD helps providers identify and treat high-risk patients at the earliest. Leveraging PGHD proves extremely valuable in chronic and acute care.

4. Patient engagement

Patients have ownership over their data and control on how and when that data is shared with their care team. They are empowered to contribute to their care and can share insights. It improves communication and contributes to shared decision-making. 

5. PGHD provides independence to seniors 

PGHD can be used in assisted living to mitigate the risk of falls. It gives confidence to the elderly for independent living and it improves adherence to complex medication plans. PGHD also alerts healthcare providers when required, avoiding the need for expensive assisted living facilities and nursing homes.

Fingent Technologies worked with NovitaCare, an early-stage healthcare startup, in setting up an online platform to enable easy administration, streamlined workflow for many healthcare services and HIPPA compliance. Improving patient and caregiver interactions, eliminating waste, enhancing accountability, and raising the quality of care were the main accomplishments of this tool.

Related Reading: Read more about the case study here.

Innovative Health Technologies To Help The Patient

Innovations in health technologies go beyond just PGHD. It includes various devices and systems designed to streamline healthcare operations, lower the costs and enhance the quality of care. Among the most promising healthcare technologies are Artificial intelligence (AI), virtual reality, chat-bots and so on. Let us consider a few.

1. Artificial Intelligence

Artificial intelligence with machine learning is proving to be essential for healthcare organizations. It is capable of reducing the risk of preventable medical situations in three ways. 

• • Reminders: It can provide automated reminders to help a patient, reminding him to take his medication within a certain time-frame.
  • Identify and alert: It helps to identify potentially dangerous situations and triggers alerts for the medical staff making timely medical intervention possible. 
  • Personalized dosage: Dosage recommendations are made depending on each patient’s body chemistry while considering environmental factors.  

2. Blockchain in Healthcare

Blockchain can create and maintain a transparent and tamper-proof transaction ledger. This technology could change the way huge healthcare sectors operate. Personal data collected in blockchain remains with the patient instead of being stored on servers, thus enhancing confidentiality.

3. Voice Search

According to research, 46% of Americans use voice-assistance on their mobile devices. The figures are not much different for the rest of the world. We can expect that soon many more would be inclined to search for health-related information using voice search. Since it is increasingly used, the healthcare industry is also making good use of voice search. This technology would be helpful to both patients and caregivers who try to locate hospitals or clinics either near their homes or offices. 

4. Chatbots 

Chatbots in healthcare provide various benefits. They assist with medication management, first-aid or in emergencies. Chatbots offer a personalized service to patients and caregivers.

5. Virtual Reality in Healthcare

Patients are often anxious about hospital stays and procedures. Virtual reality helps calm their nerves and improve the patient experience. 

6. mHealth Apps

Mobile applications provide patients with control over the options available to him. These apps can assist in making an appointment, uploading medical history or even checking into a hospital for medical care. Mobile apps ease the load of the non-medical staff at hospitals and reduce the patient’s waiting period thus reducing operational costs considerably. 

An online platform Encourage was developed to empower patients with information related to their healthcare and educational material about procedures and illnesses. The tool further helps doctors keep track of a patient’s progress, assign tasks, reminders and care plans for the patient. It also gives patients the ability to include people as their caretaker and manage their engagement with them and the doctors through a rewards system and more. 

Related Reading: Read more about the case of simplifies patient care here.

What is the Future of PGHD?

With no signs of slowing down, it is estimated that in a couple of years AI is expected to grow annually at the rate of 48%. Other technologies along with mobile apps help in communicating with patients even after they leave the healthcare facility. With such promising technologies, patient-generated health data will surely benefit patients and caregivers and aid healthcare organizations to provide better care. 

Yes, the partnership of healthcare organizations with technology is a match that brings out the best in each other. We can confidently look forward to this relationship growing and maturing in the days to come. To empower your healthcare organization with the budding technologies, get in touch with our experts now!

Top Artificial Intelligence Strategies For Investment Management

Artificial Intelligence can prompt you what best to invest in. Digital Revolution is at its height and AI implementation makes use of digitized data to help businesses make decisions based on past performance.

It is a fact that 80 percent of the companies already have artificially intelligent systems implemented. Companies rely on artificially intelligent machines to make investment decisions by analyzing the vast amount of structured and unstructured data at hand. It is necessary to understand how artificial intelligence fosters to enhancing communication, forecasting future events, and in making good decisions.

AI helps in investment management by helping businesses augment the intelligence of human workers to develop new technologies. Some examples where AI is employed by investment management teams of businesses are as follows:

• Product Innovation and R&D derive 50 percent of its revenue from AI.
• Supply Chain derives 42 percent from AI.
• Customer Engagement Services to around 46 percent revenue form AI.
• Sales deriving 34 percent.
• Security of about 40 percent.
• Data Gathering derives to about 27 percent of its revenue from AI.
• Intelligent Workflow and Automation around 23 percent.
• Operations on Analytics by 20 percent.

Related Reading: Check out how artificial intelligence is revolutionizing small businesses.

The potential of Artificial Intelligence in managing assets is significant. So how can the investment management business derive its maximum out of AI? Here’s how:

Machine learning is used in investment management to learn from large volumes of structured and unstructured data. This data is gathered from past transactions and is used to predict buying and selling decisions.

According to JP Morgan, the investment management industry is likely to spend $2-3 billion on BigData. BigData is modeled and distributed in order to generate insights by performing predictive analytics. It also ensures high investment returns.

Machine Learning takes huge chunks of unstructured and raw data. This data is then organized and streamlined into predictable patterns. Based on these patterns, deep analysis is conducted and critical insights are drawn.

Benefits Of Artificial Intelligence In Investment Management

To augment the intelligence of humans, Artificial Intelligence benefits Investment Management in the following ways:

1. Provides Critical Insights

Firms provide their structured and unstructured data sets and derive critical insights from the patterns generated. Historical data provide insights that help in making investment decisions for firms. This also helps in predicting future business outcomes.

2. Reaching Out To Clientele

Artificial Intelligence helps in automating processes. For instance, getting an email or automated feedback or notification on how to manage investments is performed by analyzing historical data via machine learning algorithms. AI helps in reaching out to the clients with the help of monitoring search engines and crucial insights drawn out of patterns from historical data.

3. Reporting Services

Natural Language Generation or the NLG technology enables the automatic analysis and explanation of data and transforms the data-driven sections into reports. These reports are generated for clients. Marketing material, portfolio, and many more such tasks use the NLG technique.

4. Better Customer Experience

Chatbots and machine learning to serve the investment management industry verticals to a great extent. For instance, there are smart chatbots that offer guidance for managing investors in taking critical decisions. Natural Language Processing techniques are a rapidly growing use case in the investment management domain.

Related Reading: AI-powered Chatbots can help you redefine your business. Read on to know how!

5. Enabling Risk Management

Machine-learning algorithms can transform the existing validation frameworks in order to mitigate risks. AI can transform the financial sector by making use of chunks of data available to build models. These data models can improve decision making, can manage risks. The McKinsey Global Institute researches state that implementation of AI and machine learning algorithms can generate over $250 billion in the banking sector.

The compliance and risk management functions enhance the investment firms in three main ways as follows:

1. Data Analysis is automated, largely into systems.
2. Tasks such as administrative activities are considerably reduced.
3. The workforce can focus on critical and value-generating tasks rather than having to spend time on redundant and time-consuming activities.

These algorithms monitor for fraudulent transactions and trigger automated responses that can help investors make accurate decisions.

Related Reading: Can Machine Learning predict fraudsters? Read along to know more!

6. Automating Functions

The aggregation revolution that AI has gone through in recent years has fueled the pace at which critical data reaches investors. Investment management is now going through an analytical revolution where artificially intelligent systems and investment is coupled together to transform the approach in analyzing data, how the data is packaged and how this data is showcased to the investors.

This augmented intelligence will help potential investors to professionally be informed about crucial investment ideas and also regarding stock selection and portfolio construction tools.

Related Read: Artificial Intelligence: Taking The Buzz Out Of Buzzwords

7. Taking Over Tedious Tasks From The Workforce

Artificial intelligence can perform screening of stocks, in addition to being able to rapidly identify stock opportunities among global markets. This is a huge preference for investors to be able to identify accurately the various means of shifting tedious tasks from the workforce. This is made possible by letting investors know about it via a visual representation of key factors derived from the AI engine.

8. Real-time Visualization And Control

Investors are prompted and notified with suggestions that mitigate the risk of unwanted exposure of critical data and decisions to the outside world. Exposing portfolios to unknown sources can lead to frauds. For instance, letting out the details of forecasted details of interbank lending rates can lead to uncertain risks. Thus, risk control is necessary and is achieved via real-time visualization made possible with AI tools.

9. Reducing Investor Biases

Smart monitoring systems powered by Artificial Intelligence are critical because the AI engine alerts the investors regarding factors such as price declines beforehand. This reduces the exposure of the investor to risk factors. It reduces investor biases considerably and creates a more balanced perspective for investors to increase performance.

10. Generating Alpha For Value Creation

Investment firms that require growth, in the long run, can enable AI-based systems, where big data plays a major role in generating alpha. This excess return measures the market’s overall risk volatility and is also termed as systematic market risk.

It is critical for the investment management industry to make accurate decisions and to allocate capital in the right way for enhanced value creation. The four pillars analyzed for a successful transformation thus, are:

• Alpha Generation
• Increasing the Operational Efficiency
• Understanding Investor Preferences in Real-Time and
• Risk Management.

These four pillars are augmented with artificial intelligence to obtain efficient business models. Investment firms that capitalize on these four pillars reap successful business outcomes. Drop a call to our IT strategists right away to gather tips on investment management!

Artificial Intelligence (AI) is considered to be one of the most significant disruptive technologies today. More and more businesses are already realizing its benefits. Gartner’s 2019 CIO survey revealed that the percentage of companies implementing AI increased by about 270 percent over the last four years, and 37 percent in 2018 alone.

Leveraging the power of AI to enhance your existing business applications isn’t nearly as complicated as you might think. You don’t need a billion-dollar budget to implement AI-powered applications. In fact, small and midsize businesses (SMBs) today are cutting costs and delivering great customer experiences with AI-powered applications—and they are competing with giant companies at scale.

Here’s a look at how you can enhance your existing business applications with AI:

Enhance CRM Apps with AI

Incorporating AI into your current Customer Relationship Management (CRM) system, for instance by using chatbot or automated live chat support, will allow your company’s helpdesk to provide better, faster and more dynamic responses. It will also help you reduce the man-hours needed to resolve queries and help you build better engagement and customer trust. And because the AI-powered CRM system provides predictive insights, you can automatically recommend similar products or services a customer may be interested in.

Related Reading: Unconventional Ways Artificial Intelligence Drives Business Value

Streamline Supply Chain with Machine Learning

Machine learning (ML) allows your system to discover patterns in the supply chain data using algorithms that automatically identify the factors that contribute to the success of your supply networks, while constantly learning in the process. ML algorithms and the applications running them can analyze large, varied data sets in no time, improving accuracy in forecasting supply and demand. If applied correctly within your SCM work tools, ML could revolutionize the agility and optimization of your supply chain planning.

AI-Powered Recruitment Apps

Artificial Intelligence is expected to replace 16 percent of Human Resource (HR) jobs within the next 10 years, according to Undercover Recruiter. Integrating AI into your existing recruitment processes or tools could help your company’s HR department find the right candidate or the best fit faster and easier, thereby saving you time and money. AI-powered video interview tools, for instance, can utilize biometric and psychometric analysis to evaluate your applicants’ tone of voice, micro-expressions, and body language.

Related Reading: AI To Solve Today’s Retail Profit Problems

Improving Cybersecurity System with AI

Given the data breaches and cyber-attacks that have hit headlines in recent years, integrating AI into your current security system is vital to protect consumer data, improve trust and deliver true business value. About 71 percent of companies in the US plan to spend more budget on AI and machine learning in their cybersecurity software this year.

AI not only improves your company’s existing detection and response capabilities but also allows new abilities in preventive defense. It enhances and streamlines your security operating model by reducing complex, laborious and time-consuming manual inspection and intervention processes. Because the AI-powered cybersecurity system can self-adjust and learn data over time, you can automatically detect and block cyber-attacks and fraud.

Enhancing Space Exploration with AI

Another area where the application of AI has great potential is exploring outer space. NASA has plans to look for life on other planets, such as Mars, in the very near future. In their Mars 2020 initiative, they will use AI to explore Mars in greater depth, which includes looking for alien lifeforms. Most of us are at least slightly familiar with or aware of NASA’s Opportunity rover, which wrapped up a 14-year Mars mission when it quietly went dark in February 2019. Opportunity, also known as “Oppy,” found evidence that Mars at some point was home to water — a huge discovery.

Going forward with Mars 2020, NASA’s Mars Exploration Program will continue its use of AI for space exploration. In ongoing efforts to evaluate whether Mars is (or was at some point) habitable for humans and other animals, the Mars 2020 rover is equipped with a drill it will use to collect samples of rock and soil. It will store these samples in special tubes that will be collected by a later NASA mission. Read more about the artificially-intelligent robotic arm that will make it all happen.

Related Reading: Industry experts weigh in on the adoption of AI and ML in software development

Taking Your Existing Business Applications to the Next Level with AI

New AI frameworks and tools make provisioning AI capabilities more feasible than ever before. Working with a development partner who has the data science and AI technology experience, creating or updating a business application with AI can be started rapidly, take less time to code, and the resulting application placed into service sooner. Nor would it be necessary to staff for these hard-to-find resources for the long term.

Related Video: Artificial Intelligence – How to navigate AI

What To Watch Out For In 2019 On ERP Market Trends

It’s true that we can never bid adieu to last year’s trend-setting technologies like blockchain, AI, IoT, and multi-cloud. But, neither can we not talk about the progress where technology is likely to echo around the ERP space.

According to a study by MarketWatch, “The ERP software market is expected to rise globally to $47B by 2022”. Let us find out what are the possible market trends in ERP for 2019.

Drastic Rise Of The IoT Market

According to Statista’s latest research, “the global IoT market will rise exponentially from $2.9 trillion in 2014 to over $7 trillion in 2020”.  This leads to a situation where  ERP systems will need a new level of intelligence and automation to make platforms collect data and insights.

Earlier, only a small percentage of data were created and processed outside a traditional data center. But in the future, there will be a situation where nearly all data will be generated from outside of the data center.

IoT is expected to drive the design and deployment of many operational analytics solutions. Industries such as retail, banking, and telecommunications will also adopt operational analytics to enhance customer experience and quality.

Related Reading: Get answers to where and why should you invest in IoT.

Accelerating Transition To Cloud Computing

According to Statista Reports, “the global market revenue of public cloud services will surpass 278.3 U.S. Dollars in 2021”.

The benefits of this would be greater data security, minimal dependency on hardware, speedy results, and high customer satisfaction. As per the research report by IDC, spending on cloud computing is anticipated to rise at a rate of six times the rate of the current IT spending through 2020 which upsurges at 4.5 times the IT spending rate since 2019.

Cloud concepts, Content Delivery Network (CDN), DevOps, Big Data and Artificial Intelligence, are going to be the key players in the future of Cloud Computing.

Contribution Of AI And Emerging Disruptive Technologies

The three main trends behind the huge adoption of ERP services are the integration of artificial intelligence (AI), deployment in the cloud, and improved IoT technology.

Big data analytics and the various kinds of AI, including predictive analytics, machine learning, and deep learning, form the catalysts for industries to improve customer experience.

The third wave of technology evolution is based on systems of intelligence (Cloud, IoT, AI, VR, AR). For instance, Chatbots and messaging apps are examples for a rapid expansion in the implementation and adoption of AI.

By implementing advanced solutions such as AI-based chat-bots, IoT sensors and more, businesses will streamline and thereby accelerate their functions. This can tackle productivity issues and also it is an opportunity for businesses to realize the value and utility of new disruptive technologies.

Related Reading: Watch out for the top AI trends in 2019.

ERP and SaaS – Differences In Overheads

The traditional applications based on ERP were stored on servers. This meant overheads as a result of increased hardware costs as well as costs associated with backup, recovery, and maintenance. The difference between traditional and SaaS applications is that SaaS applications are stored on cloud-based servers.

The benefits of SaaS are that these applications do not demand high maintenance costs, or rather are they expensive. The additional overhead costs that are reduced when it comes to SaaS are that they differ in terms of per-seat licensing costs as well as the total cost of ownership etc.

So, since Saas is a cloud-based model, SaaS-based applications are neither costly, neither are they difficult to maintain.

ERP transition has taken place rapidly. The new SaaS model for ERP is very flexible and useful.

Inclusion Of Social Media Channels

ERP systems in 2019 will need to be able to include direct marketing and data links across multiple social media channels to make their presence felt in the market.

HR managers frequently use social media to search for and hire new employees and also as a background check and even as performance management indicators. These changing trends in business operations are reflected in any competitive ERP platform.

The modules that address are becoming social-media savvy in 2019. This is mainly due to the high use of customer base that accounts for 2.77 billion customers (according to eMarketer research).

The other engaging trends in ERP adoption are as follows:

• Focus on Business Intelligence

Organizations are trying to make forecasts with ERP software for business intelligence.

• Good Integration architecture

An increasing need for ERP software system has resulted in the act of ERP consultants being shifted towards a better integration architecture for ERP software.

• Two-Tier ERP

Two-tiered ERP is very useful for enterprises since they run in different processes at different places. These tend to match the needs of all locations with a better cost structure. It best suits when the enterprise is large.

• The Personalization Advantages

Today’s ERP systems are built for personalization. Some systems offer tools to help make it easy and fast in customizing the application to their needs.

• Large Organizations Acquiring Small Startups

Large organizations try acquiring smaller startups in that regards. This increases ERP implementation.

• Partnering With Firms That Break The Traditional Rules

With the onset of the cloud, the traditional role of technology partners will no longer be enough. Finding an ERP partner that utilizes the latest technology and analyzing how they deliver service with your needs is required for a successful business.

• More focus on profit from ERP

As ERP becomes more and more successful in the market, firms blindly implement them now. They are sensitive to the return of investment.

These above trends in ERP to be witnessed in 2019 are beneficial for an organization as well as provide to business growth. ERP software is used in various fields for work and that is the reason why the demand for an  ERP software system is increasing every day.

Related Reading: Check out these tips to get your business the best out of your ERP system.

Watch out for more market trends and highlights showcased for 2019 in our latest blogs!!

Also, empower your business with trending technologies. Contact our tech-experts today!

The year 2017 has been eventful for digital transformation, with technologies such as Big Data coming of age. Digital transformation promises to be more disruptive in 2018, as evident from the following predictions.

1. IoT Becoming Mainstream

The much-hyped IoT will walk its talk fully in 2018. About 8.4 million “things” are already part of the IoT ecosystem, a 30% increase from last year’s levels.  Enterprises will start using IoT to deliver better products, services, and insights. IoT will permeate to the masses, and become mainstream and commonplace.

Among specific sectors, IoT will revolutionize analytics in a big way, driving new smart solutions. A few possibilities include hyper-efficient fleet operations, intelligent traffic signals, and more. Tech giants such as Microsoft, IBM, SAS, and SAP are all heavily investing in IoT Analytics, offering a portent of the things to come.

2. Edge Computing Offers Effective Real-Time Processing Solution

The cloud and Big Data analytics analyze tons of data seamlessly. However, the sheer volume and velocity of data create time lag and some inefficiency. For instance, the cloud, for all its advantages, is not viable for IoT powered smart drones, autonomous vehicles, and other AI-powered smart devices. These devices need real-time and instantaneous data processing. Sending data from these devices “all the way” to the cloud is an inefficient and impractical method of processing data.

Edge computing, which performs data processing at the edge of the network, near the source of the data, promises effective solutions to the shortcomings or limitations of the cloud and big data. Edge computing, for instance, allows IoT powered devices to connect and communicate instantly and seamlessly.

Industry biggies, such as HPE and CISCO have already rolled out hardware and software to actualize Edge computing. IDC predicts 40% of all computing to happen at the edge in the next couple of years.

3. Enter the 5G Network

4G or fourth-generation wireless, synonymous with LTE (Long Term Evolution) technology, went mainstream in 2017. 5G of fifth-generation wireless will go gain ground in 2018. The need for hyper-connectivity and IoT propels the need for 5G.

The Next Generation Mobile Networks (NGMN) Alliance defines 5G as “an end-to-end ecosystem to enable a fully mobile and connected society.” 5G is not an incremental upgrade over 4G or LTE.

While the 4G focus is on raw bandwidth, 5G focuses on pervasive connectivity and super-dense network, enabling even faster and resilient access to the Internet even from the remotest caves or desolate hills. Unlike the hitherto monolith networks entities such as 2G, 3G or 4G, 5G co-opts a combination of technologies, including 2G, 3G, LTE/4G, LTE-A, Wi-Fi, and more. While emerging technologies and solutions, such as IoT, connected wearables, augmented reality and immersive gaming places a great strain on incumbent networks, 5G will run these technologies seamlessly.

Industry majors such as Sony and Samsung are investing in Gigabit LTE, the stepping stone between the incumbent LTE and 5G. The already well-entrenched Qualcomm Snapdragon technology powers Gigabit LTE. However, 5G will become a household technology only by 2020.

4. Blockchain finds Its Way

Blockchain, the secure transaction ledger system distributed across a network of computers, rather than under any single entity, will finally become mainstream by 2018. The financial industry has already started to embrace blockchain in a big way. The healthcare, entertainment, and hospitality sectors are on the verge of embracing it in a big way. Dubai is rapidly moving toward becoming the world’s first-ever blockchain-powered government by 2020.

5. Artificial Intelligence Becomes Mainstream

The market size for AI is set to double up from $2420 million in 2017 to $4066 million by 2018.

Solutions powered by Artificial Intelligence are already popular. Artificial Intelligence already powers many popular solutions, such as Alexa, Siri, Salesforce Einstein CRM, IBM Watson, SAP Leonardo, Netflix, Amazon AI, Cortana Intelligence Suite, and various customer service chatbots.

Companies will continue to roll out cutting-edge solutions based on Artificial Intelligence, especially to implement smarter and cheaper automation. The scope of artificial intelligence would expand to encompass everything from emails and content generation and from industrial manufacturing to smart grids. In fact, major companies will embed Artificial Intelligence into their core operations.  Fueling the growth of Artificial Intelligence is the spread of open-source solutions. Artificial Intelligence cannot easily be integrated into closed systems.

With more investments being made betting on Artificial Intelligence, Virtual Reality is losing the race significantly because Artificial Intelligence offers whatever Virtual Reality offers, in a much cheaper and better way. For instance, companies can apply 3-D visualization to train, pitch, and envision new products in a much better way than what Virtual Reality offers.

6. Anything as a Service

XaaS or “Anything as a Service” is now within the realms of possibility. The cloud-based services market now encompasses software, infrastructure, and everything else. The latest to enter the “as a service” market is a framework!  Framework-as-a-Service (FaaS), which falls between SaaS and PaaS is a customizable cloud-based platform. Users may indulge in rapid prototyping, visualization, and other fast fail methods to discover whether a concept or strategy will work or not. Companies get to know the result of their initiative, without having to spend time and effort, doing it the hard way.

Side-by-side with FaaS, workplace-as-a-service (WaaS) and unified-communications-as-a-service (UaaS) will also become mainstream in 2018. Remote workplaces, powered by WaaS, will rise in a big way by 2018.

7. Low Code Platforms to Soar in Popularity

Low code development platforms (LCDP) will net a total revenue of $6.1 billion by 2018, and over $10 billion by 2019. These figures are impressive when compared with the total revenue in 2015 which was just $1.7 billion.

LCDPs allow creating apps through a configuration of functions, and intuitive drag-and-drop options, rather than by hand coding. The obvious advantage is ease of development and accelerated delivery of business applications. Acute shortage of talented programmers fuels the growth of LCDPs.

Some popular LCDPs, as of now, are Appian, Mendix, Google App maker, and Zoho Creator. The growing popularity of such low-code development platforms will spur ‘citizen development’.

Technology is always fluid. Companies who embrace the latest technology head-on to deliver better solutions for its customers stand to reap dividends. Companies who do not change will surely be swept away into obsolescence.