5 Predictions for AI and Analytics in 2020

Arjun Kulkarni
Crux Intelligence
Published in
5 min readDec 26, 2019
Photo by Jude Beck on Unsplash

2019 is coming to an end, and we all can agree that it has been a massive year for AI and Analytics. The enterprise world has made significant progress in the domain of artificial intelligence particularly, yet, somehow, there still remain many aspects within AI that we have to unfold to drive the future. Leaders across the world are contributing their insights on what will transpire in this exciting area of technology in 2020. Whether it be the computational or the human impact of AI and Analytics, there is still so much that we need to discover!

AI has become an integral part of the business — development tools, algorithmic models, computing platforms, management, and monitoring tools, data governance and ethics — are all part of the mainstream conversation at every forward-looking enterprise. The intersection of AI and Analytics is one that we find most exciting — and there are many trends we predict to see in 2020. Let us look at the 5 developments we are most likely to see at the intersection of AI and Analytics in the next year.

#1: AutoML Will Become Mainstream

Once considered to be a niche technology — Automated Machine Learning will be all the rage in 2020. Data scientists — sensing the opportunity to perform complex tasks faster — are catching on to the AutoML wave. It helps that major cloud platforms such as Amazon Web Services, Google Cloud Platform, and Microsoft Azure all support AutoML development.

AutoML helps businesses find a middle ground between custom machine learning platforms and cognitive APIs. Arguably its most significant advantage is that it offers customizability without requiring less technically proficient employees to handle complicated workflows. Areas like healthcare, retail, financial services, transportation, etc. are fast implementing AutoML-based applications across their businesses and expect a promising future for this technology.

With AutoML, businesses can automate end-to-end processes by and applying machine knowledge to real-world problems. This way, machine learning is used in perfect sense and enabling people with no expertise in the field to leverage AI.

#2: AI will Jumpstart Prescriptive Analytics Efforts

Without a doubt, we know that prescriptive analytics is pretty much the holy grail for business users. If your enterprise sales are down, you desperately want recommendations on what you need to do to bring them back to acceptable levels. However, the development of true prescriptive analytics applications has so far been constrained due to the tech backbone lacking in speed and scale. AI is here now to jumpstart progress in the prescriptive analytics arena and help bring it into the mainstream.

By combining prescriptive analytics with the agility and autonomy of AI, we can take the next step beyond predictive analytics. When structured and unstructured data is provided to prescriptive models, real-time decision-making in enterprises can evolve into real-time actions. AI will supercharge prescriptive analytics models and help them become precise, relevant and actionable.

Using this amalgamation of AI and prescriptive analytics, some business processes also can be automated efficiently. The growth in AI is definitely going to help further the cause of providing businesses with better prescriptive recommendations and actions in 2020.

#3: Enterprises Will Start Demanding Embedded Analytics

In 2020, it is expected that the global Embedded Analytics Market will grow at a Compound Annual Growth Rate of 14.76%. Why? Because enterprises have already made significant investments in systems of record — CRMs, ERPs, financial analysis and marketing automation systems. These systems already have significant data within them and enterprises are neither keen on moving the data to another system nor burden users with an additional system solely for performing analytics.

We are already seeing some system of record vendors graduate slowly into becoming systems of intelligence — by providing some rudimentary analytics functions on top of their software. However, enterprises needing more sophisticated functionalities are left stranded.

Enter Embedded Analytics. This technology basically allows more sophisticated analytics software to sit on top of the data that resides in the system of record. Embedded Analytics serves the dual purpose of eliminating the need to move / replicate the data, while not requiring an additional interface for users to log in to. System of record vendors too are becoming increasingly open to providing a way for analytics vendors to work in an embedded mode as they see the value of this collaboration. In 2020, we see that more enterprises and vendors will work out a win-win model using embedded analytics.

#4: Demand For Better UX Will Surge

The experience gap between enterprise applications vs personal applications today is massive. Consumer world apps are driven by a need to keep users hooked to their platform through UX-side innovation, while enterprise apps have largely kept their users due to the unavoidability of their platforms. However, big software companies are fast realizing that the competitive landscape is changing and they need to keep up with the user experience tenets of the day in order to retain users.

The world of AI and Analytics is no different. Modern Analytics platforms will do better to offer significant upgrades to the users’ experience with their platforms. In 2020, we will see a clear trend of consumers demanding a balance between good AI and even better design.

#5: Continuous Intelligence Will Become the Default Paradigm

It is said that the only constant in the world is change. This is especially true in the world of business and technology — where expectations change dramatically at breakneck speed, in the hope of achieving competitive differentiation. The analytics world has long relied on batch processing to deliver insights to their users. However, that cannot be the case any longer and a move to continuous intelligence is very much on the cards in 2020.

Today, we are generating an enormous amount of data at a fast pace. We live in a world where data is streaming from IoT devices, smart sensors, social media, and other continuous feeds. Isn’t it time that our analytics applications stayed in step with the pace it which data is being generated? This is where the need for continuous intelligence using real-time analytics comes from. Gartner predicts that before we reach 2022, more than half of major business systems will use Continuous Intelligence to improve their decisions.

Some Final Words

The desire of market leaders to do great things and invent new technology are driving us towards a better future. The things that were speculated as impossible are present today. Every year, we come up with new, propelling ways to revolutionize the digital world. Just like the invention of the wheel and the internet, AI is the future of the human world. So, we look forward to 2020 to see this acceleration in the growth of AI and analytics.

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