Top 5 Artificial Intelligence Trends for 2022

The year was 1997.

An artificial intelligence (AI)-powered supercomputer had just defeated the reigning world chess champion, Garry Kasparov. On being asked who would win if he and Veselin Topalov played each other with the machine as a helper, he replied, "he who is more inventive will win."

Although we couldn't get the chance to witness AI assisting two chess grandmasters in their game, we see AI-assisted businesses that are changing the world every day. Artificial intelligence has evolved from the dream of a wide-eyed computer scientist a few decades back to an innovative tech being adopted across industries.

Even in the business world, AI has matured from being an experimental technology to an essential one. As AI engagements grow and business integrations become more strategic, the focus has shifted towards long-term scalability. In the larger scheme of things, despite the accelerated pace of adoption, AI is still in its infancy. The key ongoing trends for AI show the progress we have made so far and the distance that we still need to cover.

AI Trends for 2022

1. AI is now core to the business strategy

Several enterprises are leveraging AI in innovative ways across various aspects of their businesses. For instance, Pandora uses AI to serve the right music at the right time. Similarly, Netflix uses it to recommend new content and Uber in almost every business area. Artificial intelligence gives these companies and many more the edge against their competition in their respective domains.

Several organizations have been working on the proof of concepts to integrate AI with their business and have seen relative success in 2021 than in the previous years. A study by Accenture shows that 75% of the global executives believe that they will go out of business in the next five years if they do not scale AI. This is spurring more and more companies to board the AI ship as they do not want to be left out.

2. Cloud-based AI platforms are driving innovation

Cloud technology has been accelerating and strengthening enterprises with a more affordable and cleaner solution to manage data for quite some time now. Cloud-based AI platforms bring a similar advantage to those who want to integrate innovative AI solutions with their business but do not have the spending capability.

Small and medium-sized enterprises have greatly benefitted from the lowered infrastructure investments with cloud-based AI platforms, and the adoption will continue to increase exponentially.

3. Better collaboration with low code AI platforms

With equally powerful tools at disposal for everyone, the one who is more inventive wins. For substantial business advantage, one must start with empowering the people. A major disconnect in business applications of AI happens because of the gap in understanding of the other domain. Low code AI platforms empower those who understand AI and those who understand business to collaboratively build AI-powered business solutions. This considerably improves the chances of success of such solutions upon implementation.

The number of people who understand the depths of AI and how it can be efficiently used is extremely disproportionate to the number of organizations that are assessing how to leverage AI to enhance their business. The number of people who can develop AI-based solutions is even fewer. This talent gap is leading organizations to search for no-code/low code platforms for developing, deploying, and monitoring AI/ML solutions and reducing the turnaround time for their projects. This opens the way for the next two AI trends for 2022.

4. Rapid experimentation with automated data science

Time is of the essence when everyone is trying to get ahead in the race to integrate AI with their business and reap its benefits. Automated data science automates several time-consuming tasks a data scientist performs, giving them more time for experimenting and figuring out innovative solutions to business and real-life problems. It also considerably lowers the turnaround time and workforce requirements for standard AI projects.

Most cloud-based AI platforms combine automated data science with low code functionality making it a lucrative approach to work with for organizations initiating or scaling their AI efforts.

5. Exponential business growth by empowering non-data science users

While the machine learning models will continue to be developed by a handful of experts, the implementation and use of AI solutions are now opening up for non-experts. Owing to the fact that the data scientists are invaluable but expensive and in scarce supply, upskilling the existing workforce inclined towards data science and related technologies seems a better approach to many. Analysts, for example, can be swiftly upskilled to accept the role of citizen data scientists, while business users can be empowered with higher data and analytics maturity with proper tooling and training.

These AI trends indicate that organizations across industries have started acknowledging AI as the transformation agent that can bring about positive outcomes across their business processes. And a concerted effort is being made to weave AI into the organizational fabric.

Have you jumped on the AI bandwagon yet?

Author: Rajan Nagina, Head of AI Practice, Newgen Software