Technology Leaders Share 10 AI Predictions for 2022

AI and machine learning are continuing their upward trajectory at companies already pushed to the limit from COVID-19 transformation and disruption. However, experts say that as businesses look to leverage AI for a growing number of increasingly sophisticated applications, they need to take a more data-centric approach to development.

Here, IT leaders share their perspectives on where AI is headed and what can be expected to change in 2022.

  1. The conversation around data for AI will be prioritized: The discussions around data for AI have started, but they haven’t nearly received enough attention. Data is the most critical aspect for building AI systems, and we are just now starting to talk and think about the systems to acquire, prepare, and monitor data to ensure performance and lack of bias. Organizations will have to prioritize a data-first approach within an enterprise architecture in 2022 to enable AI and analytics to solve problems and facilitate new revenue streams. Yashar Behzadi, CEO and Founder of Synthesis AI
  2. Companies will demand energy-efficient AI: As the climate crisis has become impossible to ignore, companies are prioritizing sustainable practices deep into the supply chain and AI compute decisions are no exception. The demand for computing power to train and run increasingly larger neural networks will only continue to grow in 2022. As a result, I predict we’ll see an increase in companies committing to reduce the carbon footprint of their AI and investing in ways to make both AI hardware and software more energy efficient. Nicholas Harris, CEO of Lightmatter
  3. AI and deep learning go mainstream: As the toolset for AI applications continues to evolve, machine learning and deep learning platforms have entered the mainstream and will attain the same level of maturity as specialized data analytics. Just like we currently see a plethora of fully integrated managed services based on Apache Spark and Presto, in 2022 we will see vertical integrations emerging based on the likes of PyTorch and Tensorflow. MLOps for pipeline automation and management will become essential, further lowering the barriers and accelerating the adoption of AI and ML. Haoyuan Li, Founder and CEO, Alluxio
  4. AI-Generated Threats Will No Longer Be Hype: Expect cybercriminals to leverage AI-generated email threats especially in targeted attacks. We are currently seeing threats being created manually, but with improved technologies available to mass-produce messaging for email threats based on what’s trending in the news or what is being mentioned in a company’s social accounts, the potential to target their victims is even greater. This could be a game-changer in the way attacks are being built and would put having an AI Response as a must-have in your cybersecurity toolbox. Adrien Gendre, Chief Product Officer, Vade
  5. AI will move from theoretical to practical, opening up new opportunities for developers: Machine Learning and Artificial Intelligence surged over the past decade, with many companies investing heavily in these advanced technologies. What used to be novel ideas, are now being put into practice and next year we’ll see ML and AI be more embedded into developer work. Not only will this help accelerate manual tasks, but it will also open up opportunities for developers to innovate at faster speeds. Jim Rose, CircleCI CEO
  6. Quantum AI environments will emerge: With recent advances in Quantum Computing, in 2022, we will start to see the convergence of Quantum Computing with Artificial Intelligence, Knowledge Graphs and Programming Languages. These distinct technologies will start to morph into a single computing environment operating in one memory space as a fully integrated solution. The separation between programming and AI/Analytics will begin to blur as developers use Quantum-based computer languages to generate incredibly complex, next generation AI algorithms and applications that result in new discoveries based on the quantum acceleration of machine learning and deep learning. Jans Aasman, CEO of Franz Inc
  7. With their hyper-focus on innovation and speed, IT teams will lean more heavily on automation to modernize code: Overall business use of automation and AI has been steadily increasing since the pandemic began, and next year will see a surge in automated tools being applied to modernization initiatives. Driven by the need for speed and the continuous demand for innovation, IT teams will be looking to automation to more quickly analyze legacy code and update business rules. Fully embracing automated modernization tools will enable IT to allocate more resources and energy toward innovation and time to value. Keith Cox, Managing Director, Application Modernization & Migration, Deloitte Consulting, LLP
  8. AI will become more accessible to developers: Previously, only big players like Google and Facebook had the deep pockets to make AI/ML models a reality. This year, there will be more off-the-shelf technology that will be used by developers at medium sized companies to make AI/ML models more accessible.  There will be functionality readily available to make applications talk, convert speech to text, automate video and image analysis, automatically eliminate inappropriate or illegal content, and many other industry specific use cases. Leah Forkosh Kolben, Co-Founder and CTO at
  9. The use of AI will increase in software development: Over the years, AI has gone from buzzword to a game-changing technology, and it is revolutionizing how developers work. From productivity to increases in quality and speed, the benefits are unmeasurable. However, the developer community continues to face a challenge: the implementation of AI. And, with the AI market expected to blow past $500 billion by 2024, next year is bound to be the steppingstone toward an AI-centric software market. For one thing, AI will alter how code is written, updated, and released?and DevOps will become increasingly automated and responsive. Software developers will need to learn how AI will fit within their own tasks—with AI-empowered to make changes to itself, the focus for developers will shift to a more creative, strategic level. For example, developers will need to learn how to “talk AI” to provide insights and drive core business operations, and integrate different APIs using AI to build a better product and provide faster go-to-market timeframes. And lastly, they will have to focus on the aspects of the software that are not so easily automated, such as finding ways that multiple software systems could work together. Developers will likely shift away from the practice and process of development and into building highly customized solutions for a wide range of challenges. Jonathan Grandperrin, CEO of Mindee 
  10. The coming year will see a shift from point solutions to a suite of AI-enabled business applications built upon a common platform: The focus of platform development has been on the platform itself and the tools needed to build highly customized point solutions. In 2022, with the focus shifting to AI-enabled solutions targeted to line of business teams with specific business problems, expect to see a corresponding shift away from point solutions to suite-oriented solutions that allow other lines of business users to capitalize on the same institutional knowledge.  Attention will shift to the platform’s ability to support the suite along with a rich user experience instead of simply focusing on the platform and tools. For example, when a company purchases MSFT Office 365, they are far less concerned with the platform and far more concerned about the productivity apps and the common user experience they share across the underlying platform. Ryan Welsh, Founder and CEO of Kyndi

Photo by Artturi Jalli on Unsplash