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2022 trends in Enterprise AI

Artificial intelligence is changing the face of businesses and industries everywhere. But what will that change look like in the coming year?

The level of automation introduced by AI technology has been nothing short of revolutionary when it comes to improving workflow. Now, the biggest organizations at the forefront of global markets are looking to implement even more advanced, enterprise-level solutions to expand their capabilities and reduce costs.

To evaluate how enterprises plan to increase their reliance on AI technology, it’s helpful to look at trends and findings from past years. AI has already proven to be an invaluable tool in several industries, including healthcare, insurance, and logistics, and it’s increasingly becoming a more versatile one.

In this blog post, we’ll take a look at how the needs of these industries are shaping the biggest 2022 trends in enterprise AI.

Tapping into big data

The industries where AI adoption has taken root to the greatest degree all have one thing in common: a need to sort through, organize, and derive insights from an enormous amount of data.

“Big data,” as it’s come to be called, consists of documents, records, communications, and quantitative information from people and organizations. This data is the driving force behind a number of important organizational functions, including:

  • Marketing/outreach: Consumer data, online search results, outreach program performance metrics, and more are all essential tools when it comes to building better marketing teams and outreach strategies.
  • Sales: Using similar sets of data as with marketing/outreach, sales departments can develop a better sense of who their customers are and what’s important to them about a product or service. This allows them to increase lead volume and close rates.
  • Product/program development: AI can help improve products, services, and programs by identifying how users are interacting with them, how they aren’t, and what drives their desire to interact with them in the first place.
  • Predictive intervention and risk analysis: Whether it’s identifying a buying opportunity for a valuable asset or a potential situation leading to an insurance claim, AI technology can be used to identify patterns and evaluate the likelihood that certain outcomes will occur.

Being able to pick out what’s relevant to a specified priority among an enormous quantity of data is of paramount importance in the work of:

  • Medical organizations
  • Insurance agencies
  • Logistics service providers

…and many others.


Countless patients are treated in healthcare facilities across the globe. Patient data, drug information, and more all play a critical role in accurate diagnosis and the development of effective treatment plans. Artificial intelligence can, and likely will, make a big difference in the efficiency and cost of this process for the better.

Treating patients isn’t where the uses of AI end, however. Medical billing, research, equipment upgrades, and facility improvements are all data-driven, time-intensive, and costly aspects of a healthcare organization’s operations. Being able to substantially cut down the time needed to sift through the data needed to make important decisions in these areas may be a game-changer for medical organizations everywhere.


Predictive machine learning is a tool growing in popularity and complexity in many industries. For insurers, it may help significantly reduce the risk of a costly payout by utilizing claims records, demographic data, and more.


Logistics service providers may also find increasing use for predictive AI technology over the coming year. The obvious benefit of reliable self-driving capabilities may help improve driver safety and delivery times, but it can also assist substantially with warehouse space and resource management, demand predictions, weather and traffic conditions along delivery routes, and more.

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