Guest post Mehdi Paryavi who is the Chairman and CEO of the International Data Center Authority (IDCA), a Digital Economy think tank and prime consortium of policymakers, investors, and developers in AI, data centers, and cloud.

A recent report from LinkedIn has found that three times more C-suite executives are adding AI literacy skills to their profiles than they were two years ago. Meanwhile, 88% of leaders say helping their business speed up AI adoption is their priority this year. The reality is, few business leaders have real confidence in how best to deploy AI in their organizations, given AI's very recent and rapid ascendency and the big questions surrounding it.

The importance of having an AI-Literate decision making process

It's clear that AI is here and starting to transform organizations in every sector of the global economy. What's less clear is how to define its usefulness to your company, its limits and risks, and its future. To address this problem, we can break it down into three simple questions: What is AI today? How is AI already being used? What are AI's risks?

What is AI today?

AI defines an entire world of software development, applications, and platforms. It is not just a single technology.

The most widely used form of AI at the moment is known as generative AI (GenAI). Google's ChatGPT and Anthropic AI's Claude are the best-known implementations at the moment. They generate answers by accessing hundreds of billions of possible word and phrase connections (known as parameters) to write out word-by-word answers, with each word determined by its probability of being the best word for that answer.

They have become infamous for their hallucinations, that is, providing bad information in some of their answers. They do this because they're created to favor the delivery of a probable answer rather than say if they don't know the answer to a question. Our experience in testing it at The International Data Center Authority (IDCA) shows they are reliable if you're looking for a specific statistic or detailed scientific formula. They are less reliable when answering questions you might have about movies or to settle sports arguments.

So if you adopt one of these platforms, we recommend that you set strict parameters, guidelines, and guardrails of its own, and not use it for casual inquires.

Agentic AI is the second big area for AI today. Agentic AI software acts as an agent to answer complex queries, monitor and improve automated processes, and offer insights and recommendations on business processes.

How is AI already being used?

GenAI is being used to simplify and amplify Google searches, whether you have people doing basic market research or keeping up with industry developments. It can also be used to dive more deeply into queries involving specific product developments, technical papers and proceedings from organizations relevant to your business, or to discover new developments in your industry.

As far as agentic AI, the IDCA held a recent webinar in which top people from Franklin Templeton Investments and the Sloan Kettering Cancer Center - obviously doing business in distinct areas - discussed how they have already integrated agentic AI into their real-time analyses and research functions. Both of these AI experts said they are not just playing around with agentic AI, but have fully integrated it into their companies. For other business leaders to do this, you'll need to define which specific processes could benefit from substantial improvement and how agentic AI can be used to address what might be longstanding problems. This is not a quick decision, and to make it with confidence will require a long-term commitment.

What are AI's risks?

The current GenAI platforms' habit of providing bad information is more of a nuisance than a risk, but does affect AI's usefulness. There have also been questions about GenAI's environmental impact, as a typical GenAI search requires several times more processing power...