We want AI now. But do we know what for? 

A comic strip went viral a few weeks back and caught my attention. A little figure asks, "Who are we?" and several others respond, "CEOs." "And what do we want?" They reply, "AI!" "Artificial intelligence for what?" And they respond, "We don't know!" "But when do we want it?" And they reply, "Now!"

The joke perfectly reflects reality, not just what we see in our daily lives, but also what's emerging from the "The GenAI Divide: State of AI in Business 2025" report, published by the MIT's Networked AI Agents in Decentralized Architecture (NANDA) initiative.

The study reveals that, while generative AI holds promise for agility, problem-solving, and even profitability in the corporate world, most initiatives have yet to reach significant levels of success. 

The report states that only around 5% of the AI pilot programs achieved any significant revenue acceleration. Most initiatives stalled, resulting in little to no measurable impact on profits or losses. 

In an interview with Fortune, the lead author of the report and MIT NANDA project collaborator, Aditya Challapally, explained which pilot programs from large companies and younger startups stood out using generative AI in recent years. "They choose a problematic point, execute well, and make smart partnerships with companies that utilize their tools," he added. 

For the 95% companies included in the report, simply implementing some generative AI solution wasn't enough. The key issue wasn't the quality of the models and tools, but rather a "learning gap." 

Fortune reports that, while executives blame regulation or model performance, the MIT investigation points to flaws in business integration. 

In other words, the AI solution does exist, but problems were found in the work routine of the other parts of this process: the humans. 

More general-purpose tools, like ChatGPT, are excellent for individuals due to their flexibility, but they're not a miracle solution for business use because they don't learn or adapt to workflows, explained Challapally.

I've spoken about this in several presentations and conversations. AI tools are an excellent support, but not a shortcut. AI is great for accelerating testing, refining ideas, verifying data, or even completing a complex task, as if it mastered a dedicated software or application.

As the report indicated, companies that successfully chose their AI agent targeted a problematic issue or point of friction and managed to solve or at least accelerate that process, naturally leading to increased productivity and profitability.

A good question to ask, before joining the chorus of "We want AI in everything now," is: what tools and solutions are available that can help meet the company's needs? 

Perhaps there aren't yet ready-made products and applications for the biggest challenges. However, if you can accelerate any process or provide a stronger foundation for your employees to make better decisions, that will be the best AI support for your company right now. 

The final decision is always human, including determining how far artificial intelligence will be helpful. And like all technology, we're in a period of evolution and refinement. So your decision may also change within six months.

Henrique Calandra He is the founder of WallJobs, a Brazilian technology company offering automated solutions for internship contracts, author of the book "Generative Artificial Intelligence for Beginners," columnist for ABStartups, and speaker at major ecosystems like InovaBRA and Distrito.