Vimal Kapur, CEO of Honeywell, believes that the payoff from AI will not come from increased productivity.

• Vimal Kapur, CEO of Honeywell, stated at the CNBC Evolve: AI Opportunity Summit that he believes AI will have a greater impact on growth than just improving productivity in the industrial sector.
• Due to a shortage of skilled labor among younger generations, AI copilots can help reduce the time it takes for new employees to become proficient in their jobs.

Vimal Kapur, CEO of a global industrial conglomerate, believes that AI is not just about replacing office workers or offering cool features to consumers. Instead, he sees it as a continuous evolution of white-collar skills that become obsolete every five years.

The biggest challenges that AI can address at Honeywell stem from a generational labor shortage that both the company and its clients are facing. With declining birth rates in industrialized countries, there are fewer individuals available to perform jobs that were popular 25 years ago. "This is a problem that everyone in the industrials is facing," he stated.

Honeywell is utilizing AI to create a new labor pool that can learn and work alongside AI, allowing for the accumulation and deployment of institutional knowledge much faster. This can be accomplished with five years of experience working with two AI co-pilots, rather than the traditional 15 years of experience required for a complex role. Additionally, Honeywell is deploying AI in other areas, such as connectivity within jet engines and smoke detectors, to proactively monitor engine performance and identify servicing or replacement needs much earlier than before.

The labor shortage is the main concern for Honeywell CEO, who believes that AI can be a revenue-generating opportunity rather than a productivity fix. "The scarcity of skills is the root of the problem for us," Kapur stated. "It's a hindrance to revenue growth. The biggest revenue obstacle is the lack of skilled labor." Most companies are still in the early stages of exploring the benefits of AI investments, far removed from the advanced language models of OpenAI and the chipmaking of Nvidia.

Jake Loosararian, CEO of Gecko Robotics, whose company specializes in energy, manufacturing, and defense, emphasizes that the unfiltered raw data collected directly from the source will be crucial for many companies' success in implementing AI. His company's AI-powered inspection robots can analyze large equipment, such as aircraft carriers, to identify structural flaws.

At the Evolve: AI Opportunity event, Jon Fortt of CNBC "Closing Bell Overtime" was told by a speaker that the future belongs to companies with "first-order" data sets.

Several executives, including Clément Delangue, CEO of Hugging Face, emphasized the importance of moving beyond the current focus on large language models. Delangue, who is also a co-founder of Hugging Face, noted that data and data sets are the next frontier for AI. He pointed out that on Hugging Face's platform, which uses an open-source approach to develop AI models, there are over 200,000 public data sets that have been shared, and the growth rate of data sets being added to the platform is faster than the growth rate of new large language models.

"Every company, industry, and use case will have their own customized models, just like how they have their own code repositories and software products. This will help them differentiate themselves."

As AI becomes more customized to meet the needs of individual companies, there is a growing consensus that the focus of AI regulation should shift from general language models to industry-specific monitoring. As more companies adopt these customized solutions, it is crucial for the C-suite to ensure that these use cases are effectively communicated to the board.

"Katherine Forrest, a former federal judge and partner at the law firm of Paul, Weiss, Rifkind, Wharton & Garrison who is an AI legal expert, said at the CNBC AI summit that board members need to understand the risks their companies may be facing. She advised asking questions such as "What are risks? Do we have the right people managing those risks? Have we had any incidents?" For all the debate about how quickly AI opportunities will materialize, Honeywell's Kapur is bullish on the adoption curve steepening quickly. He believes there will be an inflection point, and 2025-2026 will be a big year for adoption of AI in the context of industrials."