CEOs Race Towards Gen AI Adoption

A new study by the IBM Institute for Business Value found that CEOs are facing workforce, culture, and governance challenges as they act quickly to implement and scale generative AI across their organizations. The annual global study of 3,000 CEOs from over 30 countries and 26 industries found that 64% of those surveyed say succeeding with generative AI will depend more on people's adoption than the technology itself. However, 61% of respondents say they are pushing their organization to adopt generative AI more quickly than some people are comfortable with.

The findings also revealed that nearly two-thirds (63%) of surveyed CEOs say their teams have the skills and knowledge to incorporate generative AI, but few understand how generative AI adoption impacts their organization's workforce and culture. More than half (56%) of respondents have not yet assessed the impact of generative AI on their employees. Yet, 51% of CEOs surveyed say they are hiring for generative AI roles that did not exist last year, while 47% expect to reduce or redeploy their workforce in the next 12 months because of generative AI.

"There is incredible excitement around generative AI, and CEOs want to move beyond the AI hype to deliver business impact. Yet, without the right people and culture in place, progress will be slow," said Matt Candy, Global Managing Partner at IBM Consulting. "As they embed generative AI in their enterprise strategy, it's critical that executives build a cultural mindset that fosters adoption and leads people through the changes."

40% of CEOs surveyed plan to hire additional staff because of generative AI. Yet, more than half (53%) of respondents say they are already struggling to fill key technology roles. CEOs say 35% of their workforce will require retraining and reskilling over the next three years – up from just 6% in 2021. 65% of CEOs say their organization's success is directly tied to the quality of collaboration between finance and technology, yet nearly half (48%) say competition among their C-Suite executives sometimes impedes collaboration.

Most (81%) CEO respondents say that inspiring their team with a common vision produces better outcomes. At the same time, 37% acknowledge that their employees don't fully understand how strategic decisions impact them. 57% of those surveyed acknowledge that cultural change is more important to becoming a data-driven organization than overcoming technical challenges. CEOs cite generative AI adoption as being critical to success, but nearly two-thirds (64%) of surveyed CEOs say their organization must take advantage of technologies that are changing faster than people can adapt.

More than two-thirds (68%) of CEOs surveyed agree that governance for generative AI must be established as solutions are designed, rather than after they are deployed. Although 75% say trusted AI is impossible without effective AI governance in their organization, only 39% say they have good generative AI governance in place today. At the same time, 62% of CEO respondents say they will take more risk than the competition to maintain a competitive edge, with half (51%) agreeing that the risk of falling behind is driving them to invest in some technologies before they have a clear understanding of the value. 67% of surveyed CEOs say the productivity gains from automation are so great that they must accept significant risk to stay competitive. While today 71% of surveyed CEOs are no further than generative AI piloting and experimentation, 49% expect to be driving growth and expansion by 2026.

CEOs surveyed ranked product and service innovation as their highest priority for the next three years – up from sixth place in 2023. 41% of respondents say they are willing to sacrifice operational efficiency for greater innovation. However, a majority of CEOs point to a focus on short-term performance as their top barrier to innovation. Today, only 36% of the CEOs surveyed are primarily funding their generative AI investments with net new IT spending, with the remaining 64% reducing other technology spending.