Cambridge, Mass. — The rapid pace of AI development is putting CIOs in a tricky spot: Not only are they responsible for deploying tools that can boost productivity, they’re also working to ensure the tools can be utilized once deployed. The dynamic has made workforce upskilling efforts a priority.
It’s up to tech leaders to help shape a culture that enables AI experimentation, according to Monica Caldas, global CIO at Liberty Mutual Insurance.
“I do not believe that AI thrives in heavily authoritarian, top-down environments,” said Caldas, speaking last week at the MIT Sloan CIO Symposium. “I think the way people pick it up is through play.”
Along with encouraging experimentation, the risk profile of AI necessitates guardrails as businesses tackle change management.
“It’s not anarchy, but it’s also not authoritarian,” Caldas said. “You have to hit that sweet spot, and that’s where adoption really starts.”
Other businesses are preparing their employees through targeted training programs. More than half of leaders said they plan to upskill their workforce ahead of AI implementation plans, according to a January survey from Revature. More than 4 in 5 decision-makers flagged access to talent as a top concern.
Potential productivity wins can help existing staff embrace upskilling efforts, said Dimitris Bountolos, chief information and innovation officer at infrastructure company Ferrovial.
“What we have seen is an excitement of staff to be self-sufficient in activities that were really bureaucratic,” Bountolos said.
Revamped structures and roles
The deployment of generative AI tools caused a rush of interest in prompt engineering roles. Interest has since fizzled, as businesses began to understand that learning to prompt generative AI systems is a core skill that should be developed more broadly.
AI savviness should be embraced by the entire organization, according to Reshmi Ramachandran, head of partnerships and go to market strategy at consulting firm Cprime.
“When we consult with companies we often tell them: never do prompt engineering in isolation. It’s not an isolated job, it is actually a cross-functional skill,” Ramachandran said. “You get some of your best prompts from marketing leaders, from HR, because that’s where the context is.”
In addition to changes in job functions, departmental structures are also evolving.
The wave of AI adoption is helping to accelerate a shift away from the established pyramid-shaped organizational structures in software development, according to Aamer Baig, senior partner, Chicago, at McKinsey & Company.
“In the last decade or so, we’ve proven that is not the most effective and economical way of delivering software,” said Baig. A diamond-shaped model with a team of somewhere between eight to 12 was identified as the most effective.
But with the influx of agentic AI, that organizational structure is also changing.
“Now, we have a new model, which is enabled and powered by AI, that has a product person, product builders and many, many agents to support, which can deliver as much output as a diamond-shaped team does,” Baig said.
In addition to serving as CIO, tech executives will need to take on additional roles including “chief influencing officer, chief change management officer” as organizations adjust to shifts in their core talent and operational structures.
“The ability to move that sort of organization and that complexity forward will differentiate the winners and the losers in large companies,” Baig said.
