November 11, 2026 • 7 Min Read

He wanted it to help researchers sift through test results and find a compound that would meet customers’ needs. If the team could find the compound sooner, the company could bring a new product to market faster. He saw that as a good place to put the company’s limited AI budget. His colleague, the general counsel, thought the company should be moving even faster and doing more across the entire organization rather than just focusing on R&D. 

The difference of opinion over the pacing of AI investment emerged in an RGP roundtable discussion in Cleveland that brought together senior executives from across industries. Over the course of the evening, executives discussed where to invest in AI and how to tell whether those investments were paying off. The conversation also included debate about how work needs to be redesigned, and how people will gain experience and judgement in the future. 

What Counts as a Return 

“Do you feel you are moving fast enough to stay competitive over the next three years?” asked Jessica Block, RGP’s Chief AI Officer, Interim CFO and moderator of the roundtable discussion. 

Around the room, executives described what they would count as a return in their own businesses. A university fundraising executive had regular campaigns to ask for gifts, but he also wanted to give donors a reason to stay connected between appeals. The fundraising team used AI to send thank-you notes, birthday greetings and university updates to a group of donors. Those donors still received the usual fundraising appeals as well. 

In the first year giving participation doubled and donor retention tripled compared with the previous year. That gave the foundation board an early result to celebrate. Now the fundraising team is looking further ahead. Would donors who heard from the university between appeals keep giving over several years? 

“We’re playing the long game here,” the executive said. 

For a procurement leader, the value of AI comes in how soon his business sees savings. His team negotiates contracts and runs sourcing events, where suppliers compete for the company’s business. What if his team could complete a program in 12 months instead of 18?  

“Those are the KPIs we need to have,” said the leader, “It’s really all about where we decide to place our bets.”  

Where the Saved Time Goes 

In RGP’s new research report on AI, roughly two-thirds of respondents expected AI to perform most of their current tasks within five years. Only 3% felt replaceable, and 94% believed their experience brought value beyond what AI could provide. In Cleveland, the discussion turned to what to do with the time employees will have. In the research, employees said AI already helped them work faster, but the time they gained often filled with more work.  

“Does the capacity created by AI create revenue or avoid costs?” Block asked the room. 

Several executives admitted they had little visibility into how the new time was being used. “The connection is hard to see when employees save time on scattered tasks throughout the week,” said one finance leader. “Each person can be busy and productive while the work the business most needs done is still waiting.” 

Executives agreed that having conversations and strategizing with employees and teams about how to divert their attention to new areas of valuable work needs to be a big part of the AI investment decision upfront. If AI will shorten a task, managers and employees need to agree on what deserves the time it frees up. One contributor argued for involving employees in redesigning the processes they know firsthand. They can show a leader which steps are already changing and where a handoff still depends on someone who knows the business. They are also the people most likely to notice when day-to-day practice has moved ahead of company policy. 

How Will Junior Employees Gain Experience 

The RGP research found that 51% of Gen Z respondents turned to AI first for complex problems, compared with 7% of executives. The discussion moved to how AI will change learning and the implications of AI involvement so early in junior employees’ careers. 

A tax professional saw an advantage in the new habit of turning to AI. Younger colleagues could get to an answer in a fraction of the time it once took him to learn the material. Yet a technology executive wondered how junior employees would even be able to tell when the answer was wrong? He had watched his son use AI to do his homework, without really knowing or being able to understand whether the output was correct. 

“I think we still need to teach our children math. We don’t give a kindergartener a calculator,” he added, “Young people will need to learn how to think.” 

Block saw a way to use AI itself in teaching. She compared it to taking apart a radio. Give someone an answer and have them work backward to figure out why it holds up. In a finance team, that might mean asking a new analyst to trace an AI-generated explanation of a variance back to the underlying transactions and show which ones support it. 

What concerned a lawyer in the room most was how a junior associate would learn to earn a client’s trust. “Knowing the law is part of that job. So is hearing what a client is worried about and explaining a decision in terms that make sense to them,” she added, “That takes practice with clients and time with colleagues who can help a new lawyer understand what happened in the room.” 

As the evening ended, it became clear that the redesign of work belongs in the same conversation as the business case or AI will not produce ROI. And, if AI takes over work that once gave people their first experiences and judgement, executives need to deliberately determine where there needs to be human intervention, how that intervention manifests itself and who will continue to be there, on a very human level, to help younger employees grow and thrive.