Minnesota companies are adopting artificial intelligence tools at a fast pace, but a recent Deloitte Tech Trends report shows 93 percent of corporate AI investments go to the technology itself, leaving only 7 percent for worker training. This imbalance creates workplace tension as businesses race to implement systems while employees struggle to adapt, delaying any return on investment.
The training deficit
Soumya Sen, an associate professor at the University of Minnesota Carlson School of Management, points out the flaw in current corporate strategy. "We are investing in technology but not in figuring out how the technology would be used, who would use it," Sen said. As a result, few companies have demonstrated a return on their AI spending. Many organizations make decisions top-down, ignoring the employees who will operate the tools daily.
Pairing technology with employee training
Some organizations are successfully pairing technology investments directly with employee education. Thrivent offers peer forums, live demonstrations, and team-specific training to help financial advisers use AI. Since introducing these tools last year, more than 90 percent of users remain active monthly. Advisers save an average of four hours per week preparing for meetings and summarizing follow-up tasks.
Austen Wilson, who leads a 20-person team at Thrivent, said that instead of focusing solely on technical expertise, he increasingly looks for candidates who are highly relational and possess the heart of a teacher. This evolution in workforce needs underscores why AI for Human Resources strategies must adapt to prioritize relational skills over pure technical expertise.
Mayo Clinic also pairs its technology investments with employee training, offering AI fluency courses and hands-on workshops. Matt Redlon, chair of Mayo's AI program, said the health system uses AI to summarize outside medical records and assist with documentation. "What's in the best interest of the patient is that the caregivers in front of them have time to focus on them," Redlon said. The organization also solicits ideas from employees, including a recent nursing department AI competition that generated hundreds of submissions.
The danger of shadow AI
When official training fails to meet employee needs, workers often adopt AI applications without company oversight or guidance. James Holmberg, co-founder of Vilas AI, calls this shadow AI. He warns that employees might use these tools with sensitive data because they lack proper direction.
"Employees are using tools on their own, with sensitive data, because the official training didn't meet their actual needs," Holmberg said. He compared the situation to handing everyone a box of matches at once. "Matches aren't dangerous - they're essential," Holmberg said. "But you don't hand someone a book of matches and hope they figure it out." This underscores why effective AI for Management requires leaders to involve end users in the rollout process rather than expecting them to adapt independently.
Why this matters for HR and management professionals
The gap between organizations building AI proficiency and those ignoring it is widening. Leaders must budget for employee education alongside software purchases to see a return on investment. Involving end users early in the rollout helps identify safe use cases and prevents unsanctioned data handling. Without structured training, companies risk wasted capital and severe security vulnerabilities in regulated industries.
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