Research by KPMG and the University of Texas surveyed 523 entry-level workers and recommends organizations train mindsets rather than merely teaching AI tool usage instead of just AI tools.
A study published in the Harvard Business Review (HBR) on 23 July 2026, conducted by researchers from the University of Texas at Austin and consulting firm KPMG, found that what distinguishes young people who use AI effectively at work is not their AI skills, but how they approach and manage tasks from start to finish.
This large field study surveyed 523 early-career employees, asking them to perform specialized business tasks using AI agent systems designed specifically for those tasks.
The research grouped participants into three categories: AI apprentices, AI delegators, and AI amplifiers. Surprisingly, foundational skills like critical thinking, AI literacy, and domain knowledge were not clear indicators of which group individuals belonged to.
According to an analysis by Inc. interpreting this research, those who use AI most effectively are the ones who integrate domain expertise, critical thinking, and AI understanding into every step of their work—from initial questioning and shaping outcomes to delivering results. This reflects a holistic skill set rather than fragmented abilities.
Conversely, some employees possess AI skills but apply them in ways that do not add value to the organization, while others appear effective by relying on AI to produce ready-made answers, effectively masking their lack of fundamental business knowledge.
This issue directly impacts hiring strategies, as researchers found that employees with similar foundational skills and knowledge can produce vastly different results when working with the same AI agent. Organizations that previously prioritized critical thinking and AI understanding in entry-level hiring may need to reconsider, since being proficient in AI is not the same as knowing how to use AI tools to solve complex business problems.
The research suggests that organizational leaders who want their young employees to benefit most from AI should focus on "what employees know" less, and instead emphasize training that focuses on framing problems, asking questions, and verifying AI outputs. They should teach how to improve results and use insights to support decision-making, guiding employees step-by-step—from crafting initial prompts, evaluating responses, refining queries, to producing meaningful work products. Additionally, AI learning should be continuous, tailored to individual skill gaps, and embedded in daily tasks and decisions rather than delivered as one-off training.
The analysis also emphasizes that organizations cannot treat AI as "set and forget" and should not assume Generation Z employees are instantly proficient in business AI simply because they are familiar with technology. This is akin to not assigning public relations duties just because someone is adept at TikTok or Instagram. The same principle applies to senior employees as well.
Source:Inc.