KPMG Study: 4 Ways Workers Use AI Better for Complex Tasks

A new KPMG study looked at 1.4 million AI uses. It found 4 ways workers use AI better, like asking bigger questions and fixing AI answers.
By Newsroom | Technology, Business |

KEY BEHAVIORS MARK SOPHISTICATED ARTIFICIAL INTELLIGENCE ENGAGEMENT

Analysis of 1.4 million workplace interactions between employees and artificial intelligence systems has illuminated distinct behaviors associated with what researchers are calling "sophisticated AI collaboration." The study, which examined eight months of data from KPMG LLP's back-office operations, points to four key signals differentiating routine use from more impactful engagement.

Sophisticated AI use correlates with frequent AI revisits, persistent refinement of AI outputs, ambitious initial user requests, and intentional selection of AI tools or models.

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For a select group of users, AI transcends being a mere productivity tool, functioning instead as a broad 'cognitive tool'. This implies a deeper integration into problem-solving and idea generation processes, moving beyond simple task completion. This distinction suggests that simply adopting AI technologies does not guarantee their effective utilization.

DEFINING SOPHISTICATED ENGAGEMENT

The research identified specific user actions that mark a higher caliber of AI interaction. These include:

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  • Iterative Engagement: Users frequently return to the AI, indicating ongoing refinement and exploration.

  • Output Perfectionism: A tendency to persistently revise and improve the AI's generated responses.

  • Ambitious Inception: Initial requests are often broad and complex, aiming for more substantial outcomes.

  • Strategic Tool Selection: A deliberate choice of specific AI tools or models suited to the task at hand.

Furthermore, sophisticated users reportedly set clear objectives, articulated specific demands, and delegated cognitively challenging tasks, such as brainstorming, in-depth analysis, technical guidance, and complex problem-solving, to AI systems.

IMPLICATIONS FOR ORGANIZATIONS

The findings are informing strategies for organizations aiming to cultivate more effective AI usage. KPMG, for instance, is incorporating these insights into its client work, focusing on helping other organizations:

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  • Define what successful AI use looks like internally.

  • Build role-specific AI capabilities.

  • Equip leaders to scale sophisticated human-AI collaboration within daily operations.

This involves deliberate efforts to make effective behaviors visible and expected through structured training programs, routines, and guidance on problem framing, AI supervision, and purposeful iteration.

BACKGROUND CONTEXT

The impetus for this research stems from the widespread acceleration of AI adoption across industries. As organizations invest in these technologies, a critical question emerges: is this adoption translating into measurable improvements in the quality, speed, and ambition of work? The study posits that understanding and scaling "high-impact AI capability" requires a concrete roadmap, derived from observable user behaviors.

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While this specific study focused on KPMG's internal operations, the researchers suggest these identified behaviors offer a generalizable blueprint for cultivating more advanced AI collaboration across various workplaces. The notion of AI as a 'general cognitive tool' points towards a future where artificial intelligence is not just an assistant, but a partner in complex thought processes.

Other related academic work touches upon the dynamics of user engagement, the paradox mindset in human-AI collaboration, and how AI literacy influences workload. Research also explores the impact of human-AI collaboration on employee motivation and the broader effects of AI on business performance, suggesting a complex interplay between technology, human behavior, and organizational outcomes. Some studies have even begun to categorize AI's role in collaboration as automation or augmentation, highlighting its multifaceted potential.

Frequently Asked Questions

Q: What did the KPMG study find about using AI at work?
A study of 1.4 million AI uses at KPMG found that some workers use AI in more advanced ways. These workers use AI for complex problems, not just simple tasks.
Q: What are the 4 key behaviors of sophisticated AI use found by KPMG?
The study found 4 key behaviors: users go back to AI often to make answers better, they try to perfect AI answers, they ask big questions at first, and they pick the right AI tool for the job.
Q: How does sophisticated AI use differ from normal AI use?
Sophisticated AI use means AI is like a 'thinking tool' that helps with hard problems and new ideas. Normal use is just for doing tasks faster.
Q: Why is this KPMG study important for companies?
The study helps companies understand how to get more from their AI tools. It shows how to train workers to use AI better for important tasks and problem-solving.
Q: Can other companies use these findings from the KPMG study?
Yes, the study suggests these behaviors can be used in many workplaces. It gives a plan for companies to help their staff work better with AI on difficult tasks.