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Why AI Literacy Is Hurting Productivity: Forrester's JP Gownder

April 10, 2026·21 min·2 clips

Gownder describes how employees waste 30 minutes on failed AI prompts, then give up and do the work manually.

1. UC Today hosts JP Gownder, VP and Principal Analyst at Forrester, to discuss results from Forrester's second AIQ (Artificial Intelligence Quotient) study on employee AI readiness. 2. Gownder designed the AIQ framework for Forrester clients; he describes himself as a researcher with his own AIQ gaps, not a neutral observer. 3. The episode's core thesis is that enterprise AI deployment is outpacing employee AI literacy, and that employers—not employees or vendors—are responsible for closing the gap. 4. AIQ is a survey instrument using a one-to-five agreement scale; Forrester deploys it across the US, UK, Germany, France, and Australia as a benchmarking baseline. 5. Prompt engineering comprehension—'I know what prompt engineering is and how to use it'—rose from 22% in 2024 to 26% in late 2025, a four-point gain despite over 80% of companies having deployed AI tools. 6. Confidence in adapting to AI-based work systems rose from 34% to 37% over the same period, meaning roughly 63% of employees still do not feel confident. 7. Understanding of responsible and ethical AI use rose from 39% to 44%, still leaving a majority of employees below the threshold Gownder considers adequate. 8. Gownder identifies the 'if we build it, they will come' vendor mentality as the primary cause of the literacy gap: tools are positioned as requiring no preparation, so employers make no investment in structured learning. 9. For most employees, the current cost of using tools like Microsoft Copilot, Google Gemini, or enterprise ChatGPT—in failed prompts and wasted time—often exceeds the productivity benefit they receive. 10. Gownder describes 'abandonment behavior': employees try repeated prompts, get no useful output, then revert to manual methods, which takes them off the AI learning curve entirely. 11. The ethical-AI literacy gap creates concrete business risks: hallucination, coherent nonsense, GDPR non-compliance, internal information oversharing, and reputational exposure from poor AI outputs. 12. Forrester added a new AIQ item asking whether employees sometimes refrain from using AI for ethics or privacy reasons—and Gownder treats a high score on this item as a positive indicator, not a problem. 13. Effective AI learning programs are not linear online training completed on the employee's own time; they are social systems involving champions, peer mentoring, weekly tips, and continuous iteration. 14. Gownder argues organizations must frame AI adoption around employee benefit—removing rote work, enabling new problem-solving, building career-relevant skills—rather than corporate productivity mandates. 15. The central paradox Gownder states: as AI deployment expands, organizations must invest more in people, not less. 16. Gownder previews the third AIQ iteration, which will add questions about comfort using agentic AI and whether employees believe their employer is committed to helping them master AI. 17. He also flags 'work slop'—AI-generated content that recipients recognize and don't read—as a direct form of negative productivity that current AIQ surveys will begin to track. 18. The interview format is structured Q&A with a UC Today host asking prepared questions; Gownder answers at length with specific data from the Forrester research. 19. Tone is analytical and cautionary, grounded in survey statistics, with Gownder periodically offering personal admissions about his own AIQ gaps to maintain credibility. 20. Best suited for HR leaders, L&D professionals, and CIOs responsible for AI rollout strategy; listeners seeking product-specific AI feature guidance will not find it here.

As heard by us

A plainspoken case for treating AI readiness as something teams build, not something individuals are left to improvise.

UC Today asks a plain question: do Copilot, Gemini, or ChatGPT actually make workers faster when support is thin? JP Gounder answers by way of AIQ, his term for employee readiness around AI tools.

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You want AI to save time, not quietly add more work.

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