ESCAPING AI PRODUCTIVITY TRAPS: A LEADERSHIP PLAYBOOK FOR ARTIFICIAL INTEGRITY

Abstract The author is Group Vice President at Thales, a lecturer at INSEAD and HEC Paris, originator of the concept of “Artificial Integrity,” and an AI researcher. He ebelieves that “five traps neutralize AI's productivity promise.” These traps, in his words, are Trap 1: The sum‐of‐tasks fallacy. Trap 2: AI‐mediated Pseudo Work. Trap 3: Local wins and systematic bottlenecks. Trap 4: Bolt‐on adoption breaks. Trap 5: Ignoring intangible inputs. He further writes that “the focus should shift from the narrow task a system performs at a particular place and time within specific teams to enhancing the organization's human capital while safeguarding its integrity.” He weaves in his concept of Artificial Integrity, observing that “for AI‐enabled work, Artificial Integrity means AI systems that (1) states purpose, context, and limits for each use, (2) protects human capacities and values where they drive outcomes, (3) measures system flow and decision quality, not activity volume; and (4) aligns incentives and governance so speed compounds into value without eroding the social fabric.” He concludes that “as a north star for envisioning AI systems’ capabilities, Artificial Integrity is what keeps efficiency focused on meaningful outcomes, not on volume or speed for their own sake.”