ai-stakeholder-balance

Read [runtime](../../content/RUNTIME.md) and [advisory rules](../../content/policies/advisory.md) before applying this skill. Other Foreman layers and the catalog are in `../../content/`, relative to this SKILL.md. # AI Stakeholder Balance A scale, by definition, must have two sides. Most leaders deploying AI place efficiency on one side and load the other with nothing at all -- then marvel at how quickly things tip over. The promise of artificial intelligence is real: faster decisions, lower costs, sharper predictions. But efficiency is not a value-neutral concept. Efficiency *for whom* is the question that separates organisations that extract lasting value from AI from those that generate headlines about algorithmic bias, workforce revolts, and regulatory backlash. When Boston deployed an AI-optimised school bus scheduling system designed by two MIT graduates to trim a $100 million transportation budget, the algorithm dutifully reshuffled start times across hundreds of schools. It did not, however, consider that shifting elementary school start times to 7:15 a.m. would create a childcare gap that forced parents to change jobs or scramble for emergency arrangements. The city dropped the plan. The algorithm had optimised for cost. It had forgotten the humans. --- ## The Framework ### The Stakeholder Triad in AI Adoption AI adoption decisions radiate outward in concentric circles. At the centre sit the three stakeholder groups whose interests a leader must actively bala...