For the fifth consecutive year, MIT Sloan Management Review and BCG have gathered global AI experts to explore how responsible AI (RAI) is practiced across industries. While past discussions concentrated on AI maturity, risks, and governance pillars like accountability and transparency, rising anxieties about AI’s effects on employment have come to the forefront. Many companies have reported layoffs citing AI-driven efficiency as a reason, prompting calls to consider workforce implications as a critical part of responsible AI.
A strong consensus among experts emphasizes that responsible AI should not only address system safety and bias but also acknowledge its sociotechnical nature—how AI reshapes jobs, skills, power dynamics, and economic stability. Workforce impact must be integrated into AI governance at all levels, including board decisions. Neglecting this can lead to serious social and economic challenges, including worker displacement, increased inequality, and reduced consumer trust.
Experts advocate for comprehensive strategies involving reskilling and transparent communication with workers, though they highlight that human learning may lag behind technological advances. Responsibility for managing AI’s workforce effects is shared across businesses, governments, and policy makers. Without deliberate leadership and proactive policies, the negative consequences on workers and society may outweigh the benefits gained from AI efficiencies.
To address these challenges, organizations should broaden RAI frameworks to include workforce considerations, embed workforce metrics in AI strategy, evaluate worker impacts alongside technical risks, involve employees in decision-making, and designate clear accountability for workforce-related outcomes.
