The World Benchmarking Alliance (WBA) released its brief Closing the Workforce Blind Spot in Corporate AI Governance (July 2026). The assessment draws on 200 of the world's most influential technology companies covered by the WBA Digital Inclusion Benchmark, using publicly available AI governance disclosures and related corporate reporting.
Human Level’s Take:
- The next phase of AI governance is just as much about people as it is about technology. The WBA findings suggest that while companies are increasingly adopting AI governance principles, workforce impacts have yet to become a routine part of AI governance. As AI moves from experimentation to enterprise-wide deployment, greater attention will need to be paid to how it affects jobs, skills and workforce transitions.
- The biggest blind spot may be in what companies are not disclosing. The report finds that businesses have the greatest visibility into how AI is affecting their workforce, yet these impacts are rarely reflected in corporate disclosures. This limits the ability of policymakers, investors and worker representatives to identify where workforce risks are emerging and how companies are responding.
- Improving visibility is the first step towards managing workforce change. Closing this information gap would give policymakers, investors and worker representatives earlier insight into emerging workforce disruption and support more informed decision-making.
- But how can businesses respond without creating new reporting burdens? Rather than introducing a new reporting regime, the report proposes integrating AI-related workforce impacts into existing workforce, human capital and due diligence disclosures. This is presented as the first of three connected interventions, alongside earlier warning of workforce disruption and better transition support for affected workers.
- Hence, governance needs to extend beyond disclosure. Transparency alone is not enough. Companies are encouraged to assess the likely workforce impacts of AI, identify affected roles, and embed redeployment, reskilling and transition planning into their AI governance processes.
Some key takeaways:
- The nature of jobs is changing: AI is expected to reshape employment across both manual and cognitive occupations. Automation is expanding beyond manufacturing into administrative, professional and service-sector work, changing the nature of jobs across the economy. According to the IMF, around 40% of jobs globally are exposed to AI. In advanced economies, this rises to around 60%. Using China as an illustration of these broader trends, the brief estimates that 70.3 million workers face direct displacement pressure from AI. It also highlights that workers can play a dual role in the AI economy, contributing to the training of AI systems while also facing the prospect of those same systems reshaping or replacing aspects of their work. Against this backdrop, WBA argues that greater transparency on how companies anticipate and manage workforce transitions will be important to support effective policymaking, investment decisions and worker protection.
- The workforce gap in corporate AI governance: There is growing evidence that while AI is accelerating workforce transformation, corporate disclosure and governance have yet to keep pace with its social impacts. As companies increasingly deploy AI across their operations, limited disclosure on workforce impacts leaves policymakers, investors and worker representatives with reduced visibility into where AI-related workforce risks are emerging and how companies are responding. Although corporate AI governance is becoming more widespread, workforce considerations remain largely absent. Among the companies assessed, 39% disclose group-level AI principles (up from 26% in 2023), but only 13% reference workforce or employment in the context of AI, 6.5% link AI to training or reskilling, and only one company explicitly acknowledges that AI may displace jobs. Performance also varies across jurisdictions. Japan leads in the adoption of AI principles (64% of companies assessed) and the integration of human rights (43%), while the EU also demonstrates relatively strong uptake. By contrast, only 18% of Chinese companies assessed disclose AI principles. Overall, the findings suggest that clearer policy and regulatory expectations may support stronger corporate AI governance. However, the report concludes that existing AI governance and sustainability disclosure frameworks do not yet adequately capture AI-related workforce impacts, calling for workforce considerations to be integrated into existing disclosure standards.
- Strengthening workforce disclosure and transition planning: With 87% of the companies assessed making no reference to workforce impacts in their AI disclosures, strengthening workforce reporting is presented as a practical step towards improving transparency and supporting more effective workforce transitions. Rather than introducing a new reporting regime, it proposes treating AI as a trigger for disclosure within existing workforce, human capital and due diligence frameworks. Companies are encouraged to assess how material AI deployment may affect job structures, identify the roles and functions most exposed to AI, and disclose how they are managing workforce transitions through redeployment, reskilling and governance arrangements. These actions form the first of three connected interventions outlined in the report: stronger disclosure, earlier warning of emerging workforce disruption, and better transition support for affected workers. Improved corporate disclosure is intended to reduce the information asymmetry surrounding AI deployment, enabling stakeholders to identify emerging risks earlier and respond more effectively.
