AI and the future of work: An investor briefing

21 October 2026 - AI is reshaping work, organisations and the wider economy, creating new risks and opportunities for investors. This briefing explores the financial implications of AI-driven workforce transformation, highlighting key tensions for long-term value creation and practical indicators investors can use to assess company preparedness. 

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The AI-related workforce transformation is financially material to investors because it changes the very nature of jobs, tasks and economic activities, reshaping the foundations of company valuation. For investors, this creates a critical tension: the same decisions that generate near-term financial gains through automation and efficiency can also create longer-term organisational risks in terms of company resilience and future performance stability.  

Drawing on interviews with global institutional investors, as well as leading academics and experts within this field, this brief provides a live understanding of how investors are thinking about the workforce transformation and the key questions that are emerging as priorities.  

We identify four interconnected themes driving the AI-related workforce transformation: the changing nature of work, changing organisations, changing labour markets and the changing economy.  

What drives materiality for investors is the tensions emerging from these themes:  

• Short-term efficiency versus long-term organisational resilience: While automation may reduce costs and improve operating margins, workforce reductions could undermine institutional knowledge, critical skills and future talent pipelines, weakening companies' long-term competitiveness. 
• AI adoption versus durable value creation: High adoption rates do not necessarily translate into stronger financial performance. Research cited in the briefing shows a significant gap between reported individual productivity improvements and measurable contributions to company earnings. 
• Portfolio diversification versus common AI dependencies: AI-related risks extend beyond technology companies. Shared dependencies on AI infrastructure, technology providers and workforce transformation could create vulnerabilities across seemingly diversified investment portfolios. 
• Company-level impacts versus system-level risks: The cumulative effects of AI on employment, productivity and income distribution could influence consumer demand, inflation, government revenues and borrowing requirements, with wider implications for sovereign risk and asset valuations. 

What can investors do?  

The briefing identifies six areas of company preparedness that investors can monitor, covering strategic alignment, workforce involvement, governance, workforce transition, realised financial value and technology dependencies. 

Together, these provide practical indicators for assessing company readiness and understanding where AI-driven workforce transformation may create financial risks and opportunities. 

What’s next?  

The research represents the first phase of the ILG's wider programme on AI and the future of work. The next phase will explore how investors can integrate these findings across investment processes, from asset allocation and due diligence to portfolio construction and stewardship.