AI adoption in stewardship is accelerating, but many investors remain at an early stage. This Insight offers a snapshot of how stewardship teams are beginning to use AI, based on an IIGCC‑hosted investor roundtable and one‑to‑one discussion with investors. It also explores the important role of governance and how AI can support efficiency in stewardship activities.
For IIGCC’s position on the environmental impact of data centres and AI infrastructure, see our Insight piece here and learn more about upcoming events on the topic.
The current landscape
AI uptake is accelerating across financial services, including within stewardship processes. For many investors, the appeal is pragmatic: stewardship teams are often constrained by limited resourcing and are under increasing pressure to cover more companies, respond to expanding regulatory expectations and demonstrate outcomes.
Used strategically, AI tools can – and in some cases already do – support stewardship teams in navigating these pressures. Investors highlighted the potential for AI to help broaden stewardship coverage and reduce manual and resource‑intensive tasks such as reporting. However, the full benefits of AI use in stewardship have yet to be realised.
A number of significant challenges continue to hinder wider adoption and more systematic integration of AI tools, including regulatory uncertainty, gaps in skills and knowledge, concerns around reliability, safety and accountability, and persistent issues related to data quality and consistency. The central question is no longer whether AI will be incorporated into stewardship, but how it will work in practice.
How investors use AI today
AI is most commonly used to support individual productivity and administrative tasks, particularly those that are repetitive and information‑heavy. Typical uses include note‑taking, research and summarisation, engagement preparation, and basic analysis. These applications mainly reduce the time required for high‑volume, low‑judgement tasks, easing capacity constraints, without fundamentally changing stewardship models.
CASE STUDY: Brunel's advanced AI usage
In an IIGCC-led roundtable, Brunel presented five AI use cases, these include:
1. Stewardship report scanner - An AI tool used to organise all stewardship reports, enabling aggregation, search, and case‑study extraction across managers’ stewardship reports. This has significantly reduced the manual effort required to prepare stewardship reporting.
2. Horizon scanning for voting guidelines - AI tool reviews voting guidelines across the market to identify best practice and thematic strengths. Allows Brunel to compare its own guidelines with peers, and the tool can update as guidelines change.
3. Voting trend analysis - AI‑enabled NLP analyses approximately 50,000 voting records, providing more granular thematic insights than issuer‑level comparisons and supporting more informed discussions with service provider.
4. Manager data outreach tracker - AI tool assists in coordinating outreach and responses to engagement-data requests from external managers.
5. Responsible Stock Lending Recall Tool - An AI system that monitors stocks on loan and overlays relevant indicators to support recall decisions ahead of AGMs.
Brunel emphasised that clear instructions and robust quality control processes are key to improving output quality. Many of these tools were designed to reduce manual workload and enable stewardship teams to focus on decision‑making and engagement outcomes.
For most of these use cases, no programming expertise is required, as common workplace AI models are sufficient.
The governance imperative
Across the range of use cases, one point is clear: robust governance is essential. While AI tools can support and enhance stewardship activities, there is agreement among investors and experts that human judgement must not be replaced.
Stewardship remains fundamentally human-led, with AI tools acting as a support system through structured datasets and clear guardrails.
IIGCC members are converging on a set of core governance principles:
- Human oversight and accountability: Strong controls – such as audit trails and mandatory manual review – are critical to ensure that stewardship decisions are never fully delegated to AI systems.
- Data quality and integrity: Effective AI use depends on high-quality inputs. Members are addressing this through staff training on prompt writing and a clear focus on the risks and limitations of AI outputs.
- Systemic cross-checking: To reduce the risk of errors or hallucinations, some members are integrating multiple AI assistants into their workflows to enable cross-checking and automated troubleshooting.
What’s coming next
Looking ahead, IIGCC members anticipate AI becoming increasingly integrated into stewardship workflows. While processes are not expected to change overnight, gradual – and inevitable – transformation is widely anticipated. As adoption progresses, robust AI governance frameworks will remain the essential foundation.
One area of emerging interest is the partial automation of engagement reporting. Members highlighted the potential for meetings between companies and asset managers to be recorded, summarised, and shared with asset owners, significantly reducing reporting burdens while improving transparency across the stewardship chain.
At the leading edge, some organisations are pursuing more advanced integration. Here, AI is being embedded into operations beyond individual productivity, enabling organisation‑level data integration and analysis. In a limited number of cases, investors have already developed bespoke tools to support these approaches.
Overall, the direction of travel is clear, however the pace and form of adoption will vary significantly across organisations, reflecting differences in strategy, technical skills, risk appetite, and operational capacity.
How IIGCC can help
IIGCC is actively exploring how best to support members as AI use in stewardship evolves. The forthcoming Stewardship Toolkit 2.0 will include guidance on integrating AI into stewardship processes. We also want to ensure our future work remains grounded in the practical realities of investors’ day-to-day operations.
We welcome your input: How are you using AI in your stewardship work, and what support or resources would be most valuable - answer our questionnaire.