With almost 20 years in governance and stewardship, Rachit Gupta has worked across research, proxy voting and investor stewardship. Before joining Diligent Market Intelligence (DMI) in 2022, he held research and stewardship roles at Institutional Shareholder Services (ISS), Aviva Investors and Capital Group. He now leads DMI's stewardship intelligence business, helping build the infrastructure behind modern, independent stewardship programs from London.

You have spent almost two decades in governance. What has that experience taught you about the role of data in stewardship?

I spent more than 15 years researching companies’ governance and remuneration profiles for proxy advisors. At ISS, I progressed to deputy head of U.K. research and later worked in stewardship teams at asset managers like Aviva Investors and Capital Group.

Those roles gave me a clear view of what investors need: accurate, relevant intelligence on the companies they cover, delivered in time to support a real decision. And not just in time to lodge a vote, but in time for deeper engagement or consideration during a hectic proxy season. Data is not separate from proxy voting; it is essential to the stewardship workflow. It shapes how teams prioritize research, apply voting policies rigorously, prepare for engagement and explain their decisions internally and externally.

What did you see firsthand as an investor that informs your work at Diligent?

Investors need both breadth and flexibility. The questions they ask change depending on their mandate, portfolio, region and investment philosophy. Coverage universes can change somewhat unexpectedly, so it’s important to have access to broad datasets, but depth is also critical. Just as importantly, they need data that fits their workflow. A stewardship team may want a feed into an internal system, an impact assessment on a proxy voting policy change, a report for a committee or a structured dataset to support a policy engine. The use case may be highly specific.

Stewardship teams need to understand a company’s governance and compensation, but also past voting records, vulnerability to shareholder pressure, and the track records of shareholders who are nominating directors or filing proposals - something that not all proxy advisors provide a lot of color on.

What separates leading stewardship teams today?

Leading teams are moving from reactive processing toward continuous intelligence. They are monitoring portfolios year-round, testing their policies against real voting behavior and identifying issues before proxy season compresses the decision window.

They are also becoming more deliberate about what coverage they need. Active managers may require deeper context on a particular region, index, ADR or investor group, while other teams may prioritize scalable global coverage. A data provider has to be flexible enough to adapt as those needs change.

The most proactive teams combine data with a clear operating model: automate routine work, focus human attention on exceptions, and use historical intelligence to inform engagement before concerns become public.

Where does AI fit into global stewardship research?

Advances in data delivery and AI have created new ways to collect, structure and use intelligence - developments we have embraced alongside a major expansion of Diligent Market Intelligence’s coverage, built on our historic strengths in shareholder activism and proxy voting and the growth of our research teams in London, Budapest and Bangalore. However, stewardship teams need reliable, defensible data sources. Querying an LLM and producing unique results at different points in a voting process is a threat to the integrity of their fiduciary duty.

Global governance research is complex. Companies report in different formats, governance structures vary by market, and an apparently simple data point can require judgment and context. That is why AI needs to build on the expertise of experienced researchers, with human review remaining central both at Diligent for accuracy and consistency, and for stewardship teams to bring nuance and appropriate benchmarking. This year, in partnership with one of the world’s largest asset managers, we launched our Stewardship Intelligence data feed, providing more than 850 compensation and governance data points deliverable via Snowflake. We use a multi-reviewer process so that data is vetted before release, while still working to deliver it earlier than proxy advisory firms within the narrow window between a proxy filing and a shareholder meeting.

We’ve learned a lot by being nimble but it’s been a great experience and left us more convinced than ever that technology is going to shake up the stewardship research market.

Over time, I expect AI to play a larger role in custom voting policy execution. It can apply standardized rules across routine decisions while flagging edge cases for stewardship teams to investigate, discuss and potentially engage on. The goal is not to replace judgment, but to augment it to focus where it matters most.

Can you elaborate more on how Diligent is thinking about using AI in the future?

As an AI-first organization, we are uniquely positioned to leverage AI-led data extraction with strict parameters around standardizing the data to allow for relative assessments, without falling into the trap of trusting the machine better than the experienced judgement of trained researchers. Our clients hire us to navigate through the filings and provide the data in a consistent, coherent manner and whether manually collected or AI-led extracted, the human oversight in the review process becomes extremely critical.

Using standardized, structured data makes the outcome of the custom policy engines significantly accurate and is a different approach to many of our competitors who are using AI to answer custom policy guidance straight at source filings. While we take the additional step of extracting raw data and categorizing it, it allows our clients to fully own their voting decisions with confidence in the analysis.

Another exciting opportunity is when institutional investors are looking to update their proxy voting policies; the impact assessment analysis can be done in minutes with AI rather than the traditional monthslong process.

Where would you like to take Stewardship Intelligence next?

The Snowflake data feed has been very popular because it gives clients a flexible way to bring structured intelligence into their own systems. We want to build on that foundation with a stronger capability for data visualization, including pre-meeting reports, custom voting policy execution, engagement recording and tracking, stewardship reporting and vote disclosure.

We’ve been listening to the needs of the stewardship community over the last few months and are excited to meet the industry at CII later this month and at ICGN and our own Stewardship Series in November. For anyone attending any of these events, please get in touch to arrange time to learn more about what we’re doing.