by Peter du Pont (Co-CEO) and Mrutyunjaya Nanda (Team Leader for Technology & Markets)

What if we could listen to more stakeholders, synthesize insights faster, and design clean energy programs that reflect real-world needs without sacrificing rigor? That question sat at the heart of ACE Partners’ recent presentation at Energy Evaluation Asia Pacific’s (EEAP) webinar on 11 February 2026: “From Data to Design: Using AI to Improve Clean Energy Interventions.”

Peter du Pont (ACE Partners Co-CEO) and Mrutyunjaya “MJ” Nanda (Team Leader for Technology & Markets) were invited by the EEAP team to share how ACE Partners is integrating AI into qualitative research and program design as a catalyst for deeper insights and analysis, particularly in our firm’s stakeholder engagement efforts.

Why AI Matters in a World of Complex Energy Decisions

Clean energy solutions sit at the intersection of evolving policies and markets, technological constraints, and local realities. Traditionally, understanding these dynamics has required weeks (or months) of interviews with stakeholders, transcription, note taking, and manual synthesis.

But the region is moving faster. The stakes are higher. And the decisions are more complex.

Peter and MJ emphasized that AI can help us keep pace if used responsibly, within a disciplined, evidence-driven process. They also underscored that clean energy programs succeed when they reflect lived experience. Policymakers, utilities, financiers, developers, and communities all see different parts of the energy transition, and interviews remain one of the most effective tools for capturing these perspectives. However, interviews create a challenge: how do we transform dozens of hours of qualitative data into focused, strategic recommendations?

That’s where AI changes the game.

From Raw Transcripts to Actionable Evidence

Peter and MJ shared the ACE Partners workflow, refined across multiple assignments with development partners such as the Asian Development Bank (ADB):

1. Identify and engage a broad set of stakeholders across government, private sector, development institutions, and communities.
2. Conduct semi-structured interviews with consent, encouraging candid, narrative responses.
3. Transcribe using AI tools which produce high quality text within minutes.
4. Summarize and extract insights using carefully designed prompts. This step is crucial. Excellent prompts uncover themes, contradictions, priorities, and opportunities.
5. Validate findings with stakeholders by sharing transcripts and key points back to interviewees to confirm accuracy and build trust.
6. Synthesize insights with desk research. AI accelerates the first-level analysis, but expert judgment drives interpretation and recommendations.

Peter and MJ illustrated this approach through two recent assignments of ACE Partners.

Private Sector Assessment in the Philippines:
The stakeholder interviews that were part of this project revealed issues often invisible in official documents, such as informal practices, institutional bottlenecks, and sector-specific constraints, and AI enabled faster and more systematic synthesis of those insights. These insights fed into ADB’s strategic discussions and helped refine the sequencing of interventions and informed discussions between ADB and the Government of the Philippines during the crafting of its Country Partnership Strategy for 2024-2029.

ADB Private Sector Operation Department’s Climate Ambition Plan:
With 40 interviews completed in just three weeks, our AI-assisted workflow allowed the team to rapidly map internal constraints, identify immediate and “blue sky” investment opportunities, and deliver interim findings while strategy discussions were still underway. The process strengthened cross-team alignment and contributed to renewed confidence within the department. In the months that followed, ADB increased the level of ambition for its private sector climate finance target.

In both cases, AI did not replace expert judgment. Instead, it expanded our ability to listen broadly, consistently, and at scale. The result is faster, more transparent, more grounded program design.

A Smarter Path Forward for Design and Evaluation of Clean Energy Programs

As shared with the EEAP community, AI is not a replacement, but an accelerant, for evaluation thinking. It helps practitioners move smarter and faster without compromising the discipline or evidence base that good program design demands.

The clean energy transition across Asia is becoming more complex and more urgent. To address this, ACE Partners thoughtfully combines rigorous qualitative methods with AI. If you’d like to learn more about our work or discuss how AI-enabled research can support your program or strategy, we’d be happy to connect:

connectwithus@asiacleanenergypartners.com