Cristina Pieretti, General Manager and Head of Generative AI Solutions talks about the next phase of Moody's GenAI strategy
When generative AI entered the mainstream in late 2022, it did so with unprecedented velocity. ChatGPT reached 100 million users in just two months, prompting firms across industries to assess their readiness. At Moody’s however, that assessment was already well underway, with concrete steps set in motion.
In a recent interview with Microsoft's partner magazine, The Technology Record, Cristina Pieretti, General Manager and Head of Generative AI Solutions, reflects on how Moody’s recognized early that generative AI wouldn’t simply enhance productivity; it would fundamentally change how knowledge work happens in financial services. The challenge, as she saw it, was to harness that potential in a domain defined by regulatory scrutiny, data complexity, and analytical rigor.
Moody’s first major step came in December 2023 with the launch of Research Assistant, a natural language interface built on Microsoft Azure OpenAI and our proprietary data estate. The tool now gives users streamlined access to information on over 190,000 companies, including earnings transcripts, credit ratings, filings, and sector research. Within weeks, more than 115 clients had adopted it, using the interface to summarize calls, generate peer comparisons, and extract insights that previously demanded hours of manual work.
And as AI usage exploded, the potential to expand to other use cases quickly became apparent. For Moody's, it was critical to continue building on Research Assistant even as the team took the next step to “automate the workflow”.
That next step is now taking shape in the form of Agentic AI.
From information retrieval to autonomous analysis
Where Research Assistant brought speed and accessibility, Agentic Solutions is designed to deliver both structure and autonomy. These aren’t general-purpose assistants; they’re modular systems developed to complete high-value analytical tasks from start to finish.
Examples include generating credit memos and deal summaries, surfacing early warning indicators, monitoring issuers and sectors, and transforming unstructured inputs into decision-informing outputs. Each agent is grounded in our curated data, and aligned with internal standards of transparency, traceability, and auditability.
Industrializing generative AI responsibly
At Moody’s, our approach to GenAI is rooted in execution and integration -- an approach that has already delivered measurable results with our first AI solution, Research Assistant. Tasks that once took days, such as compiling risk summaries or producing peer comparisons, can now be completed in minutes. Outputs are consistent across teams, geographies, and sectors.
It's an approach we're committed to across the board. As Pieretti explains, “Agentic AI is transformational, but its power comes from being embedded within real business processes.”
Rather than chasing speculative use cases, we’ve prioritized aligning our models with the decision-making frameworks our clients already rely on, and making sure those models are auditable at every step.
From proof of concept to competitive edge
While many organizations remain in the exploratory phase, Moody’s has long moved from concept to implementation. This shift reflects a strategic alignment between our data, infrastructure, and client needs.
Pieretti is direct about the stakes: “It is better to be the disruptor than the disrupted.”
For her, the agentic transformation isn’t just about working faster, it’s about working smarter. Analysts gain more time for judgment. Decision-makers gain higher-quality inputs. And clients gain clarity, consistency, and confidence.
Learn more
To explore Cristina Pieretti’s full perspective on our GenAI strategy, read the full interview in The Technology Record.
For more on how we’re delivering secure, auditable AI at enterprise scale, visit our Agentic solutions page.
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