Informatica transforms IT teams into AI builders

As generative AI became a top-three tech priority for 89% of executives in the past few years, Informatica’s IT team saw both its transformative potential and the challenges in delivering value rapidly. The company was receiving several specific data use case requests from different business units across the company, creating pressure to deliver AI solutions quickly and effectively.

“The magic of AI is that it looks so easy,” says James Gregory, VP of AI, Data and Enterprise Platforms & Infrastructure at Informatica. “People might think you can just take a chat interface and point it at a bucket of data, and we can instantly get summaries and action items and answers. But to build those solutions we had to learn Python code and other AI technologies, and it was slow going.”

Initially, the team took a manual hand-coding approach, developing custom solutions for each use case. This approach was inherently limited by the skills gap in the marketplace and the growing shortage of developers with Python skills. With the AI landscape evolving rapidly, there were also concerns about long-term viability and maintenance.

“Do I build my own solution, hand-coding with our existing team?” reflects Gregory. “Do I augment by filling headcount, or hire a consultant to do this? Or do I go find a platform that can help eliminate hand-coding and make the whole process more efficient?”

That’s when the IT team realized there was a GenAI development solution sitting right within Informatica’s existing DMC platform.

With millions of leads in Marketo and Salesforce, Informatica’s Sales and Marketing teams were looking for a better way to populate and manage records’ quality. While leads were scored daily (0-100) and classified (A-E), the scores alone lacked context and actionable insights, making it difficult for revenue teams to take the most effective steps to increase lead scores and move opportunities closer to conversion.

The IT team saw an opportunity to harness existing data to fill in this context gap. Using IDMC, they built an AI agent that analyzes lead data, customer metadata and a business glossary to automatically generate score summaries with recommended actions directly within Salesforce. The solution integrates data from Marketo and Salesforce, processes it through IDMC and Azure Data Lake Storage (ADLS) and delivers insights back to users through their given interface.

"With the click of a button, we now get complete insight on every lead score and customized next actions for converting leads into opportunities,” says Nagarajan Radhakrishnan, Director of Marketing Analytics and Data Operations.

With 100% of lead scores in Salesforce now contextualized, the revenue team has already seen significant improvements in marketing effectiveness and AI-enhanced targeting and personalization, including a 50% increase in conversion rates across initial tests.

As leadership often scrutinizes software costs, Informatica’s IT Service Management team was also looking for a better way to manage licenses across over 5,200 global employees. Previously, a lack of context about software usage required a significant amount of time-intensive research to identify duplicative licenses. This inefficiency also led to missed opportunities to streamline vendors, reduce license costs and maintain compliance.

To modernize its IT procurement oversight, the team built an AI agent using IDMC to automatically analyze installation metadata from all Informatica employee laptops using Snow Agent. The solution categorizes software by type and vendor while generating precise usage summaries to identify redundancies and optimizations.

“Now that we have all this detailed metadata readily available, we can easily audit our systems, remove apps that are against policy and identify cost-saving opportunities,” says Chinthamalla.

After collecting all this information, 100% of software is now categorized and contextualized with minimal manual work. Moving forward, the team will aim to streamline licenses through fewer vendors and reduce duplicative software costs, with a target of up to 50% projected savings.

Building on the success of these initial GenAI implementations, Informatica has progressed to more sophisticated Agentic AI solutions. Faced with growing cloud costs and the challenge of resource optimization falling outside developers’ daily workflows, the IT team developed CloudMinder, an AI agent specifically designed to address cost optimization through owner-driven resource management.

CloudMinder uses IDMC’s data and application integrations to increase transparency of cloud environments and costs while providing AI-driven insights and trending analysis. The Agentic AI solution aims to reduce cloud costs by 20% through intelligent automation and improved reporting, demonstrating how the platform's data-agnostic nature and pre-built "recipes" enable rapid deployment of more complex AI agents.

"The evolution from simple automation to sophisticated agentic AI shows the scalability of our platform approach," notes Agrawal. "What started as basic process improvements has grown into intelligent agents that can make autonomous decisions and drive significant cost savings."