Salesforce and Informatica in $8 Billion AI Data Deal: 5 Strategic Synergies
Marc Benioff envisions "the ultimate AI-data platform"
Welcome everyone! I’m John Foley, a long-time tech journalist who has also worked in strategic comms at Oracle, IBM, and MongoDB. Now I’m an independent tech writer.
Salesforce and Informatica are joining forces in an $8 billion acquisition to seize the moment as businesses look to accelerate the development and deployment of enterprise AI, and in particular agentic AI.
The definitive agreement, announced today, puts Salesforce in a stronger position to deliver on CEO Marc Benioff’s vision of digital labor, where AI agents are introduced into everyday workflows to augment human labor and boost business productivity. The major stumbling block has been, and continues to be, data quality and other processes around data readiness, things like data cataloging and metadata management.
I know these companies well, having covered both since they were startups. (Informatica was founded in 1993, Salesforce in 1999.) In the past 10 months, I have attended four Salesforce events — including Dreamforce and its TDX developer’s conference — and I just returned from Informatica World in Las Vegas. This analysis is informed by those public events where company leaders and customers talked about their strategic efforts.
Disclosure: I work with Salesforce and Informatica (separately) as a tech writer through my former employer Method Communications. I’ve also attended a few Salesforce events as a partner/influencer. This blog post is independent of those relationships; it was not reviewed, edited, approved, or paid for.
Here’s my take. First and foremost, Salesforce-Informatica strikes me as an excellent combination of complementary technologies: Salesforce’s AI agents and Informatica’s data-management solutions.
And the timing is perfect. Many organizations want to move ahead with GenAI and agentic AI but they’re being forced to proceed with caution because their business data isn’t ready for it.
In the press release announcing the planned acquisition, Salesforce CEO Marc Benioff said it would unite “the world’s #1 AI CRM with the #1 AI-powered MDM and ETL platform.”
That’s a bunch of #1s and three-letter acronyms, so I would break it down as follows.
5 strategic syngergies
Data for AI Agents - More than any other single factor, “data for AI” is the impetus for Salesforce to acquire Informatica, in my view. Not only will agentic AI not work as advertised without good, clean, accurate data; it’s a problem waiting to happen. The risks include bias, hallucinations, rogue agents, lost customers, brand impact. The hard reality is that, despite years of investment and effort, many IT teams still don’t have their business data in tip-top shape. As I noted in an earlier post, 94% of companies say their data isn’t entirely accurate, according to KPMG. That’s all you need to know to understand the rational behind Salesforce plus Informatica.
AI Agents for Data - The big challenge in prepping data for AI is that it’s complex and talent intensive. You might need a team of data engineers, architects, and admins to integrate, ingest, catalog, cleanse, and de-duplicate data, to manage access control and privacy, and to secure it. Autonomous agents could be the perfect solution to the heavy lifting of data readiness. Informatica has announced plans for its first three data-management agents — for data quality, data discovery, and data ingestion — and demoed what it calls AI Agent Engineering at Informatica World. In that demo, the agents collected data from Oracle and SAP apps, automatically cataloged the data, performed a quality check on the staged data, then created and applied data-quality rules to increase the quality score on the data set. Such capabilities, when they become GA, promise to help solve the challenge of “data for AI agents” mentioned above.
Data Clouds & Integration - Salesforce touts its Data Cloud as a competitive advantage because it’s where and how all the data comes together, including from its flagship Customer 360 apps (Sales, Service, Marketing, Commerce) and connectivity to third-party data sources through MuleSoft and APIs. A key capability is what Salesforce calls Zero Copy, which enables access to many data sources without copying, moving, or reformatting, providing near-real-time data to its Atlas reasoning engine and agents. Informatica’s Intelligent Data Management Cloud (IDMC) has some overlapping capabilities, but also complementary ones like Master Data Management, which provides a single source of the truth for data records. Informatica also helps solve the challenge of infrastructure complexity with architectural guidelines called Blueprints that it has developed for AWS, Databricks, Google Cloud, Microsoft, Oracle, and Snowflake. Of note, Informatica recently announced integration with Salesforce’s Agentforce, as well.
Metadata - By definition, metadata — which is “data about data” — is out the scope of concern of many businesspeople. But don’t underestimate its value. Informatica just introduced a metadata “system of intelligence,” which is at the core of IDMC. (See the graphic below, which looks remarkably similar to Saleforce’s Agentforce architecture, BTW.) I mention this under the theme of strategic synergies because metadata is essential to AI agent orchestration. As organizations move beyond pilot projects to multi-agent, multi-vendor, multi-cloud initiatives, the importance of metadata grows. Salesforce is like-minded. See this Salesforce post, “Why Metadata is Key to Building a Massive AI Agent Ecosystem.”
Data Governance - Another area where Salesforce and Informatica are already strong, but should be better together is the all-important practice of data governance. This refers to policies and processes for data access, privacy, security, risk, compliance, data distribution/sovereignty, and auditing. Here too, Salesforce recently published a POV on “Data Governance for Agentic AI.” A crown jewel in Salesforce’s Agentforce platform is what they call the Trust Layer, which bakes policy and principles into what AI agents are allowed to do and not do. Capabilities include bias and toxicity detectors; security, privacy, and safety controls; audit trails; and the ability to nudge human intervention if needed. The Trust Layer serves as a gateway to LLMs to filter out unwanted behavior or inaccurate outputs, helping to reduce hallucinations. In the press release announcing the deal to acquire Informatica, Salesforce pointed to the importance of rigorous governance: “Built-in MDM, data quality controls, and policy management ensure that all data driving AI is standardized, accurate, consistent, and secure.”
Further reading
I will have more reporting and analysis to share on Salesforce and Informatica, so stay tuned. Meanwhile, below are a few of my earlier posts for added context and background.
Report from Informatica World, May 20, 2025.
Report from Salesforce’s TDX conference, March 12, 2025.