Laying the Groundwork for Scalable, Trusted AI

Salesforce’s purchase of Informatica brings a mature suite of capabilities in metadata management, master data management (MDM), data integration, and data quality control—critical functions for any organization aiming to use AI not just efficiently, but responsibly. These tools help enterprises trace data lineage, assess its reliability, and enforce governance at scale—all essential for ensuring AI outputs are trustworthy and explainable. It’s a direct response to one of the biggest challenges facing AI adoption: inconsistent, siloed, and overwhelming volumes of data that weaken performance. Even the most advanced tools, especially Agentforce, will struggle when data is duplicated, fragmented, or poorly structured.

As we begin to see tools like Einstein and Agentforce becoming more deeply embedded in Salesforce workflows, the demand for high-integrity data has become paramount. The acquisition of Informatica equips Salesforce with the infrastructure to ensure AI is acting with precision, compliance, and confidence. This then positions Salesforce to shift from supporting AI pilots to enabling intelligent automation at scale, grounded in data its users can actually trust.

How Informatica Will Fit Into Salesforce’s Products

Salesforce plans to integrate Informatica across multiple platforms in its ecosystem. We can anticipate that it will impact the following:

Data Cloud: Expect cleaner, more reliable customer data with built-in data lineage and master data management (MDM). This makes it easier to create accurate customer profiles and reduces manual reconciliation across systems.

Agentforce: Salesforce’s AI agents will now be able to access not just the data itself, but critical context around how it’s been used and verified, further improving decision accuracy and reducing risk.

MuleSoft: With Informatica’s data validation and quality tools, integrations built through MuleSoft can ensure that what’s being transferred across systems is accurate and compliant.

Tableau: Dashboards built in Tableau will benefit from clearer, more consistent data structures, leading to reports that are easier to trust and act on.

Customer 360: Frontline teams using Salesforce CRM will work with more reliable, real-time data, helping to deliver relevant, timely service across every customer interaction.

Together, these enhancements reinforce Salesforce’s vision of an integrated, intelligent platform—where every product speaks the same data language, and every decision is backed by accuracy, context, and trust.

Navigating Tool Overlap and Customer Choice

Now, for those of you familiar with the Salesforce ecosystem, you might be scratching your head. Doesn’t Salesforce already own MuleSoft—another leading integration platform? That’s exactly what makes this acquisition so interesting. 

Informatica and MuleSoft both handle data integration, but in different ways. While MuleSoft is deeply rooted in API-led connectivity and application integration, Informatica brings a more robust suite of data management capabilities, especially around metadata, data quality, and master data management.

Still, the overlap raises fair questions. Customers may wonder where one platform ends and the other begins, or whether the long-term roadmap will require consolidating tools, retraining teams, or adjusting architectures. For organizations already navigating complex digital landscapes, clarity around use cases and integration strategy will be essential to avoid added friction.

There’s also the question of neutrality. Informatica’s cross-platform flexibility–its ability to work seamlessly across AWS, Azure, Google Cloud, and beyond—has long been a differentiator. That independence has earned it trust in highly regulated industries like healthcare, public sector, and financial services, where vendor lock-in can be a deal breaker. Salesforce has stated its commitment to preserving that interoperability, but how it balances ecosystem integration with platform openness will be closely watched by both customers and partners.

What This Means for Financial Services, Healthcare, and Public Sector Clients

For highly regulated sectors like banking, healthcare, and government, the stakes for AI-readiness are especially high, and so is the need for data that’s clean, compliant, and context-rich. This acquisition signals a stronger push toward integrated data governance, which could make it easier to meet stringent regulatory demands and unlock more precise AI-powered workflows. Let’s take a closer look at how Informatica will be beneficial across data sensitive industries:

Financial Services: More reliable data lineage and deduplication can help streamline processes like Know Your Customer (KYC) verification, fraud detection, and real-time risk scoring.

Healthcare: Strengthened metadata management and privacy controls offer a better path to HIPAA compliance, especially when patient data is shared across providers, insurers, and systems.

Public Sector: Improved auditability and structured pipelines support faster case resolution, cleaner citizen records, and more transparent service delivery.

Regardless of industry, the real value will lie in not in simply collecting data, but in preparing it for responsible automation. That preparation, turning raw information into something actionable, is what will determine whether these tools improve outcomes or just create more complexity.

What This Means for You

If your organization is thinking seriously about AI, this acquisition should serve as a reminder: clean, structured data is no longer optional, it’s the prerequisite. Especially in data-intensive industries like financial services, healthcare, and the public sector, the accuracy and integrity of your data will determine whether AI accelerates outcomes or compounds existing problems.

That’s why it’s important to separate capability from completeness. Informatica brings powerful tools for data integration, lineage, and quality control but at the end of the day, it doesn’t know your business logic. It won’t decide which data points are most relevant to your operations, or how they should be prioritized, transformed, or interpreted. It doesn’t establish accountability for data ownership or define what success looks like when data is truly governed. And it can’t correct the upstream processes and cultural habits that often introduce bad data in the first place.

This acquisition strengthens the Salesforce ecosystem, but it doesn’t replace the need for strategic data engineering, well-defined governance frameworks, and a business-aligned data strategy. 

That’s where the real work begins. Turning raw, siloed, or inconsistent data into something usable, something AI can act on reliably, requires more than tooling. It takes the right architecture, pipelines, and governance layers tailored to how your organization actually functions.

This is where partners like PeerIslands and Access Global Group come in. By combining deep Salesforce expertise with advanced data engineering capabilities, we help organizations bridge the gap between data management and data readiness. From mapping data strategies that reflect business priorities to building real-time pipelines that keep information structured and accessible, our teams work to ensure that tools like Informatica and Salesforce offer more than just connectivity–it offers real results.