Imagine this. The case is open. The customer is on the phone. Your rep has everything they need — almost.

The CRM record is right there. Account history, contact details, open opportunities. Everything Salesforce was built to show. What it doesn't show is the contract the customer is asking about. Or the service correspondence from three months ago. Or the compliance policy your rep needs to quote before they can make a commitment.

So, the rep puts the customer on a brief hold. Opens a browser tab to the shared drive, searches, and finds a folder with six versions of the contract and no clear indication which is current. Opens a second tab to SAP, finds the order record but not the attachment. Checks email. Finds the right document. Pastes the number into the case. Takes the customer off hold.

Four minutes. One customer. Multiply that across your service team, across every case, across every day.

Your rep did everything right. They're trained, motivated, and they know the product. The problem is that the information they needed existed in four different places, and none of them were inside Salesforce where the work was actually happening.

The CRM knew the customer. It didn't know the customer's world.

This scene plays out thousands of times a day inside every Salesforce org we talk to. And it's not a people problem. It's a content problem.

Fragmented content doesn't just slow teams down. It loses deals.

The productivity loss in that scene is visible. For most enterprises, Salesforce content management is where the revenue gap actually begins — and it's harder to see on a dashboard than a missed quota.

Businesses are opportunities due to a lack of timely access to data. Gartner market guide for enterprise AI search reports that 34% of employees have difficulty finding information. The deals aren't being lost because of bad sales. They're being lost because the information wasn't there when it mattered.

The underlying cause is consistent. S&P Global Market Intelligence research from March 2026 found that 63% of employees cite tool fragmentation as their biggest technology obstacle. Every jump between applications is a tax on every customer interaction, and adding new tools doesn't solve the problem; it compounds it.

What makes this more than an operational inconvenience is what's coming next. The Gartner AI Governance Playbook reports that only 23% of [IT leaders] are very confident in their organization's ability to manage security and governance components when rolling out GenAI tools in their enterprise applications. The infrastructure that AI needs to function reliably inside the enterprise isn't ready, and most IT leaders already know it. They're deploying anyway, because the pressure to show AI progress is real. The risk is that the gaps don't disappear when you launch. They move downstream.

None of this is new. What's new is that AI is about to make it much worse.

Trusted AI needs trusted content

Here is the assumption most AI pilots are built on: if you give a capable model access to your data, it will give you capable answers.

It's a reasonable assumption. It's also wrong.

AI agents don't just need access to content. They need content that is classified, governed, current, and contextualized. A raw file sitting in a shared drive is not any of those things. It is a document without a history, without permissions, without a defined place in your organization's information lifecycle. When an AI agent reasons over it, the agent has no way to know whether that file is the authoritative version, an expired draft, a document that should only be visible to certain roles, or a record that is legally required to be retained in a specific jurisdiction.

The agent doesn't hesitate. It answers confidently.

In a regulated process, a contract negotiation, a claims decision, a client compliance review, a confident wrong answer is not a productivity problem. It's a liability.

This is why only 45% of companies using AI for document-heavy processes have successfully measured ROI, according to Deep Analysis in 2026. The other half are not failing because the models are bad. They're stuck because the content underneath the models is not ready to be reasoned over.

Most organizations have spent years accumulating massive content estates across dozens of systems. Documents in SAP. Correspondence in email. Policies in shared drives. Contracts in a folder structure that made sense in 2018. That content was never designed to be an AI input. It was designed to be stored and retrieved by humans who could apply judgment to what they found.

Trusted AI needs trusted content. Not eventually. From the first prompt.

The organizations that solve this first won't just be faster at Agentforce. They'll be the only ones who can trust it.

Content that comes to the rep, connected across systems, governed for AI

OpenText Content Cloud integrations for Salesforce were built for exactly this problem.

The rep in that opening scene didn't have a motivation problem. They had a Salesforce content management problem. OpenText solves it by surfacing the right documents directly inside Salesforce, in context, at the moment they're needed. The contract, the correspondence, the compliance policy — all of it appears within the record the rep is already working on. No switching. No searching. No hold music. The work happens inside Salesforce because the content is already there.

That's a different way of working. It's also a different way of thinking about what a CRM is capable of when it has the full picture.

The full picture requires connecting the systems that actually run your business. Most enterprises run Salesforce alongside SAP, Microsoft, Guidewire, and a web of other platforms, each holding documents that are relevant to the customer record but invisible to it. OpenText Content Cloud integrations for Salesforce connects those systems to a single governed content platform, giving sales and service teams a true 360-degree customer view. Not just complete CRM data — complete customer intelligence.

The third piece is what makes AI trustworthy at scale. Raw files aren't enough. Content needs to be classified, governed, and contextualized before an agent reasons over it. OpenText adds a semantic layer over enterprise content, transforming static documents into structured inputs that agents can use accurately, so that every AI-driven action is built on a governed, auditable foundation. Classification, audit trails, retention controls, and permissions travel with the content across every connected system, from document generation to archive.

This is what powers OpenText Content Aviator, the AI content assistant that works inside Salesforce to surface, summarize, and act on governed content in the flow of work.

That's why Salesforce selected OpenText as one of the first partners to build an AI-to-AI integration with Agentforce. Trusted AI needs trusted content.

Proof: how ENGIE Italia turned content into competitive advantage

ENGIE Italia is one of Europe's largest energy providers. They compete for complex B2B contracts against well-resourced rivals in a market where speed determines outcomes as often as price does. A few years ago, they were losing bids. Not on price. Not on capability. On speed.

Their pre-contract process ran on email, phone calls, and spreadsheets. Documents lived in shared drives. When a client requested a proposal or a contract review, the response required a scramble: locate the right version of the right document, obtain the right approvals, and get it out the door before the competition did. Every client request triggered the same improvised chase. The result was delays, inconsistency, and deals that slipped away in the gap between a client's request and ENGIE's response.

They deployed OpenText Content Management for Salesforce, alongside OpenText Capture and OpenText Documentum Content Management, to bring the content lifecycle inside the business processes that drove revenue.

Application switching was eliminated. 200,000 critical documents were secured and governed. Digital workflows replaced the manual handoffs that had slowed every client interaction. Francesco Presicce, Manager of IT Business Support at ENGIE Italia, describes the change plainly: the business can now respond to client contract proposals quickly, sharpening its competitive edge.

That's not a technology story. That's a revenue story.

Flexible deployment, built-in data sovereignty, and no new vendor complexity

Deployment flexibility is the starting point. OpenText supports on-premises, private cloud, hyperscaler environments (AWS, Azure, Google Cloud), and multi-tenant SaaS. The deployment model is determined by your compliance requirements, not by what's operationally convenient for the vendor. If your organization has data residency mandates or infrastructure constraints specific to your industry, the architecture can reflect that from day one.

Data sovereignty is built in, not bolted on. Multi-region data centers support GDPR, HIPAA, FedRAMP, and the regulatory frameworks governing financial services, insurance, government, and healthcare. This isn't a compliance checklist. It's the architecture.

Governance travels with the content. Classification, permissions, audit trails, and retention controls follow every document across every connected system. When a record moves between Salesforce, SAP, or Microsoft, its governance layer moves with it. That consistency is what regulated industries require and what most point solutions cannot sustain at enterprise scale.

And this integration doesn't add vendor complexity. It reduces it. According to analyst reports spotlighting the state of agentic AI adoption in enterprises, 46% of business leaders prefer extending incumbent platforms over adding niche AI vendors. OpenText and Salesforce are built to work together natively, and for organizations already running Salesforce, the integration extends the platform you've already invested in rather than adding a net-new vendor to your stack. For organizations newer to OpenText, it brings enterprise-grade content management directly into the CRM environment your teams already work in every day.

This is what enterprise-ready looks like.

The foundation you build today determines the AI results you show tomorrow

Salesforce has reported more than 29,000 Agentforce deals and counting. Organizations across financial services, insurance, healthcare, and utilities are moving from evaluation to deployment, and the gap between early movers and late adopters is beginning to show in results.

The organizations moving fastest share something in common. They built the content foundation before they scaled the AI. They didn't attempt to retrofit governance after agents were already running. They made the investment once, in the right order, and they are now generating measurable outcomes while others are still working through the architecture.

The question isn't whether your enterprise needs governed, contextualized content to get real value from AI. That question is settled.

The question is whether you build the foundation before you scale, or scramble to fix it after — at a higher cost and a longer timeline.
Trusted AI needs trusted content. The organizations that act on that today are the ones that will have something concrete to show when leadership asks what the AI investment actually produced.

Explore Salesforce content management solutions by OpenText on AgentExchange.

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