The Collaboration Bottleneck

Generative AI has quickly taken center stage in legal tech conversations—but for many in-house legal teams, it still feels like a distant promise. While law firms tout their use of GenAI to streamline tasks and impress clients, legal departments embedded inside corporations are left wrestling with tools that don’t integrate, workflows that don’t align, and collaboration that breaks down at the point of execution.

Definely recently surveyed over 200 legal professionals across the US and UK, spanning both private practice and in-house roles. What emerged is a story not of transformation—but of friction. The majority of in-house lawyers in our study reported either discomfort using GenAI tools or no usage at all. Nearly half said they didn’t know how (or whether) their external firms were using AI, and most were skeptical it was adding any real value.

This gap isn’t about technical ability or resistance to innovation. It’s about the reality that GenAI tools, for all their potential, still haven’t been designed with in-house teams in mind. And until they are, the promise of productivity gains will remain largely unrealized.

The Nature of In-House Work Is Different

To understand the disconnect, we have to start with how in-house teams operate. Unlike their private practice counterparts—who tend to specialize deeply in one area and serve multiple clients—corporate legal teams span the full legal lifecycle for a single organization. They handle contract reviews, compliance issues, employment questions, vendor agreements, internal investigations, board governance, and more. They sit at the intersection of business and risk—and they collaborate constantly across HR, finance, procurement, IT, and leadership.

That level of cross-functional work demands more than task automation. It requires tools that can keep up with the complexity of multiple stakeholders, shifting priorities, and enterprise-level systems.

Yet most GenAI tools being marketed today are optimized for legal research, summarization, or drafting support in siloed environments. They aren’t built to facilitate collaboration across functions or plug seamlessly into an enterprise tech stack. As a result, legal departments are left either underutilizing them or rejecting them outright.

When Integration Fails, So Does Adoption

Our research found that over one-third of in-house teams struggle with integration when adopting legal technology, especially when tools aren’t designed to work inside platforms like Microsoft 365 or existing contract lifecycle management systems.

In practice, this means that even a powerful GenAI tool becomes another tab, another login, another disconnected workflow. Legal teams, already short on time and resources, are unwilling to jump between systems to gain marginal efficiency.

Worse, this fragmentation slows down the very thing GenAI is meant to accelerate: decision-making. When documents must be downloaded, copied, and pasted into new tools—or when outputs aren’t easily shared back with the business — it creates bottlenecks, not breakthroughs.

The Myth of “Legal Productivity”

Legal departments are under constant pressure to do more with less. They’re expected to act as strategic advisors while managing rising volumes of work—often without the ability to hire more staff. GenAI, in theory, should be a lifeline.

But “productivity” in legal work doesn’t just mean faster drafting. It means making collaboration smoother. It means reducing risk through clarity. It means giving legal professionals the ability to focus on what truly matters, rather than hunting for a clause buried in a 50-page document.

And here’s the rub: for GenAI to unlock that kind of value, it has to understand the workflows of in-house teams—not just emulate those of law firms. It has to surface the correct information, at the right moment, in the tools that legal teams already use. It has to earn trust.

Trust Is Still Missing

Among survey respondents, 75% expressed doubts about the accuracy of AI-generated outputs. That’s not just a philosophical concern—it’s a workflow blocker. In legal, where a single misinterpreted clause or missing definition can have enormous consequences, “close enough” isn’t close enough.

Even when GenAI tools are integrated into workflow platforms, legal professionals hesitate to rely on them without complete transparency. How was the result generated? Was it trained on secure data? Can it adapt to a company’s unique playbook?

If those questions can’t be answered with confidence, the technology sits on the shelf—unused and untrusted.

Security, Confidentiality, and the Real Risks

Security concerns were the number one reason in-house teams hesitated to adopt AI, with nearly 60% citing data privacy and confidentiality as critical blockers.

For in-house counsel, the stakes are personal. They’re responsible not just for protecting privileged legal information but for safeguarding the broader company from risk—regulatory, contractual, and reputational. Uploading contracts into opaque AI tools with unknown data retention policies is a line many won’t cross.

This is where LegalTech providers must step up. Secure, enterprise-ready tools that integrate directly into existing systems—and that provide complete transparency around data use—are essential if GenAI is going to move beyond the pilot phase.

Why Collaboration Is the Blind Spot

Perhaps the most striking insight from our research is this: the most significant unmet need in GenAI for in-house teams isn’t automation — it’s collaboration.

Legal professionals don’t work in isolation. They redline in shared folders, they answer urgent questions from procurement, and they track obligations across teams. Yet most GenAI tools aren’t designed to facilitate that kind of dynamic, cross-functional collaboration.

Instead, they focus on “productivity” in narrow ways—faster clause generation, better summaries, improved search. Those are helpful features, but they don’t solve the core friction that slows legal work in corporate environments: misalignment, poor visibility, and disjointed communication.

If GenAI wants to be relevant to in-house teams, it needs to help legal act as a bridge—not just a reviewer. It needs to support how they collaborate across the business, not just how they edit documents.

Moving Forward: AI Built for Legal, Not Just Law Firms

There is a path forward—and it doesn’t require in-house teams to lower their standards. It requires vendors to raise theirs.

That means reimagining how GenAI tools are built: with secure APIs, embedded inside existing workflows, and designed to reflect the actual behavior of legal teams—not just the hopes of software developers. It means planning for real use cases like clause lookup, multi-document review, and collaborative editing with non-lawyers.

It also means investing in change management and training, because even the most elegant tool will fail if legal professionals don’t understand how it works or why it matters.

The collaboration bottleneck isn’t an abstract concept. It’s the reason why, today, GenAI isn’t delivering on its promise for many in-house teams. But it’s also the clearest opportunity. Fix collaboration, and everything else starts to unlock: adoption, efficiency, trust, transformation.

At Definely, that’s where we’re focused—on delivering legal AI that fits into real workflows, supports real collaboration, and solves real problems. Because for in-house teams, that’s the only kind of productivity that matters.