Beyond Adoption: Why GenAI in the Enterprise Needs Strategy, Not Just Software

When we talk about GenAI today, the conversation often revolves around features and capabilities. But as Aparna astutely noted in a recent LinkedIn post, transformation isn’t just about what the technology can do—it’s about what the organization is willing to believe, adopt, and scale. And that’s a much more human, messy, and strategic terrain.

Two recent essays helped crystallize something I’ve been observing across boardrooms and transformation programs.

The first is the classic Innovator’s Dilemma—revisited for the GenAI era. As explained in a sharp Substack post, it’s not that enterprises lack ambition. It’s that they optimize around their current customer and revenue models. Disruption doesn’t come from lack of awareness. It comes from being too good at what you already do. So when GenAI presents itself—not as a 10% enhancement, but a 10x rethink—legacy mental models start to panic.

The second is more subtle—and in some ways, more dangerous. The George Costanza Effect: the idea that software in enterprise settings is trapped by its historical perception. A CRM is a tool to record interactions, not to initiate them. An HR system manages benefits—it doesn’t coach your people. So when GenAI features try to elevate software into new roles, users freeze. Not because it doesn’t work—but because it feels “wrong.” Like Costanza in Seinfeld—when someone behaves differently from how we expect, our minds reject it, no matter how effective it might be.

Now combine these two forces: on one side, an organization held hostage by its own strengths. On the other, users conditioned by a decade of muscle memory about what enterprise software “should” be.

This is why GenAI isn’t just a product challenge. It’s a strategic choreography challenge. And that’s where consulting firms—particularly those embedded deeply inside enterprise operating models—can play an outsized role.

So what’s the playbook?

1. Anticipate the Dilemma, Don’t Wait for It

Most large organizations launch GenAI pilots with cautious optimism. But often, those pilots are constrained by the same legacy thinking they hope to overcome. The key is to separate exploration from exploitation. That means creating GenAI tiger teams that don’t report into the same KPIs and customer feedback loops as the core business. These teams need the freedom to imagine adjacent use cases—ones that feel small today, but could become tomorrow’s core.

2. Mind the Identity Trap

If you’re going to launch a GenAI assistant inside a CRM, you’re not just launching a feature. You’re asking users to see the software differently. That’s a branding challenge as much as a technical one. Introduce it as a new role. Give it a name. Build narrative scaffolding around it. Help users rewire what this tool is for. Without this step, you risk rejection not on merit—but on memory.

3. Fuse Strategy with Behavior Design

This is where Aparna’s insight really matters. The success of GenAI adoption isn’t in the codebase—it’s in the change narrative. Consultants must co-create with business teams. Use pre-mortem sessions to surface fears before rollout. Build success frameworks that measure time saved, new insight surfaced, or the emotional shift in how teams perceive their tools. These are soft metrics—but they often precede the hard ones.

4. Redefine What 'Adoption' Means

We’re used to measuring rollouts by the number of users onboarded, or workflows integrated. But GenAI tools are not infrastructure—they’re collaborators. True adoption means people trust the system. They’re delegating thinking, not just tasks. That trust must be earned and carefully nudged. Otherwise, you’ll get surface-level engagement and deep-level skepticism.

When you combine the Innovator’s Dilemma with the Costanza Effect, you begin to understand the real barrier to GenAI in the enterprise: not feasibility, but believability.

So here’s my proposition to enterprise leaders, CIOs, and transformation advisors:

- Don’t just build GenAI features. Redesign the roles your software plays.

-  Don’t just chase productivity metrics. Track the story your teams are telling themselves about the tools they use.

-  And don’t assume resistance means failure. Sometimes, it means you’re finally changing the script.

We’re not just at the edge of a technology shift. We’re at the edge of an identity shift—for systems, for teams, and for what “work” even means.

Curious how your platform might be stuck in a Costanza loop? Or how to pilot a GenAI solution that doesn’t get rejected by legacy perception?

Let’s open that conversation.

Labels: Enterprise Software, GenAI