Why Your AI Investment Is a Culture Decision First

You can pick the right tool. Secure the budget. Build the business case. Get executive buy-in. And still watch your AI investment underdeliver—because no one thought carefully enough about the culture it was landing in.

This is the pattern that Amy Gradnik and Tia Christopher have both watched play out across organizations of every size and sector. The technology is rarely the problem. The problem is misaligned expectations, unasked questions, leadership that isn’t in sync, and workforces that weren’t brought along before the switch was flipped. The result is shadow AI, quiet resistance, expensive walk-backs, and a lingering organizational skepticism that makes the next initiative harder to launch.

Their fireside chat at Innovation Summit 2026 was a direct, candid conversation about how to get this right—starting not with the technology, but with the people, the questions, and the culture clarity that determine whether any AI deployment actually sticks. Here are the key takeaways.

About the Session

The session was a fireside chat between Amy Gradnik, Principal of Strategic Services at HIKE2, and Tia Christopher, Founder and CEO of The Orange Peel Collaborative, an AI strategy firm. Tia brings a strategic operations background and a practice built around the idea that the way an organization peels the orange—approaches its AI decisions—matters as much as the destination it’s trying to reach. The conversation kicked off Day 2 of Innovation Summit 2026 and set the tone for a day focused on organizational readiness, culture, and the human dimensions of AI transformation.

When AI Doesn’t Work, It’s Rarely a Technology Problem

The opening framing of the session was blunt and worth sitting with: when AI deployments fail or underdeliver, it is almost never because the technology was wrong. It’s because of culture clarity issues—misaligned expectations between leadership and staff, between IT and the business, between what was promised and what was communicated.

Tia drew a pointed analogy: approaching AI adoption without first aligning your organization is like getting married without a prenup or a real conversation about expectations. You don’t technically need either to proceed. But when the surprises come—and they always do—you’ll wish you had them.

“When AI doesn’t work, it’s rarely a tool or technology problem. It’s a culture clarity or expectation issue. How are your expectations affecting the adoption process at your organization?” — Tia Christopher, Founder & CEO, The Orange Peel Collaborative

Amy reinforced this with a concrete example: an organization that went from “don’t use AI at all” to “use AI for everything” without building the bridge between those two positions. No training. No guidance on what was off-limits. No framework for which tools were appropriate for which tasks. The result was a significant change management exercise and a costly walk-back—not because the technology failed, but because the cultural infrastructure to support it had never been built.

The lesson isn’t that technology decisions should wait for perfect cultural alignment. It’s that technology decisions are culture decisions—and treating them as purely technical choices is how organizations end up with expensive, underused tools and workforce friction that outlasts the deployment.

Ask Before You Buy (And Keep Asking After)

Both speakers returned repeatedly to a single foundational practice: asking questions. Not assumptions. Not LinkedIn scrolling to benchmark where everyone else supposedly is. Actual questions, directed at the actual people in your organization whose work and lives the technology will affect.

Tia’s Orange Peel Collaborative uses a structured assessment that pairs a management survey with an anonymous line staff survey, followed by personal conversations with both groups. The gap between what management thinks is happening and what the people doing the work actually experience is almost always illuminating—and often determines whether an AI initiative will land or stall.

The questions Tia highlighted as most important before any purchase: Are key stakeholders—CIO, CEO, COO—actually on the same page? If not, that misalignment will surface in the implementation, just at a much higher cost. Why are we choosing this solution at this time? Both parts of that question matter. And does this solution fit our culture, or are we being asked to contort our organization around the tool?

That last question generated one of the session’s most useful analogies: you don’t fit yourself around your running shoe—you fit the shoe to the exercise you need to do. Organizations that select AI tools first and figure out culture fit later are running in the wrong shoes, and they’ll feel it.

“I’m not coming in here to put my values on you. I’m asking you what are the values at your organization, what’s important, and how can tech amplify that? How can tech augment that and really reinforce what you’re doing—not the other way around?” — Tia Christopher, Founder & CEO, The Orange Peel Collaborative

Amy added that this listening practice doesn’t end at purchase. Sustained AI deployment requires ongoing check-ins—with the people doing the work, with the metrics that matter, and with the strategy itself. What an organization needs from its AI tools today will not be the same as what it needs in 18 months. Building in the cadence and the organizational habit to keep asking those questions is what separates organizations that adapt from those that get locked into the wrong path.

Intention vs. Execution: The Gap Where Good AI Strategies Go Wrong

One of Tia’s client stories illustrated with precision how well-intentioned AI decisions can go badly wrong in execution. A Canadian city purchased a technology tool aimed at boosting tourism—a genuinely positive goal. But the execution involved deploying cameras throughout the downtown area, and by the time anyone noticed the public reaction, constituents felt they were living in a surveillance state. The intention was tourism. The experience was something very different.

By the time The Orange Peel Collaborative was brought in, the situation had ballooned. The fix required sitting down with community members, listening to their actual fears, and going back to the city to reconnect the initiative with its original goal. The technology itself wasn’t the problem. The gap between intention and execution was, highlighted by the absence of community input before deployment.

Amy connected this to a pattern she sees in enterprise implementations: the moment of highest culture risk isn’t usually the launch. It’s the pivot. She described a large Revenue Cloud implementation that was mid-development when a major merger brought in an entirely new product set and a separate workforce. The team faced a binary choice: go live with what they had and replatform the merged organization later, or take the pause, rebuild for both, and launch as one.

They chose the pause—and what looked like a technology decision turned out to be primarily a culture decision. Launching two separate groups onto different systems would have created an organizational “us versus them” dynamic that would have been far more expensive to undo than the rebuild. The technology was rebuilt; the culture was protected. And the merged workforce landed in a shared environment that accelerated integration in ways no communications plan could have.

The throughline across both stories: fit and alignment are not a one-time check at the beginning of an implementation. They are an ongoing practice that has to be embedded into how the organization monitors, adjusts, and evolves its AI deployment over time.

Build for Adaptability, Not Just Adoption

A thread that ran through the entire conversation was the distinction between adoption and adaptability—building the organizational habits and infrastructure that allow you to keep pace with a landscape that is changing faster than any single deployment can anticipate.

Amy cited the Goldman Sachs CEO’s public warning that in the next 12 to 24 months, a significant portion of AI capital investment will fail to deliver returns—and that when that happens, it will create real market and organizational turbulence. Her point wasn’t to discourage investment. It was to underscore why investing only in tools, without investing in the organizational capacity to evaluate, adjust, and pivot, is a fragile strategy.

Tia framed adaptability as a set of ongoing questions every organization should be asking: Are we clear about expectations and boundaries—for both our people and our technology? Do we have space to pause or pivot if something isn’t working? Are the habits we’re building now ones that will still make sense in two years? Are we capturing lessons from what works and what doesn’t, or are we treating each initiative as a one-time exercise?

The organizations that came out ahead in her experience weren’t the ones that moved fastest. They were the ones that moved with the most intentionality—establishing cross-functional working groups where titles were checked at the door, creating ongoing forums for adaptation rather than one-time steering committees, and treating their AI strategy the way they treat their business strategy: as a living document that gets reviewed, challenged, and updated.

For HIKE2 clients, this is the change management and governance work that sits alongside every technology deployment—and that often determines whether the investment delivers its intended value. The tool is the easy part. The organizational system that surrounds it is what makes it sustainable.

Watch the Full Session

The full fireside chat includes Amy and Tia’s complete exchange on real-world implementation stories, the specific questions from The Orange Peel Collaborative’s organizational assessment, a live Q&A with the audience including a rich discussion about how the City of Pittsburgh has sustained AI value alignment across two administrations, and guidance on how to create internal space for ongoing AI conversations in organizations of any size.

Ready to Build an AI Strategy That Fits Your Culture?

Technology that doesn’t fit your organization doesn’t deliver its value—no matter how good the demo looked or how strong the business case was. The organizations that get the most out of AI are the ones that invest in the cultural and organizational infrastructure that surrounds the technology, not just the technology itself.

At HIKE2, human-centered design isn’t a talking point. It’s the methodology behind every engagement we run. If you’re preparing for an AI deployment, navigating a failed one, or trying to build the organizational alignment that makes future investments more likely to succeed, we’d welcome the conversation.

Contact HIKE2 to start the conversation →