For most enterprise organizations, artificial intelligence has become a familiar topic in the boardroom. Leaders have read the reports, attended the conferences, and nodded along to the forecasts. Many have even launched pilot programs. But according to Techquity, a technology advisory firm working with enterprise and growth-stage companies across industries, familiarity is not the same as readiness — and the gap between the two may be more dangerous than most executives realize.
“We are in a genuinely different moment,” says Techquity Partner Chuck Moore. “Not different in the way that every new technology wave is called transformative. Different in the sense that the speed and depth of this shift requires a fundamentally different response than the typical approach to technology adoption most organizations are wired for.”
Techquity is making a pointed, public case: organizations that treat AI as one initiative among many — something to study, pilot, and gradually absorb — are misreading the moment. The firm is calling on enterprise leaders to move with far more urgency and conviction, while acknowledging that the path there looks different for every organization.
A Different Kind of Wave
Techquity is careful not to be alarmist. But they are direct.
The firm draws a clear distinction between this AI moment and prior technology shifts — the migration to cloud computing, the rise of the internet, the proliferation of desktop software. Each of those transformations reshaped how organizations operated. This one, they argue, is reshaping the nature of the work itself.
“Every major technology wave has moved constraints,” says Techquity Partner Andrew Tahvildary. “The critical question is always where those constraints move, and whether leadership has noticed.”
What makes AI different, in Techquity’s view, is the breadth and pace of that shift. Prior transformations offered a recognizable learning curve. Engineers who migrated workloads to the cloud were still doing something that felt, as Partner Brian Lakamp puts it, “reachably familiar.” Agentic AI — software that can reason, plan, and execute across complex tasks — does not feel familiar to most technology teams. It requires a genuine rethinking of how work gets done, not just an upgrade to existing tools.
“This is the first time that people who have coded one way for 30 years face a true change management moment,” Lakamp says. “That’s something most technology teams have never experienced before.”
What Techquity Is Seeing on the Ground
Across client engagements, the firm describes a consistent pattern: organizations that intellectually understand AI’s importance but are organizationally stuck. Enthusiasm at the leadership level. Hesitation on the ground. Blockers around security, tooling decisions, unclear ownership, and the simple inertia of existing backlogs and processes.
The result is a kind of productive-looking paralysis — teams that are talking about AI, debating AI, perhaps even buying AI tools, but not materially changing how they work.
“We see teams that whipsaw between saying ‘this is going to be amazing’ and then not actually doing anything,” says Partner Peter Zatloukal. “There’s a lot of uncertainty about how to get started, and a tendency to wait for the infrastructure decisions and the policy questions to be resolved before anyone actually picks it up and uses it.”
Techquity’s position is that waiting for perfect conditions is itself a strategic mistake. The firms that will be best positioned in two or three years are the ones building hands-on capability now — not the ones that have the most refined AI governance documentation.
The Recommended Approach: Earn the Conviction First
Rather than mapping clients onto a multi-year adoption roadmap, Techquity advocates for getting organizations to real, hands-on experience quickly. The firm has developed an approach — part workshop, part hackathon — designed to give technology teams direct, low-stakes exposure to agentic tools in an environment deliberately isolated from their production infrastructure, security debates, and existing project pressures.
The goal is not to produce a deliverable. It’s to produce conviction.
“Don’t worry about your tooling decisions,” Zatloukal explains. “Don’t worry about your specific backlog. Take some isolated problems, work through them, and actually see what’s possible. That shared experience is what unlocks the broader conversation about how you start doing this at scale.”
Techquity sees this kind of rapid capability-building as the necessary precursor to the harder organizational work — the process changes, the hiring decisions, the governance frameworks. Without it, those conversations tend to stall in abstraction.
The firm is also deliberate about the level at which this work happens. The goal is not to position itself as a permanent engineering resource for its clients. It is to accelerate the moment at which a client’s own team can carry this forward.
The Harder Question: Where Does AI Actually Create Value?
Techquity is equally clear about the limits of a one-size-fits-all approach. Not every organization should be building software. Not every AI initiative belongs in engineering.
“A lot of companies could genuinely use guidance on where in their business it makes sense to apply AI at all,” says Partner David Howell. “There are organizations spending real energy applying AI to problems that don’t warrant it, while sitting on proprietary data and operational knowledge that could be genuinely valuable — if they asked the right question first.”
Howell’s point reflects a broader caution within the firm: maximalism about AI as a force does not mean maximalism about every AI application. The right starting point, Techquity argues, is often a clear-eyed assessment of where an organization has unique data, unique processes, or unique expertise that AI could meaningfully compound — rather than a reflexive push to automate whatever is most visible.
This nuance matters especially for the kinds of companies Techquity works with: infrastructure firms, energy companies, industrial enterprises, professional services organizations. These are not software companies by identity or by culture. Their path to AI leverage looks different from a product-led technology firm, and the firm acknowledges it is still developing its thinking on how to best serve clients in domains where its own hands-on depth is newer.
“We have real depth in product building and technology development,” Moore says. “We know what the maximalist approach looks like there, and we know the risks. We have to be honest about where we’re still building that same depth in other fields.”
The Risk of Waiting
Techquity’s broader message to enterprise leaders is not that their companies face immediate existential threat. Most of their clients will not experience the disruption of their core business as a sudden crisis. It will feel, for a while, like a gradual drift — a slow erosion of competitive position, a growing gap between what their organizations can do and what newer, more capable competitors can do.
That, the firm argues, is precisely what makes it dangerous.
“Companies won’t feel the urgency from the inside,” says Techquity Founder Anthony Bay. “There’s no alarm that goes off. You just keep doing what you’ve been doing, and the distance grows.”
The Microsoft parallel surfaces often in the firm’s thinking: a dominant company that nearly missed the internet entirely, not out of ignorance, but out of organizational momentum. The lesson, in Techquity’s reading, is not that every company will fail to adapt. It is that the ones that do adapt tend to do so because someone in a position of influence decided to treat the shift as a strategic priority — not a background initiative.
Zatloukal puts it plainly: “The companies that don’t make bold bets on this are at competitive risk. That’s not a provocative claim. That’s just the direction this is going.”
A Friendly Push, Not a Mandate
For all the urgency in their internal thinking, Techquity is deliberate about how it shows up with clients. The firm is not interested in selling fear. It is not pitching wholesale transformation as a prerequisite for engagement. And it has no interest in positioning itself as a permanent replacement for a client’s own capability.
The posture, Bay says, is more like a trusted advisor who happens to have strong views — and is willing to say them out loud.
“We’re going to tell you where we think you are,” Bay says. “We’re going to tell you what we think the gap is. And then we’re going to help you close it in a way that’s real and durable — not a report that sits on a shelf.”
That combination — honest assessment, practical urgency, and genuine respect for where a client is starting from — is how Techquity believes the best version of this work gets done.
The window, they believe, is still open. But it is not indefinitely so.
Techquity is a technology advisory firm partnering with enterprise and growth-stage organizations on digital transformation, AI strategy, technology leadership, and operating model design.