When Rokt CEO Bruce Buchanan told his roughly 800 employees that up to 45 percent of their jobs could be greatly impacted as the company moved to adopt AI tools at scale, he described it as a great opportunity for employees to embrace ways in which their jobs could be streamlined, enhanced, and assisted with AI adoption. What followed was one of the more deliberate, successful, and documented examples of enterprise-wide AI adoption in the tech sector, and it offers a practical model that many organizations are still struggling to build.
Rokt, the New York-based e-commerce technology company whose platform is projected to power more than 10 billion transactions in 2026, structured its AI rollout not as a product initiative but as a people one. The distinction matters. Most companies introduce AI tools and then wait to see who picks them up. Rokt removed that optionality entirely.
Clearing the Calendar
One of the more striking decisions Rokt made was to wipe all regular internal meetings from every employee’s schedule, replacing that time with a structured opportunity to experiment with AI. Simon Curran, Rokt’s Chief Development and Culture Officer, described the reasoning plainly: the goal was to normalize the technology, to make it feel less like a test and more like part of the job. In a LinkedIn piece reflecting on the initiative, Curran described the company’s message as: “We’re all in this together.”
Curran, who joined Rokt in October 2024 after years of coaching high-performance teams, including the All Blacks Performance Labs, brought a sports psychology framework to what is fundamentally a workforce transformation challenge. His read was that anxiety around AI was less about the tools themselves and more about identity. People feared that learning to use AI well meant acknowledging their current way of working was insufficient. Rokt addressed that head-on by making the experimentation collective rather than individual.
Building the Infrastructure for Adoption
Clearing calendars was the signal. The infrastructure that followed was the substance, with the rollout of RoktGPT, a company-specific knowledge assistant that reduced the time spent hunting for internal documents, drafting communications, and generating first-pass ideas. Within a single month, called AI April, the company built more than 150 workflow automations through the automation platform n8n, many of them built by non-technical employees who had never written a line of code.
Perhaps more importantly, Rokt embedded what it called AI Champions across functions. These were not centralized IT roles. They were domain experts from sales, marketing, operations, and product who took ownership of AI experimentation within their teams, then shared what worked across the company. The model borrowed from how Airbnb and Netflix pair technical specialists with domain experts, a pairing that tends to produce faster, more relevant automation than top-down mandates from an AI center of excellence.
The company also formalized AI usage policies and security frameworks during this period, a detail that often gets deprioritized in the early rush of adoption. Rokt treated speed and responsibility as parallel tracks rather than competing ones.
Hiring Strategy as Signal
One of the clearer structural signals of Rokt’s AI posture is where it has been directing roughly 90 percent of its recent hiring: early-career talent and recent graduates. Curran described this cohort as “AI natives,” people who bring practical familiarity with AI tools alongside the energy to experiment without the habit-inertia of established workflows.
This allows employees to not only continue to build and enhance their job-related skills, but also showcase the notion that AI adoption can be assistive in an individual’s successes. Rokt’s internal promotion rate sits above 10 percent annually, well above industry averages according to Built In’s profile of the company. This continued focus on employee education, promotion, and overall professional success is embedded in the company’s culture.
What Gets Measured
Rokt began tracking a metric it calls experiment velocity: the speed at which teams could test an idea, collect a result, and iterate. This is not a standard performance indicator in most HR systems. Rokt introduced it specifically to make the culture of experimentation legible, to give employees and managers a shared language for the kind of behavior the company was trying to amplify.
McKinsey’s 2025 workplace AI report found that employees are three times more likely to be using generative AI tools than their C-suite executives estimate, pointing to a persistent measurement gap between what leaders think is happening and what employees are actually doing. Rokt’s experiment velocity metric is a response to exactly that problem. Rather than asking employees to self-report AI usage in quarterly surveys, Rokt can garner enhanced transparency and insight directly from employees, encouraging honest experience feedback and growth opportunities based on feedback.
BCG’s AI at Work 2025 analysis found that companies committed to AI adoption as a cultural transformation rather than a technology rollout see better and more meaningful outcomes. The distinction they draw is between companies that deploy tools and companies that reshape how people and machines collaborate. Rokt’s calendar reset, AI Champions program, and experiment velocity tracking sit clearly in the second category.
Culture as Precondition
It is worth examining what made Rokt’s approach viable, because most organizations that attempt company-wide AI adoption do not have the same starting conditions.
Great Place To Work reports that 91 percent of Rokt employees say it is a great place to work, compared to 57 percent at a typical U.S.-based company. In a July 2025 engagement survey, 88 percent of Rokt employees said the company provides equal opportunity regardless of age, race, gender, or other identities, a six-point increase from the year prior. The company has ranked on Fortune’s Best Workplaces in Advertising and Marketing, earned Built In Best Places to Work recognition across multiple U.S. markets in 2026, and been named among the Best U.S. Midsize Companies to Work For.
These are not just employment brand metrics. They reflect the trust infrastructure required to ask 800 people to rethink how they do their jobs. When a company announces that nearly half of what its employees do will look different because of AI, the response depends almost entirely on whether employees trust that the organization is invested in their development. At a company with low trust, that announcement reads as a warning. At Rokt, by Curran’s account, it read as an energizing challenge.
The framework Rokt uses internally, documented across its culture materials, organizes around three concepts: Connection, Clarity, and Courage. Rokt’s own blog on company culture describes the first of these as “connect before you correct,” a practice Curran brought from his work with elite sports teams. Meetings begin with a brief personal check-in before any agenda item, not as a formality but as a mechanism for building the kind of trust that makes honest feedback and fast decision-making possible.
Clarity, in Rokt’s framework, means cascading context rather than just tasks. Employees understand why a piece of work matters, not just what it is. This matters particularly in an AI context, where the “what” of someone’s job may shift while the underlying purpose stays constant. When people understand the purpose, they can redirect their own energy rather than waiting to be redirected.
Courage means challenge early, commit fully. It is the cultural permission to surface uncomfortable observations before a decision hardens, then to move decisively once a direction is set.
These three elements do not make AI adoption easy. They make it survivable at the pace Rokt operates.
The Broader Implication
The World Economic Forum projects that 77 percent of employers plan to reskill employees for AI collaboration between 2025 and 2030. Most of those programs will focus on the tools: which platforms, which prompts, which workflows. Rokt’s experience suggests that the tools are the easier part. The harder and more consequential work is building the organizational conditions under which people are willing to experiment in public, to share what did not work, and to redefine their own roles without waiting for permission.
Curran’s framing for the LinkedIn piece that described all of this was not about AI tools at all. It was about reinvention, and about who owns it. At Rokt, the answer the company gave its 800 employees was: you do. And it built a culture designed to make that possible.
