Geotab Deployed Custom AI to 3,400 Employees in One Day
You have probably sat through a technology rollout that began with a steering committee, a phased pilot and a promise that the real launch would come once the platform felt ready.
You have probably sat through a technology rollout that began with a steering committee, a phased pilot and a promise that the real launch would come once the platform felt ready. By the time access reached your desk, the tool had already aged and the team that designed it had moved on to the next project. Geotab, a fleet-data company with 3,400 employees, took the opposite path. It deployed its custom AI tool, GIA, to every employee in a single day. Within seven days the rollout recorded a 97 per cent daily active rate. Neil Cawse, founder and CEO, laid out the rollout and its lessons in a first-person account, arguing that speed beat a polished launch plan and that companies waiting on AI risk a gap that may become impossible to close.
What happened
Every employee, technical or not, received full access to a secure AI gateway with pre-loaded skills straight from their laptops. Cawse said he believed Geotab would learn more and get further ahead by putting GIA at people's fingertips immediately rather than designing a perfect rollout. The friction point, in his telling, was onboarding, the moment most technology rollouts lose people. Geotab's answer was to make the first step trivial: employees could simply type "GIA" and begin. The easier the start, the faster people moved from uncertainty to experimentation.
Cawse led a hackathon with over 2,000 participants to build skills. Geotab's monthly town halls let employees share how they use AI. The company makes usage information available to all employees immediately, including token consumption. Cawse's logic: transparency helps people understand how they use AI and encourages responsible, purposeful adoption.
The six rules
Cawse distilled the rollout into six operating rules.
First, be the first adopter. Leaders cannot ask employees to embrace a technology they have not taken the time to understand themselves. Cawse tests new tools personally so he can speak honestly about what AI does well and where it falls short.
Second, make the first step easy. The onboarding moment determines whether people experiment or abandon the tool.
Third, share real examples. Geotab's monthly town halls let employees demonstrate how they use AI in their own work.
Fourth, set clear boundaries. Employees must know what information can be used, what outputs need review and when human expertise takes over.
Fifth, measure what matters. Geotab makes usage data visible to all employees, including token consumption. It is harder, and more important, to verify that teams produce more value with unchanged resources, the test Cawse says actually matters. The real question: are teams delivering more with the same resources?
Sixth, move fast and iterate. Rapid implementation is not optional with technology moving at lightning speed, he wrote. Let the first version be imperfect; the messy start buys the learning that a delayed, polished one never delivers.
The stakes
Cawse's warning is blunt: companies that wait on AI may never catch up. "Companies that learn how to use AI will move faster, make better decisions, and produce more with the same resources," he wrote. "Those that wait will create a gap with competitors so wide that it may become impossible to close."
"The transition has been one of the hardest changes I've led at Geotab," Cawse wrote, noting that it changed how people work, how teams are organised and how leaders measure performance. His conclusion: "Avoiding that disruption is a decision to fall behind."
The biggest mistake leaders can make is waiting for AI adoption to feel neat and comfortable, Cawse wrote. His closing argument: the companies adopting AI now will outpace competitors and build the confidence, skills and adaptability a quickly transforming future demands. For Cawse, the risk calculus is settled, the only decision left is whether leaders accept it before the gap widens.
For L&D and digital transformation leaders, the lesson is operational. A perfect rollout plan that arrives late delivers less learning than a messy launch that puts the tool in people's hands immediately. The question is whether your organisation is prepared to measure what actually matters, not adoption theatre, but whether teams produce more value with the same resources, and whether your leaders have used the tools themselves before asking anyone else to.
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