The Team
Kareem Hersi
10+ years of management consulting at Accenture, EY, and Deloitte. Mostly leading change management, training, and organizational transformation for companies going through big technology shifts. The kind of work where you learn pretty quickly that the tech is rarely the hard part.
The company name came during a long run, the way these things sometimes do. The marathon connection runs deeper than branding though. Before launching Marathon AI, Kareem let ChatGPT build his marathon training schedule without pressure-testing it. He ended up running his third marathon with both knees wrapped in blue medical tape. The lesson stuck. AI can be incredibly useful, but trusting it blindly comes at a cost.
That’s the same philosophy he brings to every engagement. AI fluency isn’t a competitive advantage anymore. It’s table stakes. But readiness can’t be a one-time investment. It has to be sustained.
“The organizations getting this right aren’t gatekeeping AI behind walls of caution. They’re removing friction so their people can actually use these tools in meaningful ways.”
Sam Plaquin
Sam has worked in data across a pretty wide mix of settings, from academia and tech to an ML startup and the Government of Alberta. In government, he led data teams and saw up close what it actually takes to move data-informed change through a big system. That meant dealing with procurement, governance, competing priorities, and the very real challenge of getting people to trust and use something new.
He studied economics at the University of Calgary, and he also spent years coaching AAA hockey. That shaped a lot of how he works. The goal was never to throw numbers at people. It was to understand what they were saying, pull out what mattered, and turn it into something coaches and players could actually use.
At Marathon AI, Sam leads the technical side of the work, including machine learning models, Python and SQL development, data pipelines, and dashboards. He likes building things, but he also knows building is only part of it. A lot of good tools go nowhere because they don’t fit how people actually work. He thinks a lot about that piece too, because adoption is usually where the real work starts.
“AI is powerful, but the real opportunity is not in throwing it at everything. It is in helping people understand it well enough to trust it, enjoy using it, and spend less of their life on work that drains them and more on work that feels creative, meaningful, and human.”