Following the launch of our AI Sherpa Programme – designed to help our portfolio companies navigate the opportunities and complexities of AI – a key question keeps coming up: what actually defines an AI Sherpa?
At Tenzing, we’re building a very specific profile. It sits at the intersection of deep technical expertise, commercial instinct, and a real focus on application. This isn’t a generalist AI role – it’s a different kind of operator, built to turn capability into performance.
Technically strong, commercially grounded
Great AI Sherpas are, first and foremost, builders. Typically, with 5–8 years’ experience, they’re technically trained – often from engineering or product – and bring a deep, constantly evolving understanding of AI.
They stay close to what’s happening across tools, models, and workflows, but not passively. They’re hands-on – building, testing, breaking things, and figuring out what works.
What really sets them apart is their ability to apply AI under real-world constraints: speed, ambiguity, and commercial pressure. They move quickly from idea to prototype and stay focused on where AI can genuinely drive impact.
That combination – technical fluency and commercial instinct – is what allows them to work closely with CEOs and leadership teams, bridging strategy and execution.
AI-obsessed
AI Sherpas aren’t just familiar with AI – they’re deep in it.
They don’t just follow developments; they stress-test them. New models, tools, and workflows get pulled apart, rebuilt, and applied in real contexts – often before they’re widely adopted.
Put simply, they’re AI-obsessed! Not in theory, but in practice.
How they show up
Beyond skillset, mindset really matters. The best Sherpas combine high emotional intelligence with low ego. They embed quickly, build trust easily, and work well with stakeholders at all levels. They’re collaborative, pragmatic, and focused on outcomes rather than recognition.
There’s also a strong sense of ownership. They’re there to deliver impact – not just insight – and take responsibility for moving things forward.
A different kind of operator
This role is intentionally a bit different.
AI Sherpas tend to be earlier in their careers, bringing fresh thinking and a strong bias towards action. They work in a project-based way, moving quickly across different problems and contexts.
Most importantly, they’re focused. They’re not spreading themselves across multiple domains – they’re going deep into one of the most important shifts in technology right now.
The AI Sherpa profile in practice
Our first AI Sherpas, Baxter Brook and Kevon Kelly, are a good reflection of this – strong technical foundations, paired with a clear focus on applying AI in ways that actually matter commercially.
At the end of the day, AI only matters if it moves the needle. The role is about finding those opportunities quickly, testing them, and turning them into something scalable.
Turning AI into action
Ultimately, the role of the AI Sherpa is simple: identify where AI can create value, test quickly, and scale what works. Done well, this helps our portfolio companies move beyond just exploring AI – and start turning it into a real capability that drives performance.
