We’ve all seen it: someone discovers a great AI tool, shares it in a group chat, and two weeks later everyone’s back to the old way of working. No compounding. No real acceleration. Just scattered energy and a growing sense that something important is being missed.
At Ocean Investments, we recognized this pattern in ourselves. And this year, we decided to do something about it.
We’re launching Ocean AI Academy – a group-wide program led by our CIO Dobriela Kirilova and a few other AI early adopters and enthusiasts, with one clear objective: 10x acceleration in how we work. Not across everything at once, but in the workflows we’ve already identified as highest-leverage through the internal data we have collected previously. This is not a one-off training initiative, and it’s not another theme added to an already full agenda. It’s a long-term capability engine – built to turn scattered experimentation into real, measurable outcomes across all Ocean companies.
What the academy actually is
The academy runs on a twice-monthly rhythm, using two complementary formats designed for different needs and levels of depth.
Open sessions are accessible to everyone – no technical background required. The focus is practical and immediately applicable: writing and editing, summarizing and analyzing information, preparing documents, streamlining day-to-day workflows, and understanding clearly what can and cannot be shared with AI tools. The guiding question in every session is simple: how can I use this tomorrow?
Technical sessions go deeper, tailored for roles that are building and implementing. The focus shifts to prototyping, automations, integrations, measuring impact, and creating solutions that are sustainable across teams – not just impressive in a demo.
Beyond the sessions themselves, the academy is supported by a dedicated AI team, including interns and people eager to learn and contribute, as well as real development work in the domains our survey identified as most relevant to Ocean’s operations. There’s a shared Microsoft Teams space for ongoing questions and dialogue, and a growing Knowledge Hub with session recordings, presentations, and curated resources – so that learning compounds over time rather than evaporating after each meeting.
And critically – something harder to build than any of the above: a shared platform for conversation and synergy across all Ocean companies, both those deploying AI and those using it. Different companies in the group are at different stages, solving different problems, building different things. That diversity is an asset if we create the conditions to actually learn from each other. That cross-company layer is where some of the most interesting leverage sits, and it’s something very few organizations – even large ones – manage to build well. This is what creates the ecosystem approach behind the academy: not isolated pockets of experimentation, but shared learning, shared momentum, and stronger collective progress across the group.
The harder question nobody’s asking clearly
The technology part of AI adoption turns out to be the easy part. Tools are accessible. Capabilities are no longer limited to large tech companies. Anyone with curiosity and an internet connection can start experimenting today.
What’s genuinely difficult – and what almost nobody is talking about clearly enough – is building teams that are actually capable of using AI well over time. This is the talent and organizational challenge sitting underneath all the excitement.
It’s not about training people to prompt better, though that matters. It’s a deeper structural question: what does it mean to be a high-performing team when AI can handle a significant portion of analytical and execution work? How do you hire for it? What skills become more valuable, and which ones need to be rebuilt? How do you structure accountability when the boundary between human judgment and AI output is shifting constantly? How do you keep people genuinely developing and engaged when the nature of work itself is changing underneath them?
These aren’t hypothetical questions. They’re the questions every manager and team lead at Ocean will be navigating. Ocean AI Academy is built with this in mind – not just as a way to upskill individuals, but as a way to develop the collective organizational muscle to use AI as a real competitive tool. Not an add-on. Not a novelty. A fundamental part of how work gets done, with the culture, standards, and shared language to support it.
The window is real, and it’s now
Most departments across most industries are still running largely on manual effort, institutional memory, and workflows that haven’t meaningfully changed in years. The stress, the repetitive tasks, the bottlenecks – they’re still very much human problems. And that’s precisely where the opportunity is most open.
The organizations that move from scattered pilots to deliberate, structured capability-building in the next 12-18 months will develop advantages that are genuinely hard to replicate later. Not because the tools will become unavailable – they won’t – but because organizational capability takes time to build, and the teams that start now will simply be further ahead. Habits, confidence, shared standards, proven workflows: these things don’t appear overnight, and they don’t transfer easily from one company to another.
We’ve mapped the areas that matter most for Ocean. We have the leadership in Dobriela, the structure in the academy, the cross-company platform, and the internal survey data to point us at the right problems. We also have a partnership with INSAIT – an important part of the broader AI ecosystem and talent foundation that this kind of long-term capability-building depends on. So, what we’re doing in 2026 isn’t a response to hype, and it isn’t a defensive move to avoid being left behind. It’s a deliberate bet – on our people, on the right domains, and on the compounding value of building this capability now, while the window is wide open.