I introduced AI into developers' work and trained them to use it for concrete tasks. That taught me where value comes from: choose a problem, test a method, check the output and help people adopt the new workflow. I can bring that approach to the conversation between technology and business teams.
I use Codex, Claude, ChatGPT and other tools from OpenAI myself. In our development work, AI has helped with analysis, task breakdown, implementation and review. We estimated that AI made development about 50 percent faster in many tasks, including review and checking. This is an experience-based estimate from our team. See how we used AI in software development.
Find a task worth changing
If I am to help a company introduce AI, I start with the people who do the work. What takes time today? Which part requires judgement, and which part is repetition? Which data and confidential information are involved? What would be a better outcome for the customer or the employee? Those questions come before the choice of model or product.
My experience from customers' software projects is that technology rarely solves an unclear problem. That applies to AI as well. A small trial with a clear task, human oversight and an agreement on what we measure can yield more insight than a broad launch with vague expectations. When a trial works, we can describe the way of working, teach it to others and follow up on mistakes as well as gains.
Leadership means making the learning shared
When I introduced AI to developers, it was not enough for one employee to get an impressive result. The team had to talk about when the method worked, how output should be assessed and who took responsibility for the code that ended up in the product. We already had a culture of time for learning and knowledge sharing every other Friday. It gave us room to try out methods and share both good discoveries and mistakes.
That experience applies more broadly: people need to understand why a new workflow helps them and have the opportunity to ask critical questions. I want to give specialists room to challenge a proposal, because that is how we get a solution that lasts. It is also how you avoid mistaking fast output for good quality.
From trial to a workable way of working
I can contribute practical AI experience, software understanding, process clarification and leadership of the people who will use the tools. I connect the specialists' knowledge with a concrete business need, clear decisions and a way of working that employees can adopt.
That is the kind of transformation I am interested in: exploring where AI can genuinely make a piece of work better, and helping the organisation bring the result into everyday work without letting go of responsibility for what is delivered.
Contact: kontakt@tomc.dk · +45 299 297 67