4 ways to get value from your AI investments

Many companies have invested in AI, but few are reaping the rewards. Many CFOs now face the same question: Are our AI investments actually creating value? Here are four focus areas that make the difference between AI as a cost and AI as a value creator.

If the development team in your company is still writing concrete code in 2026, something is wrong: AI can programme and does it well.

Where AI always fails is when there's high ambiguity. But code is formal language with very low ambiguity, because there are no hidden meanings. This means that large language models are almost tailor-made to work with coding solutions.

Concretely, this means you can now expect: faster prototypes for development tasks and faster development of concrete new solutions and automation that can manipulate everything that can be manipulated with code.

This means the solution you need can be developed in 2 weeks instead of 3 months – and at a fraction of the cost.

By now, everyone has access to a raw AI language model, and therefore we're moving towards something that more closely resembles what we previously called software: purpose-built solutions that perform specific tasks.

But as with all potential, it's not necessarily easy to fully realise. The winners will be the companies that are able to define concrete tasks and processes, specific and accurate datasets, and non-overlapping system landscapes for a well-instructed AI engine. Because, as with coding, ambiguity must be reduced.

The possible gains are enormous when AI becomes software. At least if you do it properly and ensure solid frameworks for the projects you set in motion.

From time to time, when we at Basico have hosted AI events, we've asked the room how many have Copilot from Microsoft. And every time, 70–80% of the hands go up.

Perhaps it can be compared to the rollout of Excel in the 90s – but otherwise it's completely and utterly unprecedented how big a task Danish companies have ahead of them in making the licences productive together with, by virtue of and despite their employees.

Because the bottom line is that the licences in the vast majority of companies have already been purchased. With a Copilot licence at DKK 150/month per user, 100 relatively unused licences cost you DKK 180,000 a year. Do you have control over whether your investment is productive? The task in 2026 for Danish companies and for you as CFO is not to remove the licences again, but to make them productive, so that you're not only paying, but also reaping benefits continuously.

There's a chasm between what AI can do and how it's actually used. Far too many workflows remain unaffected by what AI can help with – for several reasons:

• You've tried with a raw AI model that failed and have therefore concluded that AI cannot solve the task.

• You see AI as something separate, outside the tools you normally work with ‒ as a curiosity rather than a usable tool.

• Tasks must be moved over into an AI – there's no AI in the tasks.

Companies don't operate in isolation – they're embedded in complex ecosystems of systems and partners. And that's the core of the problem.

If this ecosystem isn't AI-ready, AI becomes an external discipline instead of a natural part of the work.

Therefore, it's absolutely crucial to sit down, get serious and begin the hard work of being specific, so that the unlimited potential for value creation, productivity and new ways of solving tasks that AI contains can be released.

Happy working.