In the previous post, I introduced 73 AI concepts every leader should have in their vocabulary. Yet knowing the terminology is only the entry ticket to the game. The real battle is about what those terms mean for your company’s valuation – and its future. A new era is unfolding: AI is no longer the domain of IT departments; it is becoming the most closely guarded strategic asset – the digital crown jewel of the modern organisation.
The end of the “Open” era. Time for digital alchemy.
For years, the AI world thrived on a spirit of academic openness. Giants shared code, and engineers swapped insights at conferences. That chapter is now closing. Today, when tools like ChatGPT or Claude can generate code in seconds, the very structure of an algorithm has become commoditised.
So where does competitive advantage come from? Not from the tool itself, but from how it is “raised”. Real value has shifted to proprietary, unique datasets and the original processes used to train on them. What we call digital alchemy is becoming the new closely guarded recipe – the modern equivalent of Coca-Cola’s formula.
4 levels of AI value in your company
Leading organisations we work with don’t treat AI as a cost — they treat it as an investment in capital. That value shows up across four key levels:
- Valuation and IP (Intellectual Property)
- A fundamental capability
- An operational engine
- Monetisation (MaaS – Model-as-a-Service)
AI-powered intellectual property – a new dimension of intangible value
Companies that build their own algorithms, train models on unique data, or develop proprietary AI pipelines accumulate assets with growing market value. Those elements can be patented, licensed, or protected as trade secrets. What’s more, they are often more scalable than traditional products, and their value increases with data quality and with user feedback loops.
AI as a fundamental business capability
Owning in-house AI teams, proprietary models, and the ability to integrate them into processes and products is worth its weight in gold. Just as logistics is Amazon’s strategic asset and design is Apple’s, AI can become the backbone of a modern company’s operating model, product strategy, and innovation engine.
An engine for operational efficiency
AI delivers measurable outcomes: faster service, fewer errors, better decisions, lower costs. That’s a direct impact on EBITDA.
Efficiency, however, is not only about automation – it also means hyper-personalised customer experiences, demand forecasting, and resource optimisation. In short, AI acts like a turbocharger for the entire organisation.
A source of new revenue
More and more companies are offering their AI models as a service – Model-as-a-Service. The approach is not only a way to monetise in-house solutions, but also a route to creating entirely new business lines. Importantly, AI models scale exceptionally well, and their margins can outperform traditional products.
The leadership challenge: a digital fortress or a glass house?
The most significant leadership test in the coming years will be finding the balance between protection and transparency. On one hand, boards must build “digital fortresses” to protect their IP. On the other hand, customers and regulators are increasingly demanding ethical standards and algorithmic transparency.
The leaders of tomorrow will be those who can safeguard trade secrets without losing market trust. A few challenges this decade will test a board’s strategic wisdom more than ever.
Strategic insight:
Does your company already have a strategy for protecting AI models? Do you know which of your data is “rocket fuel” – and which is merely noise? Answers to those questions are available in the full version of our report.
Learn more in the AI Radar Trendbook.
The article above is only a fragment of a broader analysis of leadership in the AI era. The AI Radar Trendbook includes a dedicated chapter on building company value through AI, as well as the earlier-mentioned dictionary of 73 key terms to help you navigate these strategic questions with confidence.
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