A Better Way to Measure AI Adoption: 10 Metrics That Actually Matter

Posted by Dan Toma
On 12/10/2026

Most AI adoption dashboards measure activity: how many employees use AI, how many prompts they generate, or how many have access to the tools. But these numbers tell us little about whether work is getting better. We outline 10 practical metrics to help leaders move beyond vanity metrics and connect AI usage to workflow improvements, business performance and economic value.

The 3 Types of Innovation Are Not What You Think They Are (But They Do Determine Your Success)

Posted by Robyn Bolton
On 10/10/2026

The Official Story “Innovation” is not peanut butter. You can’t smear it all over everything and expect deliciousness. When discussing innovation, you must be specific so people know what you expect. This is why so many thought leaders, consultants, and practitioners preach the importance of defining different types of innovation. It’s easy to get […]

You Can’t Regulate Your Way to AI Sovereignty

Posted by Dan Toma
On 25/09/2026

Europe’s AI Act was mocked for preferring rules over innovation. Now, as US political whims disrupt giants like Anthropic, legal stability looks like a superpower. Austria wants to lure top AI labs to the EU, but can regulation alone replace American compute?

Europe’s defense industry may be facing a Kodak moment

Posted by Dan Toma
On 12/09/2026

Europe’s defense industry may be facing a Kodak moment. The issue isn’t whether low-cost drones are better than tanks, artillery, or missiles. It’s whether they are changing the economics of warfare. As the cost of attack falls dramatically, Europe risks continuing to optimize for increasingly sophisticated systems while missing a fundamental shift in what “military value” means.

Who Gets Blamed When You Kill the Pilot?

Posted by Sara Husk
On 27/08/2026

Stopping work that isn’t paying off sounds obvious, but organizations struggle to do it. Projects become “zombies,” consuming budget and attention because stopping them feels like admitting failure. The solution isn’t more courage—it’s structure: agree the criteria for stopping before the work begins and assign clear ownership. In the age of AI, knowing when and how to stop is becoming as important as knowing what to fund.

Is the ‘SaaSpocalypse’ a myth? The real cost of AI-built software

Posted by Dan Toma
On 20/08/2026

AI has made software dramatically cheaper to build. But that does not mean software has become cheaper to own. As companies consider replacing SaaS subscriptions with AI-built internal tools, the real question is not whether they can build them, but whether they are prepared to maintain, secure, evolve and ultimately own them. The SaaSpocalypse may be less about the death of SaaS—and more about companies discovering the hidden cost of running their own software.

Want to Sound Smart? Stop Saying ‘Innovation.’

Posted by Robyn Bolton
On 17/08/2026

“Innovation” has become one of the most overused words in business. We say innovation is a priority, that it drives growth, that we need a culture of innovation—but rarely explain what we actually mean. The better approach is to replace vague language with concrete outcomes: new revenue streams, new products, new customers, higher margins, new business models. The point isn’t to stop using the word innovation altogether. It’s to stop using it as a substitute for saying what we actually want to achieve.

AI Is Putting a Price Tag on Bureaucracy

Posted by Dan Toma
On 13/08/2026

AI is changing how companies measure innovation, growth, strategy and governance. As AI reduces the cost of building, Cost of Failure becomes a more powerful Innovation Accounting KPI for measuring how efficiently organizations learn, make decisions and allocate resources. The article explores how Cost of Failure can help leaders put a financial value on slow decision-making and inefficient governance—and rethink how they measure innovation and growth in the AI age.

Changing the Ending

Posted by Sara Husk
On 03/08/2026

Most AI governance discussions focus on ethics, regulation, or technology. The more immediate challenge is organizational: ensuring that the decisions determining whether AI creates value remain owned by people with the authority to make them. This article presents four structural changes that restore accountability before AI's speed turns governance into an afterthought.

Germany’s Innovation Paradox

Posted by Mihai Diga
On 30/07/2026

In 1990, a group of brilliant engineers set out to build the future. They envisioned mobile and cloud computing, digital assistants, connected devices, mobile commerce, and software ecosystems. Their company was called General Magic. General Magic did not lack talent, vision, funding, or prestigious backers. It failed because the ecosystem and infrastructure were not ready, […]

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