Peter Yngen and Ola Hedin: resolving governance issues for AI
Ola Hedin
In the early days of the digital technology boom, Peter Yngen had a radical idea: music would shift from ownership to access — and become almost free.
As chief executive of MNW Records, one of Scandinavia’s largest independent music labels at the time, Yngen recognised that the industry’s traditional model — built on the physical distribution of music — was beginning to erode. Value, he believed, would migrate towards access.
In November 1999, MNW launched a virtual record label online. Within weeks, Yngen was presenting the concept to analysts in Stockholm. Soon after, he and colleague Ola Hedin took the idea to Ericsson, proposing that consumers could use WAP-enabled mobile phones to play music.
“At the time, Ericsson had nearly 40 per cent of the global handset market,” Yngen recalls. “If it had decided to go for it, the reach could have been global.”
The company declined, opting to focus on hardware. By October 2000, Yngen had been dismissed as MNW’s chief executive and the virtual music strategy abandoned. It would take nearly a decade for the industry to catch up — first with Apple’s App Store, then Spotify’s subscription model.
Now Yngen believes a comparable shift is under way again, this time in artificial intelligence.
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“Until now, data has been the big thing in AI,” he says. “But values-based AI is the next step.”
Yngen and Hedin’s new venture, Tribety, is built on that premise. The Stockholm-based start-up aims to address what its founders see as a growing gap in how companies deploy AI.
In recent years, the rapid adoption of generative AI tools has coincided with a striking convergence in capabilities. As models become more powerful, they are also becoming more standardised. The risk, Hedin argues, is that organisations begin to sound — and eventually behave — alike.
“AI is entering everyday work,” he says. “At the same time, the underlying technology is becoming increasingly uniform.”
The corporate response has been swift. The AI governance market is forecast to expand from $620mn in 2024 to more than $7bn by 2030, driven by regulation such as the EU’s AI Act and mounting investor pressure for oversight and transparency.
Yet much of this activity is focused on compliance. Existing platforms emphasise risk controls, bias mitigation and auditability, while AI laboratories seek to build broadly safe systems.
For Yngen, this misses the point.
“Most companies are solving the wrong problem,” he says. “Compliance matters — but it doesn’t address what happens when AI meets the reality of organisations.”
The missing layer
That reality, he argues, is shaped by factors that are difficult to formalise: tacit knowledge, cultural norms and contextual judgement. These determine how organisations communicate, make decisions and differentiate themselves — yet they remain largely absent from current AI systems.
Tribety’s approach is to make those elements explicit.
The company takes materials such as chief executive letters, strategy documents, presentations and other curated content, and translates them into what it calls a ‘judgement filter’ — a layer that sits on top of AI tools. Another way to describe it might be to call it an ethical filter, informed by the values and culture of people in the organisation.
The aim is not to control outputs in a rigid sense, but to guide them.
A marketing team, for instance, could use the filter to ensure that AI-generated campaigns maintain a company’s tone of voice. Internal communications could be aligned with organisational norms, even when drafted by automated systems.
The ambition is to ensure that AI reflects the identity of the organisation using it, rather than flattening those differences.
Ideas ahead of their time
In developing the methodology, Hedin has drawn on the work of the German sociologist Georg Simmel, who argued that value emerges through exchange and interaction rather than from the intrinsic properties of a product.
The idea has precedents in digital business models that emphasise access over ownership — from music streaming to ride-hailing platforms.
For Yngen, the parallels are familiar. In the late 1990s, the shift towards digital music was already visible, even if the market was not yet ready to act on it. Today, he sees a similar lag between technological possibility and the organisational adoption of AI.
An emerging market
Tribety is still at an early stage. The company launched only weeks ago and is in discussions with several companies. Yngen, now 71, has assembled a younger team of co-founders to scale the business, including chief executive Emil Clase.
The broader question is whether companies will move quickly enough to embed values into their AI systems, rather than treating them as a separate layer of governance.
Aligning AI with human values is already a central concern for researchers and regulators. But for businesses, the issue may be more immediate: how to remain distinct as the tools they use become increasingly indistinguishable.
If Yngen’s track record is any guide, that shift may take longer than expected to materialise — but once it does, it could reshape the competitive landscape.
The challenge for companies is no longer simply adopting AI. It is ensuring that, in doing so, they do not lose what makes them different.