AI strategy with substance: How leadership combines speed and safety

The question of whether every company must become a “tech company” today is no longer a theoretical debate. It has become a concrete reality – across all industries.

Whether in banking, automotive, retail or energy, executives everywhere face the same challenge. How can artificial intelligence (AI) and other future technologies be meaningfully integrated into the organisation? Technology alone is not the decisive factor here. At its core, it is about leadership, culture and a viable AI strategy.

Tradition vs. disruption: the balancing act that many companies are unable to resolve

In Silicon Valley, the global centre of the tech industry, the attitude towards innovation is particularly radical.

1. Mark Zuckerberg coined the principle at Meta: „move fast and break things“ – Act quickly, even if something gets broken in the process.
2. Sam Altman from OpenAI puts it even more bluntly: „No one knows what happens next.“

Historical perspectives also support this dynamic: in Guns, Germs, and Steel, Jared Diamond describes how, in a conflict between technology and tradition, technology almost always wins. Ray Dalio picks up on similar developments in his observation of the changing world order.

For many companies, this creates a dilemma:
Should we preserve stability and tradition – or focus on rapid technological adaptation?

Economic history is full of organisations that excelled in their tried-and-tested systems – and then lost touch at the very moment of change. The crucial question is therefore: how can change be achieved without jeopardising one’s own foundation? This is where a clear AI strategy comes in.

China as an example: Technology adoption as a systemic issue

We recently visited China to meet with executives from one of the country’s largest banks. The picture was clear: everyone is aware of the need to use AI, but in a conservative, highly regulated environment, the question remains: how do you do it right?

At the same time, many Chinese companies are demonstrating a high speed of implementation. Tech giants such as Tencent and new players such as DeepSeek are increasingly competing internationally – both in terms of model releases and performance advances. The issue is also being driven forward politically: the government is pursuing an “AI Plus” strategy that aims to integrate AI into the world of work and everyday life – with the goal of structurally transforming the economy.

A key success factor here is a centrally controlled implementation approach. However, another point is at least as important: technology adoption works as an ecosystem – in other words, as an interaction between government, business, research, education and infrastructure. For companies, this means that an AI strategy is not just an internal project, but must also take the context (market, regulation, talent, partners) into account.

AI in conservative industries: What successful organisations do differently

Pressure is high, especially in regulated industries, and there is little tolerance for error. Nevertheless, companies that are successful in the future will not treat innovation as a side project. They will integrate AI into their strategy, culture and operational implementation.

A good example is provided by a Harvard case study on JPMorgan Chase (USA), which we have used in discussions to show how tech adoption can succeed in a highly regulated environment.

The key insight: Successful AI implementation is not just about purchasing technology. It means that managers and teams must simultaneously manage two conflicting requirements:

• Ensuring stability: Security, compliance, trust, risk management
• Enabling disruption: Speed, experimentation, new skills, innovation

JPMorgan Chase focuses on broad empowerment (“democratisation”) and a kind of “ambidexterity” in everyday life: employees at all levels should learn to find the right balance depending on the situation. At the same time, there are clear guidelines: AI solutions are piloted, tested and only then transferred to scalable, controllable systems.

This is precisely where the difference becomes apparent: a sound AI strategy combines speed with security – rather than opting for one or the other.

What this means in concrete terms for managers

Leadership in an AI-driven world is not a tool issue. It is transformation work.

Many leaders – particularly in compliance-oriented industries – describe their state of mind as a mixture of optimism and caution: the opportunities are great, but they must remain compatible with stability, data protection, security and regulatory requirements.

In practice, this means that anyone who wants to successfully introduce AI needs leadership skills to constantly balance competing demands – and an AI strategy that is more than just a technology plan. It must bring together vision, culture and implementation.

Conclusion: AI strategy is not a tech project – it’s a management issue

An AI strategy is relevant for almost every company today – not because “everyone has to become tech-savvy,” but because AI is fundamentally changing processes, products, customer relationships and competitive dynamics.

The crucial question is not whether AI is coming, but how companies will integrate it:

• with clear guidelines,
• with scaling instead of actionism,
• with cultural anchoring instead of isolated pilots,
• and with leadership that can steer stability and innovation at the same time.

This is how AI becomes a driver of genuine, sustainable transformation—rather than an uncontrolled disruption.

| Andrew Grant