Leading with integrity in a Digital Age

By Sam Solaimani, Professor of Digital Technology, Innovation & Operations Management, Nyenrode Business Universiteit; Senior Managing Advisor, Berenschot

Most organisations did not begin their AI journey with a board decision.

They began with a colleague summarising a document, a manager testing a chatbot before a meeting, a legal team exploring a first draft, or a marketing professional generating ideas for a campaign. In many cases, AI entered the organisation quietly, not through a formal transformation programme, but through individual curiosity and the pressure to work faster.

That is understandable. Innovation often starts with people trying to improve their work. But it also creates a leadership challenge. In many organisations, actual AI use is moving faster than policy, governance and collective understanding.

This is where integrity becomes essential.

In its simplest form, integrity means alignment between what we say and what we do. Values are not just words on a website or principles in a code of conduct. They become real only when they are visible in decisions, systems, incentives and daily behaviour.

In the digital age, that alignment is becoming harder to maintain. An organisation may speak confidently about responsible AI, ethical principles and human oversight, while employees are already using AI tools in ways that are informal, uncoordinated or not fully understood. The result is not only a governance gap, but an integrity gap.

From individual use to organisational responsibility

In Berenschot’s annual AI Trend Research – conducted in collaboration with PublicNL and Link Magazine, and this year joined by Nyenrode Business University - we examine how organisations are actually using AI in practice.

One of the striking findings from last year’s edition was the gap between expectation and structure. More than 90% of organisations expected AI use to increase, while fewer than 10% reported structural use based on formal policy. The most frequently mentioned concerns included digital security and the knowledge and skills needed to use AI responsibly.

For this year’s edition, we are again gathering insights from organisations across sectors. Directors, executives and professionals who want to contribute to this broader understanding of AI adoption can participate in the short AI Trend Research survey. The results will be shared with participants and are intended to offer practical insights for their own organisations.

This finding should not lead to panic, but it should focus attention. AI is already present in daily work. Employees experiment, teams find shortcuts, and business units test tools because the pressure to improve productivity, quality and speed is real.

The answer is not to stop experimentation. That would be unrealistic and, in many cases, unwise. The answer is to lead it.

If leaders do not create clarity, the organisation will still move — but it will move through fragmented choices, informal habits and local improvisation. That is not a deliberate transformation. It is organisational drift.

Make the invisible visible

The first responsibility of leadership is to understand reality.

Many executive teams see approved systems, official pilots and formal technology roadmaps. They see less of the informal AI use already happening in departments, teams, and individual workflows. This so-called “shadow AI” is not always malicious or reckless. Often, it is simply the result of motivated employees trying to solve practical problems.

But what remains invisible cannot be governed.

Leaders should, therefore, create conditions in which actual AI use can surface. This requires more than a policy. It requires psychological safety. If employees believe that transparency will be punished, they will not disclose how they use AI. If they believe the organisation is willing to learn, they are more likely to share practices, concerns and lessons.

That visibility is the starting point for responsible scaling.

Governance should change behaviour

There is a temptation to respond to digital risk with documents. Policies, frameworks and principles all have a role to play, especially for multinational companies operating across jurisdictions. But a policy that nobody reads, understands or applies is not governance. It is a theatre.

Effective AI governance is proportional. It should be strict where the risks are high and simple where the risks are low. Summarising a public document is not the same as using AI to support recruitment, pricing, credit decisions, compliance assessments or customer interactions. The level of oversight should reflect the materiality of the decision.

Good governance is also practical. It helps people make better decisions in real situations. Can I enter this data into this tool? Can I use AI-generated analysis in a client report? When do I need human review? Who is accountable if the output is wrong? Which use cases are encouraged, restricted or prohibited?

The test is not whether governance exists. The test is whether it changes behaviour.

Integrity cannot be delegated

Legal, compliance, risk and IT functions are essential in this agenda. But they cannot carry it alone. AI affects strategy, operations, people, customers and reputation. It is therefore a leadership issue.

Executives set the tone not only by how they speak about AI but also by how they use it themselves. Leaders who are curious, transparent and thoughtful in their own use of AI create a different culture from leaders who delegate the topic to a working group and move on.

This does not mean that every board member must become a technologist. It does mean that leaders need enough understanding to ask the right questions, challenge easy answers and recognise when risks are being hidden behind technical language.

For multinational companies, the stakes are especially high. They operate across legal systems, cultures and stakeholder expectations. A digital practice that seems acceptable in one context may create legal, ethical or reputational problems in another. At a global scale, small blind spots can quickly become serious issues.

The real test of digital leadership

The real test of leadership is not whether an organisation can launch AI pilots. Almost every organisation can do that. The test is whether it can translate experimentation into reliable, responsible and value-creating practice.

That requires more than technology. It requires organisational adaptability: the ability to renew processes, capabilities, governance and culture as technology changes. In my experience, digital transformations rarely fail because the technology is not impressive enough. They fail because the organisation lacks the capability to absorb, steer and scale the change.

Leading with integrity in a digital age, therefore, means asking more than “Can we use this technology?” It means asking: “Should we use it here, in this way, for this purpose, with these safeguards?”

AI will continue to move quickly. Regulation will continue to develop. Competitive pressure will continue to rise. But trust remains the foundation on which business is built. Customers, employees, regulators, investors and society will judge companies not only on whether they use AI, but also on whether they use it responsibly.

Integrity is not the brake on digital innovation. It is the steering system. Without it, speed becomes risk. With it, digital transformation can become what it should be: a source of better work, better decisions and more resilient organisations.

Prof. Dr. Sam Solaimani is involved in the annual AI Trend Research, a collaboration between Berenschot, PublicNL, Link Magazine and Nyenrode Business Universiteit. The research tracks how organisations across sectors are adopting, governing and responding to AI — and the organisational implications that follow.