AI, Culture and the Questions We Haven’t Started Asking

Boards have an important role in overseeing AI. They need to understand the risks, challenge management’s assumptions and ensure appropriate governance and accountability.

But responsible adoption is only part of the conversation. Are we using AI to improve the business we have, or rethinking the business we could become?

The answer has implications well beyond technology. It affects how work is organised, how people develop expertise, what leaders are expected to deliver and how organisations create value for their stakeholders.

1. From efficiency to transformation

Much of the conversation about AI focuses on productivity, automation and the skills people will need to remain relevant. These are important questions, but they tend to start with the work we do today.

Perhaps the more useful question is not which human capabilities will always remain beyond AI’s reach (the answer may well be none), but what we want work to be for, and what value the human experience brings to our organisations and their stakeholders.

Consider what happens when AI takes on tasks through which people have traditionally developed their expertise. If junior roles change, how will the next generation acquire the judgement that comes from experience? If technology releases capacity, will the organisation use it to reduce costs, improve the customer experience or create opportunities for people to apply their expertise differently?

These are choices about the future of the business, not simply the implementation of a new technology.

An organisation might use AI to make existing processes cheaper and faster. Another might use it to rethink its services, redesign how work gets done or develop new ways of serving customers. Neither efficiency nor transformation is inherently the right answer. The important question is whether the choices being made are deliberate and aligned with the organisation’s ambitions.

Case study | IKEA: Beyond automation

In 2023, Ingka Group, the largest IKEA retailer, reported that its AI chatbot, Billie, had resolved around 47% of customer enquiries over the preceding two years. Alongside this, 8,500 call-centre colleagues had been reskilled for roles including remote interior design, digital sales and more complex customer problem-solving.

The example is interesting because the organisation was doing more than automating enquiries. It was also developing its people and expanding the service it could offer customers.

The lesson is not that every business should follow the same route. It is that automation creates choices about where people can contribute next, and those choices are strategic.

When AI releases capacity in your business, what opportunities are you considering beyond reducing costs?

2. What gets rewarded shapes what happens next

The choices organisations make will depend on more than the technology. They will also be shaped by culture, leadership and the systems that influence how people behave and make decisions.

An organisation may talk about innovation while rewarding leaders primarily for cost reduction. It may encourage experimentation while holding people to performance measures that leave little room for it. It may invest in AI while overlooking how people will develop the expertise and judgement needed to work effectively alongside it.

For NEDs, HRDs and RemCo Chairs, this brings strategy, workforce planning, culture and reward into the same conversation.

If AI changes how work is done, organisations will need to think carefully about the capabilities they retain, develop and recruit. Technical understanding alone will not be enough. People will also need domain expertise, the judgement to challenge AI outputs and the ethical and social awareness to understand the consequences of decisions.

These capabilities do not develop overnight. They are shaped by experience, the opportunities people are given, the behaviour leaders model and the expectations the organisation sets.

This creates a potential tension for boards. Automating routine work may improve productivity and reduce costs, but some of that work may also have provided the experience through which people learned their profession. If those opportunities disappear, how will future specialists and leaders develop? If people increasingly rely on AI-generated analysis, how will they build the confidence and judgement to challenge it?

The risk is that an organisation improves its efficiency while gradually eroding capabilities it will later need. These consequences may not be visible in the initial business case or captured by conventional performance measures.

This is where reward and performance management matter. If leaders are primarily rewarded for immediate savings, how much incentive do they have to invest in developing people or protecting the opportunities through which future expertise is built? If experimentation is encouraged in principle but penalised when it disrupts current performance, which message will people follow?

For boards, the challenge is to ensure that leadership expectations, incentives and organisational systems support the outcomes the business wants to achieve. The balance will differ between an AIM-listed company, a private equity-backed business and a privately owned organisation, but the underlying questions are much the same.

3. What are we optimising for?

AI governance and risk oversight remain essential. Alongside this, boards need to understand whether management is making deliberate choices about how the technology will change the business, and whether those choices are creating the intended outcomes.

Looking beyond adoption rates and efficiency targets means asking what is changing in practice. Are decisions being made differently? Is the organisation developing the expertise it will need? Are employees and customers experiencing the benefits management anticipated? And are the measures being reported to the board giving a sufficiently complete picture?

Questions to take into the boardroom

Five questions can help move the discussion beyond technology adoption:

• Strategy: Are we using AI to improve existing processes, or have we identified opportunities to change how we compete and create value?
• Performance: How will we distinguish genuine business benefits from activity, such as the number of tools adopted or employees trained?
• People and expertise: As AI changes roles, how will we develop the domain expertise, judgement and experience the business will need?
• Culture and reward: Do our leadership expectations, performance measures and incentives support the behaviours needed to realise the opportunities AI presents?
• Accountability: How will we know whether the changes are working for our business and its stakeholders, and who is responsible for challenging our assumptions?

Seeing beyond the board pack

Boards rely on management for insight into how AI is being adopted and what it is delivering. But performance data and implementation updates may not reveal how work, decision-making and behaviour are changing across the organisation.

An independent perspective can help test the assumptions behind the results. It can explore the gap between intended and lived experience, bring different stakeholder perspectives into the conversation and identify cultural or organisational consequences that might otherwise be overlooked.

This is not about duplicating management’s work or second-guessing operational decisions. It is about giving the board a fuller picture of whether the organisation’s culture, leadership and systems are supporting the outcomes it wants from AI.

Perhaps the biggest risk isn’t that AI changes too much about how we work, but that we change too little about how our organisations operate.

At your next board or RemCo discussion, ask yourself: what might we be optimising away that we will later wish we had kept?

MM&K can bring an independent perspective to these questions, helping boards explore how AI is affecting organisational culture, leadership and behaviour, and whether the systems and incentives around them support the outcomes the business is seeking.

To explore this further, please contact Tamsin Howells at tamsin.howells@mm-k.com or Rob Miller at robert.miller@mm-k.com.

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