What the executive team needs to know about AI: six tasks that decide who gets ahead

An opportunity that won’t stay this large for long

AI makes available what used to be reserved for large companies: knowledge on demand, analysis in minutes and routine work that no longer ties up your best people. An SME brings an advantage that large corporations can’t buy: short paths. Those who decide often sit at the same table as the people who carry it out.

The gap between leaders and the rest can already be measured. According to a BCG survey of 1,000 executives, 98 percent of companies are at least experimenting with AI. Only 4 percent generate substantial value from it, a further 22 percent see first value, and 74 percent have yet to see tangible value. Over three years, revenue growth at companies in the first two groups was 50 percent above the average.

This lead grows over time. Companies that start today build experience, well-practised processes and employees who know how to work with AI. None of that can simply be bought later.

Technology can be bought. The lead has to be earned by leadership.

Who is responsible for what

The board is responsible for the strategic direction: where do we want to be in three to five years, how will the market develop, and how is AI changing the competition? The executive team develops this strategy together with the board and makes sure it becomes reality.

	Board	Executive team
Key question	Where is the company heading, and what role does AI play?	How does that become measurable business success?
Task	Strategic direction, framework and oversight	Help develop the strategy, execute it and keep steering
Horizon	Three to five years	From the next 90 days to the implemented strategy
Result	A clear position on AI	Goals, a roadmap and proven impact

What the board is legally responsible for is covered in our article «AI governance for boards».

Where AI initiatives fail before they start

The most common pattern we see begins with a success: the board recognises the importance of AI and passes the topic to the executive team. There it competes with day-to-day business and ongoing projects. IT is busy too and pushes back. Months later little has happened, although nobody was against it.

Willingness is rarely what’s missing. Planning is. AI is not part of the strategic financial and resource planning: there is no budget, no time set aside and no reserved IT capacity. What isn’t planned doesn’t happen in day-to-day work.

An AI strategy without budget and dedicated time remains a declaration of intent.

For this to work, competencies have to grow at both levels:

• On the board, for strategy and oversight. It must be able to assess how AI is changing the market and competition, and ask whether the planned resources match its own ambition.
• On the executive team, for quantitative goals and decisions. It must be able to put a figure on the benefits of AI, weigh initiatives against each other and decide on that basis, including against other items already on the list.

What you need to know about AI yourself

You don’t need to code. But there are three things you should be able to judge from your own experience.

What AI can do reliably today and where it makes mistakes. The fastest way to learn is to use AI for your own work: a market analysis, preparing a meeting, drafting a concept. Executives who do this ask better questions and are more credible when they expect the same of others.

Where AI makes the difference in your value chain. Which costs, lead times, scarce expertise and customer experiences will change? And what does it mean if a competitor gets there first?

Which rules and risks apply to you. These include data protection, the handling of confidential data, supervisory requirements in some industries and the EU AI Act if you do business in the EU. And one fact: AI is probably already being used in your company, whether regulated or not.

The six tasks of the executive team

In our playbook «Growth through AI» we sum it up like this: Value = Strategy × Execution × Adoption. If one factor is missing, no value is created. The six tasks ensure that all three are in place.

1. Balance potential and risk. If you only see the risks, you lose time and ground. If you only see the opportunities, you put data and trust at stake. Your task is to weigh them deliberately: where do we move ahead, and where do we stay cautious? Waiting is also a decision, and it has its price too.

2. Translate the strategy into goals and a roadmap. The shared direction becomes a few strategic goals and an AI roadmap with a clear order. Focus pays off: according to BCG, leaders pursue only about half as many initiatives as less advanced companies.

3. Define success in business figures. Before you start, clarify which figure should move, by how much and by when. Usage figures show whether a tool is catching on. Whether it pays off is shown by margin, lead time, quality or revenue. At the same time, set the conditions under which an initiative will be stopped.

4. Secure resources and clarify responsibilities. AI belongs in strategic financial and resource planning: budget, suitable data, the time of the right people, IT capacity and often partners. That includes deciding what will be put on hold in return. Good governance starts with the question of who is responsible for what. One member of the executive team owns the topic overall, each initiative has a named person from the business, and a few binding rules set out what is allowed.

5. Win over the organisation. Leaders put around 70 percent of their resources into people and processes, 20 percent into technology and data and only 10 percent into algorithms. Your employees are asking what AI means for them. Tell them early and openly. Involve future users in the design, train on real work and make early successes visible. The strongest motivation is often the simplest: less routine, more time for the work that matters.

6. Set the process in motion and stay at the helm. The real leadership task begins once the first initiatives start. Check every quarter: are we still aligned with the strategic goals? Are the success criteria being met? Resources go to the initiatives that create value and are withdrawn from those that don’t. Adjust the plan when the market or the technology changes, and report to the board on impact and risks.

Where to start in the next 90 days

1. Clarify the situation: Where is AI being used today, and what data is involved?
2. Set the direction: Agree with the board what role AI should play in the business model.
3. Define goals, owners and resources: Two to three goals, each with a figure, a responsible person, a budget and dedicated time.
4. Involve employees: Say what you are planning and provide simple rules for getting started.
5. Schedule the first review: Put it in the calendar now, no more than three months out.

You don’t need to become an AI expert for this. It takes what distinguishes a good executive team anyway: clear goals, clear responsibilities and the willingness to direct resources to where they have an effect. Those who apply this to AI now build a lead that others will find hard to close.