What role should AI play in executing my strategy?

Over the past few months, I cannot recall a single strategic conversation, whether with clients, partners, or boards, which has not touched on AI. And it often raises the same question:

“What role should AI play in this strategic project?”

Not an easy one to answer for me, as I am trying to strike the right tone between cautious realism and forward-looking enthusiasm.

So, let me offer a perspective on how I approach this question.

A Gen X perspective, shaped by thirty years of experience transitioning to digital, through every hype cycle and “game-changing” innovation wave. Spoiler alert: not all those transitions went well. Many failed to deliver the long-term value they promised.

This time, the stakes are arguably higher, possibly even greater than the shift we experienced at the end of 1990s.

A few basic principles before we start:

• AI is not your strategy. It is a toolkit, potentially very powerful, that can support strategic execution. But it will not define your direction or vision.

• AI’s value in your strategy should go beyond short-term cost savings. Cost-cutting may offer quick wins, but it rarely builds lasting advantage. Strategic use of AI should focus on creating value through, for instance, better decisions, improved customer experience, or faster execution. The real strategic payoff comes not from doing things cheaper, but from doing them better.

• Technology alone does not create value: fit for purpose and organization readiness are key. Many companies have jumped on digital transformations too early or without a clear strategic intent. The memories of underwhelming ERP rollouts or failed cloud migrations should remind us: fit for purpose and preparation come first.

Step 1: Start with strategic clarity.

When AI comes up in a strategic execution discussion, I always start here:

• What is the actual strategic challenge? What outcome are you trying to achieve? If that is not yet clear, focus on solving that first.

• Where do you want to build strategic advantage? Identify precisely in which area you will create differentiated value (e.g. stronger product offering, better execution, superior customer intimacy …)  to help narrow down the search for the right AI tool able to help unlock that advantage.

• What capabilities do you already have, especially in AI? If you are starting from zero, the path forward will look quite different from if you have already built some internal expertise.

Once these are understood, we can explore how AI might help.

Step 2: Identify the right solutions and evaluate them with rigor. 

As as with anything within strategy execution, AI implementation requires thoughtful planning, not hasty trend following. In my experience, the greatest value often lies in fixing often-overlooked basics, where AI can already turn weak into solid, and be scalable.

Let me offer two real examples where I have seen AI already deliver tangible value in strategic execution without requiring massive disruption.

1. Customer service: from inconsistency to brand asset

Many brands, even premium ones, struggle with service quality. Customer support remains a common blind spot, often deprioritized when budgets tighten. And yet, it’s one of the most visible brand touchpoints.

Today’s AI tools can handle first-line support reliably and at scale. Automating responses to the most common questions, reducing wait times, and ensuring consistency across channels can quickly improve the customer experience. In some cases, cost reductions follow, but that should not be the main goal.

The trick is not to overdo it. Keep, and ideally strengthen, your human second-line support to manage edge cases. That is where loyalty is won and where sustainable brand equity gets built.

2. Sales forecasting: improving accuracy under uncertainty

Sales forecasting has long been a challenge in consumer durables, particularly in volatile or seasonal markets. Machine learning models, applied well, have proven to outperform traditional methods, especially during sudden demand shifts like those we saw during COVID.

This is one of the earliest and most mature areas of applied AI. A word of caution though: these tools are only as good as the data you feed them. You will need the right infrastructure, teams, and discipline to maintain and adapt them over time.

Pay attention to hidden costs and overlooked risks when evaluating your identified solutions.

Too many companies rush to adopt AI under pressure, underestimating the actual costs and the risks. This oversight can not only reduce the expected benefits but may also negate them completely. Here are six areas where costs often escalate:

1. Infrastructure: Most AI tools require upgrades in IT infrastructure, whether cloud-based or in-house. Legacy systems were rarely designed nor dimensioned to support AI requirements.

2. Integration and workflow redesign: AI does not operate in isolation. Existing workflows need to be redesigned, assessed, and documented to reflect new inputs and decision-making.

3. Data quality and preparation: Despite appearances, AI is not magic. Without clean, structured, and relevant data, your outputs will be of inferior quality. Training these systems can be as time-consuming as training human staff.

4. Talent: Whether you hire in-house or outsource, deploying AI effectively requires new skill sets. And today, those are not cheap.

5. Compliance and security: Data volume and sensitivity are increasing. Regulations are evolving rapidly. Do not underestimate the compliance overhead costs, especially in regions with strict data protection rules.

6. Ongoing maintenance and updates: AI models must be tuned, monitored, and adapted continuously. Plan for recurring annual costs or be prepared to have an obsolete tool sooner than expected.

Conclusion 

When someone asks “What role should AI play in this strategic project?” my default short answer is:

“Start small. Build capabilities gradually. Make sure it aligns with your strategy.”

If you want to leverage AI meaningfully in your strategy execution, take these six steps:

1. Clarify your strategic intention. What are you trying to achieve, and how will you measure success?

2. Break it down. Translate your strategy into actionable, granular initiatives.

3. Assess your capabilities. What skills, systems, and processes do you already have? Where are the gaps?

4. Explore where AI can support. Look at specific initiatives where AI could help improve execution, not replace it.

5. Do a realistic, long-term cost-benefit analysis. Avoid the temptation of over-promised savings. Make sure you can commit to the long game.

6. Pilot before you scale. If possible, testing within your specific environment business would sharpen your cost-benefit analysis and improve your decision making before deciding or not to scale the chosen solutions.

Final thought

AI will transform the way we work. No question there. But as with any tool, its value depends entirely on how it is applied. If you are serious about executing your strategy, treat AI with the same discipline and realism you would apply to any other investment.

I'd love to hear your thoughts and suggestions. Feel free to share your feedback in the comments below!

#AI #StrategyExecution #ConsumerBrands #Transformation #Newshores