Strategy before Technology

Strategy Before Technology: Why SMEs Must Start With “Why” Before Adopting AI

Artificial intelligence has captured the imagination of businesses everywhere. From writing content to forecasting sales, the possibilities feel endless. For SMEs in Ireland and the UK, the temptation is strong to dive straight in, experiment with tools, and hope for quick wins.

But here’s the truth: AI without strategy is just noise. Unless businesses start with the why, they risk wasted investment, confused teams, and solutions that don’t actually solve the problems that matter.

Just as you wouldn’t expand your team without a business plan, you shouldn’t bring in AI without a clear strategy. Technology must always follow strategy.

1. The Risk of Starting With the Tools

Every week, new AI tools flood the market, each promising to save time or increase productivity. For SMEs already juggling limited resources, this can create “shiny object syndrome.” Leaders feel they must adopt something (anything) simply to keep up.

The problem? Implementing AI tools in isolation leads to:

• Fragmented systems that don’t talk to each other.

• Confused employees who don’t understand how AI fits into their work.

• No measurable results, making it hard to prove the investment was worthwhile.

Without strategy, AI becomes an experiment rather than a driver of growth.

2. Strategy Defines the “Why”

At its core, strategy is about focus. SMEs must decide: What do we want to achieve? AI should only be introduced once the answers are clear.

Ask questions like:

• Do we want to reduce costs, or is growth the priority?

• Is customer satisfaction slipping, or is staff time the bigger challenge?

• What outcomes would truly move the needle in the next 12 months?

Once these goals are defined, AI can be assessed through a strategic lens: Will this tool help us achieve our business objectives faster, more efficiently, or more effectively? If the answer is no, then it’s not the right tool, at least not yet.

3. Strategy Ensures Integration, not Disruption

Most SMEs already run on a patchwork of systems - CRMs, accounting software, marketing platforms. Dropping a new AI tool into the mix without a plan often creates duplication instead of efficiency.

A strategy-first approach maps out:

• Where AI fits within existing workflows.

• How tools connect to current systems.

• Who will use them and how their roles may evolve.

This avoids the trap of AI being a bolt-on gimmick and ensures it actually supports the way the business operates.

4. Measuring Success Becomes Possible

Strategy turns vague hopes (“AI will make us more efficient”) into specific goals (“Reduce invoice processing time by 40%”). This allows leaders to measure whether AI adoption is working.

Without benchmarks, it’s impossible to know whether AI is delivering real business value or simply keeping staff busy experimenting.

5. Risk and Compliance Management

AI is not risk-free. From inaccurate outputs to data privacy concerns, SMEs need to tread carefully. Regulations like GDPR in the UK and Ireland and the EU AI Act, make it clear that businesses are accountable for how they use AI.

A strategy-first approach:

• Defines acceptable use policies for staff.

• Identifies where human oversight is essential.

• Clarifies what data can and cannot be shared.
  

This protects the business legally, ethically, and reputationally.

6. Gaining Team Buy-In

Employees are the ones who will use AI day to day. If they don’t understand why it matters, adoption will fail.

By starting with strategy, leaders can explain:

• The business challenge AI is solving.

• How it will make staff roles easier, not redundant.

• The specific improvements expected in the business.

This transparency builds trust and makes teams far more likely to embrace AI.

7. A Simple Framework for SMEs

Before rushing into tools, SMEs can use this 3-step strategy-first framework:

1. Clarify the Why

   • What’s the biggest challenge or opportunity right now?

   • Why does it matter to the business?

2. Define the Outcomes

   • What does success look like?

   • How will we measure it?

3. Choose the Tools Last

   • Which AI solutions best support the goals we’ve defined?

   • How will we integrate them into current systems?

Strategy First, AI Second - AI is not a silver bullet, but used wisely, it can be transformative.

Don't just take our word for it ... Recent findings from MIT’s NANDA initiative, known as “The GenAI Divide: State of AI in Business 2025”offer a sobering reality check: 95% of businesses deploying generative AI initiatives failed to generate measurable P&L! You can read the full report here: https://nanda.media.mit.edu/