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How to Write an AI Strategy for Your Business (Without the Buzzwords)

Most AI strategies are 50 pages of buzzwords that nobody reads. Here is how to write one in 5 pages that your team will actually follow.

Most AI strategies are 50-page documents full of buzzwords, framework diagrams, and abstract visions that nobody reads and nobody follows. Then the company wonders why their AI initiative failed.

A good AI strategy fits in 5 pages. It answers five questions clearly. Here is how to write one.

Page 1: Business Goals (Not Technology Goals)

Start with what the business needs, not what AI can do. “Implement machine learning” is not a goal. “Reduce customer churn by 15% in 12 months” is.

List 3-5 business problems AI could address. Rank them by impact and feasibility. The intersection of “high impact” and “we have the data” is where you start.

Page 2: Use Case Prioritization

For each business goal, define 1-2 specific AI use cases. Be concrete: “AI-powered lead scoring that routes high-value leads to senior reps within 5 minutes” not “leverage AI for sales optimization.”

Score each use case on: expected ROI (1-5), data availability (1-5), implementation complexity (1-5), and time to value (1-5). The highest-scoring use case is your pilot project.

Page 3: Data Audit

For your top use case, answer: What data do we need? Do we have it? Is it clean? Is it accessible? How far back does it go? Who owns it?

Remember: 80% of AI effort is data preparation. If your data is not ready, your AI project is not ready. The strategy should include a data readiness plan with specific timelines.

Page 4: Team and Skills Plan

Who will implement this? Options: build an internal team, hire consultants, use a hybrid approach. For most Greek SMEs, the hybrid approach works best: an external partner builds and implements while training your internal team to maintain and iterate.

Skills gap is the #1 barrier to AI integration (Deloitte 2026). Your strategy needs a concrete plan to close that gap, not just “we will upskill the team.”

Page 5: Timeline, Budget, and Success Metrics

Timeline: Pilot project (weeks 1-8), evaluate results (weeks 9-10), scale or pivot (weeks 11-16). Do not plan beyond 4 months for the first phase. AI projects need fast feedback loops.

Budget: Include everything. Software, data cleanup, implementation, training, ongoing maintenance. For a first AI project in a Greek SME, expect €5,000-€25,000 total investment. ESPA can subsidize up to 50%.

Metrics: How will you measure ROI? Define baseline measurements before you start. Set a 90-day review point.

Next Steps

Your AI strategy should fit on 5 pages because it is a living document, not a monument. Write it, execute the pilot, learn, and update. If you need help building yours, our automation audit is often the best starting point. In 30 minutes we will identify your highest-impact use case.

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Need help putting this into practice? Our Consulting Services or Let’s Talk.

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