AI Strategy is about people.
People will identify opportunities, devise risk mitigations, set guardrails and establish policies that will govern the use of AI.
As part of an AI change management approach, organisations must plan for building the knowledge and skills their people need to enable, adopt and embrace AI.
This is Key to creating an AI Strategy, just like any business strategy. Everything starts with the right people.

So what does an AI Business Strategy look like:

AI Business Strategy

Objective:
To leverage Artificial Intelligence (AI) to drive operational efficiency, enhance customer experience, and unlock new revenue streams, positioning the company as a technology-forward industry leader.

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1. Vision & Goals

• Short-Term (6–12 months): Automate routine processes, pilot AI-powered analytics, and improve decision-making speed.
• Mid-Term (1–2 years): Integrate AI into core products/services, personalize customer engagement, and optimize supply chains.
• Long-Term (3–5 years): Develop proprietary AI capabilities, expand AI-driven offerings, and lead innovation in the sector.

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2. Key Areas of Focus

• Process Automation: Use AI (e.g., RPA + ML) to reduce manual effort in back-office functions.
• Customer Experience: Deploy chatbots, recommendation engines, and predictive support tools.
• Data & Analytics: Implement AI for real-time forecasting, trend analysis, and strategic insights.
• Product Innovation: Embed AI into products to create smarter, more adaptive offerings.
• AI Governance: Ensure responsible AI use, focusing on fairness, transparency, and data privacy.

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3. Implementation Roadmap

• Q2–Q3: Assess AI readiness; identify high-impact use cases; form AI task force.
• Q3–Q4: Launch MVPs; begin workforce training; invest in data infrastructure.
• Year 2: Scale successful pilots; build in-house AI capabilities; form external partnerships.

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4. Partnerships & Talent

• Collaborate with AI startups, academic institutions, and cloud providers.
• Upskill current employees and hire data scientists, AI/ML engineers, and ethical AI advisors.

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5. Success Metrics

• % cost savings via automation
• Increase in customer satisfaction/retention
• New revenue from AI-enhanced products
• AI project ROI & adoption rates

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Governance & Ethics
Establish an AI ethics board, align with industry standards (e.g., ISO/IEC 42001), and ensure compliance with local/global AI regulations.

Further Reading:

https://www.techtarget.com/searchenterpriseai/tip/How-to-formulate-a-winning-AI-strategy