AI strategy playbooks from Google, Microsoft, McKinsey and more

Useful #AI Strategy Playbooks to define / redefine your organization‘s AI strategy to (among others..) 1) align with / achieve your business goals 2) drive better results 3) improve customer experience 4) increase efficiency 5) manage risks … With the Number One by Accenture Link to the Report: https://lnkd.in/eTt8hY7p #AI #AIstrategy #ArtificialIntelligence #futureprooforganization

As a minimum, companies *must* use AI to enhance (white collar) employees’ productivity. However, some leaders I’ve talked with aren’t using AI to its full potential. Thanks Clare Kitching for posting this!

insightful post and i am sharing my thoughts as well An AI strategy is a business-wide plan for how artificial intelligence will be used to: Improve decision-making Increase efficiency and productivity Create new products, services, or business models Strengthen competitiveness and profitability It’s not just about technology — it’s about aligning AI initiatives with core business goals. --- 2. Key Components of an AI Strategy (a) Business Objectives First Start with the why, not the what. Ask: What business problems are we solving? --- (b) Data Strategy AI depends on quality data. That means knowing: What data you already have What data you need How it’s stored, cleaned, and governed --- (c) Technology & Tools Choose the right tools and platforms: The key is scalability and integration — AI must connect smoothly to your existing IT systems and workflows. --- (d) Talent & Skills AI success depends on people as much as machines: If in-house capability is limited, form partnerships with AI vendors, universities, or consultants. (e) Governance, Ethics & Risk Establish clear policies for: Data privacy and compliance (GDPR, etc.) This builds trust — with regulators, customers, and employees. (f) Implementation Roadmap Break it into phases: This ensures quick wins while building long-term capability. 3. How to Get It Right (Success Factors) ✅ 1. Executive Alignment: Leadership must understand AI’s value and commit budget, time, and cultural support. ✅ 2. Clear Value Proposition: Each AI project should have measurable business outcomes (e.g., increase sales by X%, cut costs by Y%). ✅ 3. Start Small, Scale Fast: Avoid over-engineering — begin with a few focused use cases that demonstrate ROI quickly. ✅ 4. Data Maturity: Invest in clean, connected, and compliant data before scaling AI solutions. ✅ 5. Change Management: Train teams, address fears, and create an AI-friendly culture where humans and machines collaborate. ✅ 6. Governance: Implement strong ethical, legal, and risk frameworks to ensure compliance and trust. ✅ 7. Continuous Learning: AI is not static — continuously refine models, monitor performance, and adopt new techniques. 4. Real-World Example Company: Starbucks AI Strategy: “Deep Brew” Uses AI to personalise customer offers, manage stock, and optimise store staffing. Combines data from loyalty apps, weather, and sales trends. Result: Higher customer engagement, reduced waste, and improved profitability. 5. Quick Checklist for Building Your AI Strategy Step Focus Area Key Question 1 Business Alignment What business goals can AI support? 2 Data Readiness Is our data accessible, clean, and secure? 3 Technology Which tools/platforms fit our needs? 4 Skills Do we have the right people or partners? 5 Governance Are we compliant and ethical? 6 Execution How do we pilot, measure, and scale?

From Accenture, BCG to Microsoft and Google every market leader is saying the same thing: Old data infrastructure is holding companies back. ❓ Still building integrations to break data silos? ❓ Still keeping every dataset synced in a central warehouse? ❓ Still spending endless hours fixing data quality before you can even start your AI work? It’s time for a data infrastructure transformation. ✅ No more integrations. ✅ No more waiting for data to be AI-ready. Data ready for AI in minutes. That’s the new standard!!!!

It looks like I have some reading ahead of me. The AI world is an interesting place right now - with a number of perspectives on how to succeed. I’m seeing several “sub-trends” that are reminiscent of all past technology adoption trends. In my heart, I’m a Systems focused thinker and I’m quite interested in AI Architecture as it relates to digital transformation. These should be very interesting. (And, I’m scripting/animating a video on AI today as well). #aiineducation #aiinSystemsThinking #aiplaybook #digitaltransformatio #aiarchitecture

Leading companies built solid data foundations first. Then they layer an AI strategy on top. Thanks to Luís Rodrigues for pulling these together. Give him a follow. Top playbooks to get started: 👇 1️⃣ Accenture – The Art of AI Maturity 🔗 https://lnkd.in/gUnDT8e8 2️⃣ Amazon - AI/ML/GenAI Cloud Framework 🔗 https://lnkd.in/gAhPsZcw 3️⃣ Bain - Winning with AI 🔗 https://lnkd.in/gpyqfbBE 4️⃣ BCG - Transforming with AI 🔗 https://lnkd.in/gMK25kcW 5️⃣ Google - Google Cloud’s AI Adoption Framework 🔗 https://lnkd.in/g2GmTJRV 6️⃣ IBM - The CEO’s guide to generative AI 🔗 https://lnkd.in/gJUe8KfK 7️⃣ McKinsey - The executive’s AI playbook 🔗 https://lnkd.in/gvCRtQ_c 8️⃣ Microsoft - CIO’s GenAI Playbook 🔗 https://lnkd.in/gUY-Z_W7 9️⃣ PWC - Agentic AI - the new frontier in GenAI 🔗 https://lnkd.in/gwgXUDJi 🔟 WEF - Empowering AI Leadership: AI C-Suite Toolkit 🔗 https://lnkd.in/g2h7y_JD How will you start defining your AI ambition? ♻️ Repost to help someone rethink their AI strategy. ⏩Follow Paul Thompson for AI insights

95% of AI projects fail. But here’s the secret: you don’t need to fail to learn. Most companies are stuck in endless pilots, wasting $$$ and time… when the world’s top firms have already published their battle-tested AI playbooks. Why reinvent the wheel when you can copy what works? 💡 I’ve pulled together 12 of the best AI strategy playbooks from McKinsey, BCG, Deloitte, Google, Microsoft, and more — all free, all actionable. 📌 Save this post (you’ll thank yourself later). Here are the gold standards for moving from AI pilots → production success: 🟢 McKinsey & Company – The Executive’s AI Playbook https://lnkd.in/dQTBSkcJ 🟢 techNgraphic (Pvt) Ltd. – How To Make Your AI Toolkit https://lnkd.in/dMctEhdy 🟢 Boston Consulting Group (BCG) – Transforming with AI https://lnkd.in/dRSmdF53 🟢 Bain & Company – Winning with AI https://lnkd.in/dV_t6Jd5 🟢 Deloitte – AI Transformation https://lnkd.in/dcUWNbhA 🟢 Amazon – AI/ML/GenAI Cloud Framework https://lnkd.in/dbc3RkYW 🟢 Google – AI Adoption Framework https://lnkd.in/dAmAyBgX 🟢 IBM – CEO’s Guide to GenAI https://lnkd.in/dZStjHet 🟢 Microsoft – CIO’s GenAI Playbook https://lnkd.in/db3WMfaS 🟢 PwC – Agentic AI Playbook https://lnkd.in/dNkevkUA 🟢 World Economic Forum – AI C-Suite Toolkit https://lnkd.in/drQnmKiX 🟢 Accenture – The Art of AI Maturity https://lnkd.in/dnrQi3j2 👉 Which one do you think is the most practical for 2025?

95% of AI projects fail. Moving from pilots to production is difficult. According to MIT, most AI pilots never scale. Thousands of companies are reinventing the wheel. Why not adopt battle-tested playbooks that already work? Follow Alex Barády for proven AI strategies that work.