--- title: "Enterprise AI Strategy: The Alice Labs 6-Step Framework (2026)" description: "The Alice Labs Enterprise AI Strategy Framework, used in 100+ Nordic enterprise engagements. 6 steps from readiness to scale, with EU AI Act alignment built in from day one." lang: en json-ld: | [ { "@context": "https://schema.org", "@graph": [ { "@type": "Organization", "@id": "https://alicelabs.ai/#organization", "name": "Alice Labs", "alternateName": [ "Alice Labs AB", "AliceLabs" ], "legalName": "Alice Labs AB", "identifier": "559443-5470", "foundingLocation": { "@type": "Place", "name": "Stockholm, Sweden" }, "url": "https://alicelabs.ai", "logo": { "@type": "ImageObject", "@id": "https://alicelabs.ai/#logo", "url": "https://alicelabs.ai/images/alice-logo.png", "contentUrl": "https://alicelabs.ai/images/alice-logo.png", "width": 2000, "height": 2027, "caption": "Alice Labs" }, "image": { "@id": "https://alicelabs.ai/#logo" }, "description": "Alice Labs är en svensk AI-byrå som hjälper företag implementera AI - från strategi till skalning.", "slogan": "From AI strategy to measurable results.", "foundingDate": "2023", "email": "hej@alicelabs.ai", "telephone": "+46734157476", "address": { "@type": "PostalAddress", "streetAddress": "Hammarbybacken 27", "addressLocality": "Stockholm", "postalCode": "120 30", "addressCountry": "SE" }, "contactPoint": [ { "@type": "ContactPoint", "contactType": "customer service", "email": "hej@alicelabs.ai", "telephone": "+46734157476", "areaServed": [ "SE", "EU" ], "availableLanguage": [ "Swedish", "English" ] } ], "areaServed": [ { "@type": "Country", "name": "Sweden" }, { "@type": "Place", "name": "Europe" } ], "knowsAbout": [ "AI strategy", "AI implementation", "AI agents", "AI automation", "Generative AI", "AI governance", "AI training", "Machine learning", "Large language models", "RAG", "AI consulting", "Digital transformation", "AI search optimization", "LLMO", "AI for enterprise" ], "founder": [ { "@id": "https://alicelabs.ai/#linus" }, { "@id": "https://alicelabs.ai/#eric" } ], "sameAs": [ "https://www.linkedin.com/company/alicelabsai", "https://www.trustpilot.com/review/alicelabs.ai", "https://www.wikidata.org/wiki/Q140369570" ] }, { "@type": "Person", "@id": "https://alicelabs.ai/#linus", "name": "Linus Ingemarsson", "givenName": "Linus", "familyName": "Ingemarsson", "jobTitle": "Co-Founder", "description": "Co-founder of Alice Labs. 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Build governance and classification into Step 3, not after a pilot succeeds." }, { "@type": "WebPageElement", "isAccessibleForFree": true, "name": "Five Mistakes That Kill Enterprise AI Pilots", "url": "https://alicelabs.ai/en/insights/enterprise-ai-strategy-framework#common-mistakes", "description": "Industry reporting (Gartner, BCG, MIT Sloan) consistently cites five patterns: starting with technology instead of business problems, no governance (shadow AI), no success metrics, underinvesting in change management, and treating GenAI as a project instead of a capability." }, { "@type": "WebPageElement", "isAccessibleForFree": true, "name": "How to Measure Strategy Success", "url": "https://alicelabs.ai/en/insights/enterprise-ai-strategy-framework#measurement", "description": "Track four portfolio-level metrics quarterly: use cases in production, business value realized, time-from-idea-to-pilot, and compliance incidents. 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A further 3–6 months to get the first pilots to production (Steps 5–6). Full portfolio maturity is a 12–24 month journey." } }, { "@type": "Question", "name": "Who should own enterprise AI strategy?", "acceptedAnswer": { "@type": "Answer", "text": "Ownership works best at Chief Digital Officer, Chief Data Officer, or Chief Technology Officer level, with an explicit mandate from the CEO or COO. A dedicated AI lead (often a Head of AI or Director of AI) runs day-to-day. Avoid putting strategy under a single business function — it won't cross-functional." } }, { "@type": "Question", "name": "How do I prioritize AI use cases?", "acceptedAnswer": { "@type": "Answer", "text": "Score every candidate on two axes: business impact (€ value + strategic importance) and feasibility (data availability + technical complexity + change-management effort). Plot on a 2x2 matrix. Prioritize high-impact + high-feasibility. Park high-impact + low-feasibility for the next planning cycle." } }, { "@type": "Question", "name": "Build or buy AI?", "acceptedAnswer": { "@type": "Answer", "text": "Most mature programs are 70% buy (SaaS AI products + foundation models via API) and 30% build (proprietary data, differentiated workflows). Use a five-factor scoring matrix: strategic differentiation, data proprietary-ness, time-to-value, 3-year TCO, and in-house capability. Default to buy unless two or more factors score strongly toward build." } }, { "@type": "Question", "name": "What does enterprise AI strategy cost?", "acceptedAnswer": { "@type": "Answer", "text": "Strategy phase: €25,000–€150,000 depending on scope (single function vs enterprise-wide). First-pilot cost: €50,000–€500,000 depending on complexity. At-scale production: €500,000–€5M per year across the portfolio for mid-market; substantially higher for global enterprises." } }, { "@type": "Question", "name": "When do EU AI Act obligations apply?", "acceptedAnswer": { "@type": "Answer", "text": "The Act entered into force 1 August 2024. Unacceptable-risk prohibitions applied from 2 February 2025. General-purpose AI model obligations applied from 2 August 2025. High-risk AI system obligations apply from 2 August 2026 (with a longer transition for systems already on the market). Plan Step 3 around the 2026 date for high-risk systems." } }, { "@type": "Question", "name": "What is the biggest reason enterprise AI strategies fail?", "acceptedAnswer": { "@type": "Answer", "text": "Poor use case selection. Gartner, McKinsey and BCG all report that spreading investment across too many low-impact use cases is the primary cause of underwhelming ROI. Top-quartile companies concentrate spend on 3–5 high-impact use cases rather than running 20 small pilots." } } ] }, { "@context": "https://schema.org", "@type": "HowTo", "name": "How to Build an Enterprise AI Strategy: 6-Step Framework", "description": "The Alice Labs Enterprise AI Strategy Framework, used in 100+ Nordic enterprise engagements. 6 steps from readiness to scale, with EU AI Act alignment built in from day one.", "totalTime": "12 min read", "step": [ { "@type": "HowToStep", "position": 1, "name": "Run an AI readiness assessment", "text": "Audit five dimensions: business alignment, data maturity, technology stack, talent and skills, and AI governance. Output is a 1–5 scorecard per dimension with a 90-day action list. Expect 2 weeks. Red flags: no data catalog, no data owner per domain, or no named executive sponsor.", "url": "https://alicelabs.ai/en/insights/enterprise-ai-strategy-framework#step-1" }, { "@type": "HowToStep", "position": 2, "name": "Discover and prioritize use cases", "text": "Run structured workshops with business function leaders (sales, marketing, HR, operations, finance, product) to surface 30–60 candidate use cases. Score each on business impact (€ value, strategic importance, strategic fit) and feasibility (data availability, technical complexity, change-management effort). Output is a prioritized shortlist of 3–5 use cases for the 12-month plan. Expect 2 weeks.", "url": "https://alicelabs.ai/en/insights/enterprise-ai-strategy-framework#step-2" }, { "@type": "HowToStep", "position": 3, "name": "Set governance and classify under the EU AI Act", "text": "Decide who owns AI risk, model approval, and incident response. Classify each shortlisted use case under the EU AI Act risk categories (minimal, limited, high-risk, unacceptable). For high-risk use cases, budget for Fundamental Rights Impact Assessment (FRIA), post-market monitoring, and technical documentation per Annex IV. Output is a one-page governance operating model plus risk classification per use case. Expect 1 week.", "url": "https://alicelabs.ai/en/insights/enterprise-ai-strategy-framework#step-3" }, { "@type": "HowToStep", "position": 4, "name": "Decide build vs buy per use case", "text": "Use a five-factor scoring matrix: strategic differentiation, data proprietary-ness, time-to-value, total cost of ownership over 3 years, and in-house capability. Commodity use cases (meeting summaries, basic copilots) score towards buy; differentiated use cases (your proprietary data, your unique workflow) score towards build. Most mature programs end up ~70/30 buy/build. Output is a build-vs-buy decision plus vendor shortlist per use case. Expect 1 week.", "url": "https://alicelabs.ai/en/insights/enterprise-ai-strategy-framework#step-4" }, { "@type": "HowToStep", "position": 5, "name": "Design and run the first pilots", "text": "For each pilot, define the business owner, target metric with baseline and goal (e.g. 30% cycle-time reduction), success threshold, kill criterion, and timeline (typically 6–10 weeks). Assemble a cross-functional squad — business owner, technical lead, data engineer, governance partner. Expect 4 weeks from kick-off to first measurable result. Output is a validated or killed hypothesis per pilot.", "url": "https://alicelabs.ai/en/insights/enterprise-ai-strategy-framework#step-5" }, { "@type": "HowToStep", "position": 6, "name": "Scale successful pilots and operationalize", "text": "For pilots that hit the success threshold, build the production path: integration, change management, training, support model, monitoring, and SLA definition. Move ownership from the AI team to the business function. Add new use cases into the backlog and rerun steps 2–5 on the next wave. Budget 3–6 months from pilot-complete to at-scale production. Set a quarterly review cadence for the portfolio.", "url": "https://alicelabs.ai/en/insights/enterprise-ai-strategy-framework#step-6" } ] }, { "@context": "https://schema.org", "@type": "ItemList", "name": "Related articles", "itemListElement": [ { "@type": "ListItem", "position": 1, "url": "https://alicelabs.ai/en/insights/why-ai-projects-fail", "name": "Why AI Projects Fail: 7 Root Causes & How to Avoid Them" }, { "@type": "ListItem", "position": 2, "url": "https://alicelabs.ai/en/insights/ai-adoption-by-country-2026", "name": "AI Adoption by Country 2026" }, { "@type": "ListItem", "position": 3, "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "name": "Best AI Agent Frameworks 2026" } ] }, { "@context": "https://schema.org", "@type": "ItemList", "name": "Table of Contents", "numberOfItems": 4, "itemListOrder": "https://schema.org/ItemListOrderAscending", "itemListElement": [ { "@type": "ListItem", "position": 1, "name": "Why a Framework — and Not a PowerPoint", "url": "https://alicelabs.ai/en/insights/enterprise-ai-strategy-framework#why-this-framework" }, { "@type": "ListItem", "position": 2, "name": "Getting the EU AI Act Into the Strategy From Day One", "url": "https://alicelabs.ai/en/insights/enterprise-ai-strategy-framework#eu-ai-act-alignment" }, { "@type": "ListItem", "position": 3, "name": "Five Mistakes That Kill Enterprise AI Pilots", "url": "https://alicelabs.ai/en/insights/enterprise-ai-strategy-framework#common-mistakes" }, { "@type": "ListItem", "position": 4, "name": "How to Measure Strategy Success", "url": "https://alicelabs.ai/en/insights/enterprise-ai-strategy-framework#measurement" } ] } ] }, { "@context": "https://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": 1, "name": "Home", "item": "https://alicelabs.ai/en" }, { "@type": "ListItem", "position": 2, "name": "Insights", "item": "https://alicelabs.ai/en/insights" }, { "@type": "ListItem", "position": 3, "name": "AI Strategy", "item": "https://alicelabs.ai/en/insights/ai-strategy" }, { "@type": "ListItem", "position": 4, "name": "How to Build an Enterprise AI Strategy: 6-Step Framework" } ] } ] --- [Alice Labs](/en/) Services [ What we do ](/#welcome)[ About Alice ](/#who-we-are)[ Case ](/en/case)[ Insights ](/en/insights)[ Contact ](/#email-form) 1. [Home](/en) [Insights](/en/insights) [AI Strategy](/en/insights/ai-strategy) How to Build an Enterprise AI Strategy: 6-Step Framework AI Strategy How-to Guide Fresh Last reviewed: 1 June 2026 · 85d ago # How to Build an Enterprise AI Strategy: 6-Step Framework ## TL;DR Quick Answer Cited by AI > Build an enterprise AI strategy in six steps: (1) AI readiness assessment, (2) use case discovery and prioritization, (3) governance and EU AI Act risk classification, (4) build-vs-buy decisions, (5) pilot design and execution, (6) scaling and operationalization. Expect 6–8 weeks for strategy, 3–6 months to first production deployment. A practical, 8-week framework used in 100+ enterprise engagements. Covers readiness, use case prioritization, governance, pilots, scaling — with EU AI Act alignment built in from day one. An enterprise AI strategy is a multi-year plan that aligns AI investment with business objectives, governance, talent, and risk tolerance. The Alice Labs Enterprise AI Strategy Framework — refined across 100+ Nordic enterprise engagements — specifies where AI will create value, how use cases are prioritized, who owns delivery, and how compliance (EU AI Act, sector regulation, data privacy) is maintained as the portfolio scales. Time 6–8 weeks Difficulty Intermediate Typical cost €25,000–€150,000 (strategy phase) Tools Cross-functional steering committee, Use case inventory template, EU AI Act risk classification checklist… ## Before you start - Executive sponsor at C-level (CEO, COO, CTO, or CDO) - Preliminary view on data maturity (quality, governance, platforms) - Willingness to run 1–3 pilots within 6 months ## What you'll have at the end A prioritized 12-month AI roadmap with 3–5 funded use cases, a governance operating model aligned to EU AI Act, a build-vs-buy decision per use case, and go-live dates for the first 1–3 production pilots. ![Linus Ingemarsson - Author at Alice Labs](/images/linus-ingemarsson.png) Written by [Linus Ingemarsson ](https://www.linkedin.com/in/linus-ingemarsson/) ![Eric Lundberg - Reviewer at Alice Labs](/images/eric-lundberg.png) Reviewed by [Eric Lundberg ](https://www.linkedin.com/in/eric-lundberg-3530451bb/) Published April 15, 2026 · Updated June 1, 2026 12 min read ## 6-step process 0/6 complete 1. 01 #### Step 1: Run an AI readiness assessment Audit five dimensions: business alignment, data maturity, technology stack, talent and skills, and AI governance. Output is a 1–5 scorecard per dimension with a 90-day action list. Expect 2 weeks. Red flags: no data catalog, no data owner per domain, or no named executive sponsor. 2. 02 #### Step 2: Discover and prioritize use cases Run structured workshops with business function leaders (sales, marketing, HR, operations, finance, product) to surface 30–60 candidate use cases. Score each on business impact (€ value, strategic importance, strategic fit) and feasibility (data availability, technical complexity, change-management effort). Output is a prioritized shortlist of 3–5 use cases for the 12-month plan. Expect 2 weeks. 3. 03 #### Step 3: Set governance and classify under the EU AI Act Decide who owns AI risk, model approval, and incident response. Classify each shortlisted use case under the EU AI Act risk categories (minimal, limited, high-risk, unacceptable). For high-risk use cases, budget for Fundamental Rights Impact Assessment (FRIA), post-market monitoring, and technical documentation per Annex IV. Output is a one-page governance operating model plus risk classification per use case. Expect 1 week. 4. 04 #### Step 4: Decide build vs buy per use case Use a five-factor scoring matrix: strategic differentiation, data proprietary-ness, time-to-value, total cost of ownership over 3 years, and in-house capability. Commodity use cases (meeting summaries, basic copilots) score towards buy; differentiated use cases (your proprietary data, your unique workflow) score towards build. Most mature programs end up ~70/30 buy/build. Output is a build-vs-buy decision plus vendor shortlist per use case. Expect 1 week. 5. 05 #### Step 5: Design and run the first pilots For each pilot, define the business owner, target metric with baseline and goal (e.g. 30% cycle-time reduction), success threshold, kill criterion, and timeline (typically 6–10 weeks). Assemble a cross-functional squad — business owner, technical lead, data engineer, governance partner. Expect 4 weeks from kick-off to first measurable result. Output is a validated or killed hypothesis per pilot. 6. 06 #### Step 6: Scale successful pilots and operationalize For pilots that hit the success threshold, build the production path: integration, change management, training, support model, monitoring, and SLA definition. Move ownership from the AI team to the business function. Add new use cases into the backlog and rerun steps 2–5 on the next wave. Budget 3–6 months from pilot-complete to at-scale production. Set a quarterly review cadence for the portfolio. ## Key Takeaways - EU27 enterprise AI adoption reached 20.0% in 2025 (Eurostat), so most enterprises are now past the 'should we?' phase and into 'how?'. - The biggest predictor of AI ROI is use case selection, not model choice — McKinsey and BCG both report top-quartile companies concentrate AI spend on a narrow set of high-impact use cases. - Govern for the EU AI Act from day one: high-risk use cases (HR, credit, healthcare, critical infrastructure) need Fundamental Rights Impact Assessments before deployment. - Build vs buy is rarely 100%: most mature AI programs are 70% buy (SaaS AI + foundation models) and 30% build (proprietary data, differentiated workflows). - Pilots that reach production share three traits: clear success metric defined upfront, a named business owner, and a kill criterion if metrics aren't met by week 8. ### Contents 12 min left - [01 Why a Framework — and Not a PowerPoint ](#why-this-framework) - [02 Getting the EU AI Act Into the Strategy From Day One ](#eu-ai-act-alignment) - [03 Five Mistakes That Kill Enterprise AI Pilots ](#common-mistakes) - [04 How to Measure Strategy Success ](#measurement) 01 / 04 Step ## Why a Framework — and Not a PowerPoint In short Most enterprise AI strategies fail in execution, not in strategy. A framework imposes decisions with owners, dates, and kill criteria — not slides. McKinsey's 2025 State of AI found that top-quartile companies concentrate AI investment on fewer, higher-impact use cases rather than spreading across dozens of pilots. In 100+ enterprise engagements, the pattern we see is consistent: strategies that ship as 60-slide PowerPoints get filed and never executed. Strategies that ship as a one-page operating model plus a 3-use-case roadmap survive the first budget cycle and produce measurable results. The six-step framework below is biased toward action. Each step has a time-boxed output and an owner. If you can't name the owner, the step isn't done. 02 / 04 Step ## Getting the EU AI Act Into the Strategy From Day One In short The EU AI Act (Regulation 2024/1689) entered into force 1 August 2024. Provisions on unacceptable-risk systems applied from 2 February 2025; obligations for general-purpose AI models applied from 2 August 2025; high-risk AI rules apply from 2 August 2026. Build governance and classification into Step 3, not after a pilot succeeds. A common failure pattern: a pilot reaches production, then compliance raises objections, then the project is delayed 6–12 months for rework. Classify risk in Step 3, before you spend on Step 5. High-risk categories most enterprises encounter: - Employment (recruitment, evaluation, task allocation) - Access to essential services (credit scoring, insurance pricing) - Education (admission, testing, evaluation) - Law enforcement and migration (narrower, but check scope) - Critical infrastructure (energy, transport, water) For these, Fundamental Rights Impact Assessment (FRIA), post-market monitoring, and technical documentation obligations apply. Budget accordingly — compliance overhead can add 15–30% to use-case TCO for high-risk systems. Don't skip classification The Act's fines for non-compliance on prohibited systems reach €35M or 7% of global annual turnover — whichever is higher. High-risk system violations can reach €15M or 3%. Treat classification as a Day-1 deliverable. EU AI Act, Art. 99 03 / 04 Step ## Five Mistakes That Kill Enterprise AI Pilots In short Industry reporting (Gartner, BCG, MIT Sloan) consistently cites five patterns: starting with technology instead of business problems, no governance (shadow AI), no success metrics, underinvesting in change management, and treating GenAI as a project instead of a capability. The five recurring failure patterns: 1. **Technology-first framing.** "Let's do something with LLMs" is not a strategy. Start from business problems, work back to technology. 2. **No governance = shadow AI.** Employees will use AI tools anyway. Without a policy and a sanctioned stack, you get data leakage and compliance exposure. 3. **No success metric.** Pilots that launch without a defined metric and baseline cannot be judged — so they drift for 6–12 months and then get quietly killed. 4. **Under-investing in change management.** AI adoption is 20% technology, 80% human workflow change. Budget accordingly. 5. **Treating GenAI as a project.** It's a capability. Build a persistent AI function, not a one-off program. ![Linus Ingemarsson](/images/linus-ingemarsson.png)![Eric Lundberg](/images/eric-lundberg.png)![Alice Holmgren](/images/alice-holmgren.png) Alice Labs practitioner team ## Need this framework, but for your enterprise? We run the full 6-step strategy engagement in 6–8 weeks — including EU AI Act classification, use case prioritization, and a funded 12-month roadmap. 100+ engagements delivered. [Book a strategy call](#contact) 04 / 04 Step ## How to Measure Strategy Success In short Track four portfolio-level metrics quarterly: use cases in production, business value realized, time-from-idea-to-pilot, and compliance incidents. Individual pilot metrics roll up; the portfolio metrics signal whether the strategy is working. Four metrics, reviewed quarterly at the AI steering committee: - **Production count.** Number of AI use cases live in production, by business function. Goal: 3–5 in year one, 10+ in year two. - **Value realized.** Business value captured in € (cost avoided, revenue lifted, time saved × loaded cost). Be strict — uncaptured value is theatre. - **Time to pilot.** Days from use case approved to pilot kick-off. Mature programs reach <30 days; early programs sit at 90+. - **Compliance incidents.** Policy violations, model drift escalations, FRIA findings. Low numbers can mean you're not looking; steady low numbers mean controls are working. ## About the Authors & Reviewers Published April 15, 2026 · Updated June 1, 2026 Written by ![Linus Ingemarsson - Co-Founder, Alice Labs at Alice Labs](/images/linus-ingemarsson.png) [Linus Ingemarsson](https://www.linkedin.com/in/linus-ingemarsson/) Co-Founder, Alice Labs Co-Founder at Alice Labs. Author of 7 research reports on AI adoption, governance and labor markets cited across EU, OECD and US benchmarks. - 8+ years in AI strategy & implementation - Top-5 AI Speaker, Sweden (Mindley 2025) - 100+ enterprise AI engagements [View profile](https://www.linkedin.com/in/linus-ingemarsson/) [](https://www.linkedin.com/in/linus-ingemarsson/)[](mailto:linus@alicelabs.ai) Reviewed by June 1, 2026 ![Eric Lundberg - Co-Founder, Alice Labs at Alice Labs](/images/eric-lundberg.png) [Eric Lundberg](https://www.linkedin.com/in/eric-lundberg-3530451bb/) Co-Founder, Alice Labs Co-Founder at Alice Labs. Builds AI automation, agent workflows and integration systems that hold up in real business operations. - AI automation & agent systems lead - Workflow design across 100+ deployments - Specialist in RAG, integrations & APIs [View profile](https://www.linkedin.com/in/eric-lundberg-3530451bb/) [](https://www.linkedin.com/in/eric-lundberg-3530451bb/)[](mailto:eric@alicelabs.ai) Published April 15, 2026 · Updated June 1, 2026 Reviewed for technical accuracy, methodology and source integrity. · All claims trace to public sources cited in-line. ## Frequently Asked Questions ### How long does an enterprise AI strategy take to build? 6–8 weeks for the strategy itself (Steps 1–4). A further 3–6 months to get the first pilots to production (Steps 5–6). Full portfolio maturity is a 12–24 month journey. ### Who should own enterprise AI strategy? Ownership works best at Chief Digital Officer, Chief Data Officer, or Chief Technology Officer level, with an explicit mandate from the CEO or COO. A dedicated AI lead (often a Head of AI or Director of AI) runs day-to-day. Avoid putting strategy under a single business function — it won't cross-functional. ### How do I prioritize AI use cases? Score every candidate on two axes: business impact (€ value + strategic importance) and feasibility (data availability + technical complexity + change-management effort). Plot on a 2x2 matrix. Prioritize high-impact + high-feasibility. Park high-impact + low-feasibility for the next planning cycle. ### Build or buy AI? Most mature programs are 70% buy (SaaS AI products + foundation models via API) and 30% build (proprietary data, differentiated workflows). Use a five-factor scoring matrix: strategic differentiation, data proprietary-ness, time-to-value, 3-year TCO, and in-house capability. Default to buy unless two or more factors score strongly toward build. ### What does enterprise AI strategy cost? Strategy phase: €25,000–€150,000 depending on scope (single function vs enterprise-wide). First-pilot cost: €50,000–€500,000 depending on complexity. At-scale production: €500,000–€5M per year across the portfolio for mid-market; substantially higher for global enterprises. ### When do EU AI Act obligations apply? The Act entered into force 1 August 2024. Unacceptable-risk prohibitions applied from 2 February 2025. General-purpose AI model obligations applied from 2 August 2025. High-risk AI system obligations apply from 2 August 2026 (with a longer transition for systems already on the market). Plan Step 3 around the 2026 date for high-risk systems. ### What is the biggest reason enterprise AI strategies fail? Poor use case selection. Gartner, McKinsey and BCG all report that spreading investment across too many low-impact use cases is the primary cause of underwhelming ROI. Top-quartile companies concentrate spend on 3–5 high-impact use cases rather than running 20 small pilots. ### Want to discuss how this applies to your organization? Book a free 30-minute strategy call with our AI team. [Book a call](/en/ai-consulting-services#contact-form) [Next in AI Strategy ### Build vs Buy AI: Decision Framework for 2026 ](/en/insights/build-vs-buy-ai) ## Further reading - [EU AI Act — Regulation (EU) 2024/1689 (official consolidated text)](https://eur-lex.europa.eu/eli/reg/2024/1689/oj)· eur-lex.europa.eu - [McKinsey — The state of AI (2025 annual report)](https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai)· mckinsey.com - [Eurostat — AI use in enterprises 2025 (DDN-20251211-2)](https://ec.europa.eu/eurostat/web/products-eurostat-news/w/ddn-20251211-2)· ec.europa.eu - [Stanford HAI — AI Index Report 2025](https://hai.stanford.edu/ai-index/2025-ai-index-report)· hai.stanford.edu ## Related services [AI Strategy Consulting Alice Labs' strategy engagement — the framework on this page, delivered. ](/en/ai-strategy)[AI Implementation Services Once strategy is done — scoped delivery from pilot through production. ](/en/ai-implementation) ## Related reading [deepdive ### Why AI Projects Fail: 7 Root Causes & How to Avoid Them Deep-dive on the failure patterns that kill most enterprise AI pilots. 10 min](/en/insights/why-ai-projects-fail) [data insight ### AI Adoption by Country 2026 Benchmark where you stand vs Eurostat, OECD, and Stanford HAI baselines. 10 min](/en/insights/ai-adoption-by-country-2026) [listicle ### Best AI Agent Frameworks 2026 Technology landscape for Steps 4–5 when use cases involve agents. 10 min ](/en/insights/best-ai-agent-frameworks-2026) ## Sources 1. [EU AI Act — Regulation (EU) 2024/1689 (OJ L, 12 July 2024)](https://eur-lex.europa.eu/eli/reg/2024/1689/oj)(accessed 2026-04-15) 2. [McKinsey & Company — The state of AI (2025 annual survey)](https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai)(accessed 2026-04-15) 3. [Eurostat — AI use in enterprises 2025 (DDN-20251211-2)](https://ec.europa.eu/eurostat/web/products-eurostat-news/w/ddn-20251211-2)(accessed 2026-04-15) 4. [Stanford HAI — AI Index Report 2025](https://hai.stanford.edu/ai-index/2025-ai-index-report)(accessed 2026-04-15) 5. [BCG — AI at Scale (2024 research series)](https://www.bcg.com/capabilities/artificial-intelligence)(accessed 2026-04-15) Next scheduled review: 2026-08-15 ![Linus Ingemarsson](/images/linus-ingemarsson.png)![Eric Lundberg](/images/eric-lundberg.png)![Alice Holmgren](/images/alice-holmgren.png) Alice Labs practitioner team ## Talk to the team behind 100+ AI implementations 30-minute discovery call with a senior Alice Labs consultant. No slide deck, no sales pitch — just a scoping conversation. [Book a Discovery Call](#contact) Share [](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Falicelabs.ai%2Fen%2Finsights%2Fenterprise-ai-strategy-framework)[](https://twitter.com/intent/tweet?url=https%3A%2F%2Falicelabs.ai%2Fen%2Finsights%2Fenterprise-ai-strategy-framework&text=Enterprise%20AI%20Strategy%3A%20The%20Alice%20Labs%206-Step%20Framework%20\(2026\)) ## Get in Touch! The lab usually responds within 24 hours. 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