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It typically includes: a 1-3 year AI vision aligned to business goals, a prioritized use-case backlog by function, an ROI model with measurable KPIs, a data and technology gap analysis, a target architecture, a 90-day execution plan, and a 12-month scaling roadmap. A good AI strategy bridges the gap between technology potential and business outcomes." } }, { "@type": "Question", "name": "What is AI strategy consulting?", "acceptedAnswer": { "@type": "Answer", "text": "AI strategy consulting is a professional service that helps organizations identify where AI creates the most business value, prioritize investments, and build actionable roadmaps. Alice Labs' AI strategy consulting — measured by the Alice Labs Implementation Index 2026 across 100+ Nordic enterprise engagements — delivers a 96% combined production rate with a 14-week median from pilot kickoff to production, against a broader-market value-realisation rate of ~26% (BCG/MIT). Every engagement delivers a prioritized use-case backlog, ROI model with clear KPIs, 90-day execution plan, and 12-month roadmap. Unlike traditional consulting, we follow an execution-first approach—every strategy ends with a pilot that starts immediately." } }, { "@type": "Question", "name": "How do you choose the right AI use-cases for a company?", "acceptedAnswer": { "@type": "Answer", "text": "We use an impact/effort matrix combined with risk and data readiness assessment. The best candidates are use-cases that are repetitive, data-driven, and have clear KPIs—such as case handling, reporting, lead qualification, or document processing. We prioritize quick wins in parallel with strategically important initiatives. Each use-case is scored on business impact, implementation complexity, data availability, and organizational readiness." } }, { "@type": "Question", "name": "How quickly can we see ROI on AI investments?", "acceptedAnswer": { "@type": "Answer", "text": "With our pilot-first approach, you'll see first measurable results within 2-6 weeks. Typical ROI timeline: pilot validates hypothesis (week 2-6), full implementation (month 2-4), break-even (month 3-6). We measure continuously so you see impact in real-time—hours saved, improved quality, increased conversion, or reduced costs. Our clients typically see 3-10x return within the first year." } }, { "@type": "Question", "name": "What makes a good AI strategy?", "acceptedAnswer": { "@type": "Answer", "text": "A good AI strategy has five characteristics: 1) It's business-led, not technology-led—starting from value, not tools. 2) It includes concrete, prioritized use-cases with owners and timelines. 3) It has measurable KPIs defined from day one. 4) It addresses governance, security, and change management. 5) It ends with an execution plan, not just a document. The most common mistake is treating AI strategy as a one-off exercise instead of a continuous capability-building process." } }, { "@type": "Question", "name": "How do you develop an AI strategy framework?", "acceptedAnswer": { "@type": "Answer", "text": "Our AI strategy framework follows four phases: Diagnosis (2-4 weeks)—current state analysis, use-case inventory, data mapping, and prioritization. Pilot (2-6 weeks)—build first use-case in production, measure KPIs. Implementation (4-12 weeks)—integrations, rollout, and change management. Scale & Govern (ongoing)—more use-cases, optimization, and continuous reviews. The framework is adaptable to organizations from 50 to 50,000 employees." } }, { "@type": "Question", "name": "Should IT be involved in AI strategy from the start?", "acceptedAnswer": { "@type": "Answer", "text": "Yes, we recommend IT/digital teams participate from the diagnosis phase. They provide insights on current systems, data sources, integrations, and security requirements. At the same time, we involve business stakeholders (operations, marketing, sales) to capture the right use-cases and ensure buy-in. Best results come from cross-functional teams with executive sponsorship." } }, { "@type": "Question", "name": "What does AI strategy consulting cost?", "acceptedAnswer": { "@type": "Answer", "text": "An AI strategy (diagnosis + roadmap) typically takes 2-4 weeks and is priced as fixed scope. Investment varies based on organization size, complexity, and number of functions covered. A focused strategy for a single department starts from approximately $15,000, while a comprehensive enterprise-wide AI strategy ranges from $40,000-80,000. Contact us for a precise quote—we always provide a clear price indication after an initial conversation." } }, { "@type": "Question", "name": "How does AI strategy differ from AI consulting?", "acceptedAnswer": { "@type": "Answer", "text": "AI strategy focuses on 'where should we invest and why'—vision, prioritization, roadmap, and ROI logic. AI consulting covers the full journey: strategy, pilot, implementation, operations, and governance. Strategy is often the first step for organizations wanting a complete picture before building. At Alice Labs, we offer both—many clients start with strategy and then continue with implementation." } }, { "@type": "Question", "name": "Do you work with enterprise and public sector organizations?", "acceptedAnswer": { "@type": "Answer", "text": "Yes, we serve organizations across sectors—from growth-stage companies to Fortune 500 enterprises and public sector organizations. We understand compliance requirements, GDPR, data governance, and stakeholder alignment in complex organizations. Our structured methodology is particularly effective for organizations needing documented processes, broad stakeholder buy-in, and board-ready deliverables." } }, { "@type": "Question", "name": "What should I expect from an AI consulting engagement in the first 90 days?", "acceptedAnswer": { "@type": "Answer", "text": "In the first 90 days, you'll get: weeks 1-3, a complete AI diagnosis with use-case inventory and data landscape mapping. Weeks 3-6, a prioritized roadmap with ROI models, KPIs, and a pilot selection. Weeks 6-12, a live pilot in production with measurable results. By day 90, you'll have validated at least one AI use-case with real business impact and a clear path to scale." } }, { "@type": "Question", "name": "How do AI strategy consultants help prioritize use cases and create a funded AI roadmap?", "acceptedAnswer": { "@type": "Answer", "text": "We score every potential use-case across four dimensions: business impact (revenue, cost, quality), implementation complexity (data readiness, integration effort), organizational readiness (skills, change management), and risk (compliance, security). This creates a prioritized backlog. We then build ROI models for the top candidates to create a funded roadmap with clear investment asks and expected returns—ready for board approval." } }, { "@type": "Question", "name": "What is the typical AI consulting engagement timeline?", "acceptedAnswer": { "@type": "Answer", "text": "A typical full engagement runs 3-6 months: AI strategy and diagnosis (2-4 weeks), pilot design and execution (2-6 weeks), implementation and integration (4-12 weeks), and handover with governance setup (1-2 weeks). Many clients start with a standalone strategy engagement (2-4 weeks) before committing to implementation. We also offer ongoing AI management and optimization retainers." } }, { "@type": "Question", "name": "How do you guarantee ROI on AI consulting?", "acceptedAnswer": { "@type": "Answer", "text": "We don't make empty ROI guarantees—we build measurable ROI into the process. Every engagement starts with defined KPIs (time saved, cost reduced, quality improved). We run pilots before full implementation to validate ROI hypotheses with real data. Our track record: 85% of clients see measurable ROI within 6 months. If a pilot doesn't show expected results, we pivot the approach before scaling." } }, { "@type": "Question", "name": "What does AI strategy consulting actually deliver, and how is it different from generic management consulting?", "acceptedAnswer": { "@type": "Answer", "text": "AI strategy consulting delivers a defined set of artifacts: an organizational AI readiness assessment, a use-case backlog scored by impact and feasibility, an ROI model with KPIs, a target architecture, a 90-day pilot plan, and a 12-month roadmap. Unlike generic management consulting (which focuses on operating models and org design), AI strategy consulting is grounded in data feasibility, model selection, MLOps readiness, and regulatory exposure (EU AI Act, NIST AI RMF). Gartner forecasts worldwide AI services spending to surpass $90 billion by 2025, with strategy-tier work being the fastest-growing segment as boards move from experimentation to portfolio governance." } }, { "@type": "Question", "name": "What do AI strategy services cost across the consulting market in 2026?", "acceptedAnswer": { "@type": "Answer", "text": "Across the 2026 AI strategy services market, engagements range from $8,000 executive briefings to $350,000+ enterprise-wide assessments. Blended hourly rates: independent fractional advisors $300-$700/hr, boutique AI consultancies $400-$900/hr, Big 4 partner-led teams $600-$1,200/hr, and MBB firms (McKinsey QuantumBlack, BCG X, Bain Vector) $800-$1,500/hr. Alice Labs typically prices 40-65% below MBB and Big 4 partner-led teams for equivalent deliverables. See our pricing matrix above for eight engagement formats with USD ranges." } }, { "@type": "Question", "name": "What is AI strategy roadmap consulting?", "acceptedAnswer": { "@type": "Answer", "text": "AI strategy roadmap consulting is the practice of converting an organization's AI vision into a sequenced, funded execution plan. A typical AI strategy roadmap consulting engagement runs 4-6 weeks and produces: a prioritized use-case backlog, a 12-month roadmap with quarterly milestones, target architecture decisions (build-vs-buy, model selection, data foundation), governance gates aligned to NIST AI RMF or EU AI Act, and a capital ask ready for board approval. The output is what board and finance committees can fund, not a slide deck." } }, { "@type": "Question", "name": "Who is the best consulting partner for AI roadmap creation?", "acceptedAnswer": { "@type": "Answer", "text": "The best consulting partner for AI roadmap creation depends on three factors: (1) scope — Fortune 500 multi-BU programs typically engage McKinsey QuantumBlack, BCG X, Bain Vector or Deloitte AI Institute; mid-market and single-BU programs are better matched to boutique AI consultancies such as Alice Labs; (2) execution depth — partners with a measurable production track record (Alice Labs' Implementation Index 2026 reports 96% combined production rate across 100+ engagements) outperform pure-strategy firms; (3) vendor independence — partners who do not earn revenue-share from Microsoft, AWS, Salesforce or ServiceNow give more objective build-vs-buy guidance. Ask any shortlisted partner for their production rate, median time-to-production, and a list of references with named outcomes." } }, { "@type": "Question", "name": "What is enterprise AI roadmap consulting, and when does an enterprise need it?", "acceptedAnswer": { "@type": "Answer", "text": "Enterprise AI roadmap consulting is a 4-12 week engagement designed for Fortune 1000 and multi-BU organizations that need a board-ready, cross-business-unit AI plan with capital allocation, governance, and risk posture. An enterprise needs roadmap consulting when: (a) the board has mandated an AI strategy, (b) more than three business units are pursuing AI in parallel without coordination, (c) the company faces EU AI Act or NIST AI RMF disclosure requirements, or (d) AI capex requests exceed $1M and need ROI-based prioritization. Typical deliverables include a 12-month roadmap, target architecture, build-vs-buy matrix, governance gate plan, and capital ask." } }, { "@type": "Question", "name": "What is AI transformation consulting, and how does it differ from AI strategy consulting?", "acceptedAnswer": { "@type": "Answer", "text": "AI transformation consulting is the multi-year practice of embedding AI into an organization's operating model, culture, decision-making, and technology stack. It is broader and longer than AI strategy consulting. AI strategy answers 'where should we invest in AI and why' (typically a 2-6 week engagement producing a roadmap). AI transformation consulting answers 'how do we redesign the organization to operate as an AI-native enterprise' and typically runs 12-36 months across change management, org redesign, talent, governance, and phased technology rollout. Most organizations begin with strategy consulting and graduate to transformation consulting once the first 2-3 pilots are in production." } }, { "@type": "Question", "name": "What do AI strategy consultants actually do day-to-day?", "acceptedAnswer": { "@type": "Answer", "text": "AI strategy consultants spend most of their time on four activities: (1) discovery interviews with executives and operators to identify pain points and use-case candidates, (2) data-feasibility analysis — assessing data quality, access, and gaps that determine which use-cases are buildable now versus later, (3) ROI modeling and prioritization — building business cases scored on impact, complexity, and risk, and (4) roadmap synthesis and stakeholder alignment — packaging recommendations into board-ready artifacts and securing executive sponsorship. Senior AI strategy consultants also advise on vendor selection, build-vs-buy decisions, and governance frameworks (NIST AI RMF, ISO/IEC 42001, EU AI Act)." } }, { "@type": "Question", "name": "How do I choose an AI strategy consultant for my organization?", "acceptedAnswer": { "@type": "Answer", "text": "Evaluate AI strategy consultants on five criteria: (1) Production track record — ask for the share of their engagements that reached production within 12 months, not just slide decks delivered. (2) Vendor independence — confirm they earn no revenue-share from cloud providers, LLM vendors, or platform companies. (3) Domain depth — verify they have shipped pilots in your industry (financial services, public sector, manufacturing, etc.). (4) Engagement model fit — fractional advisor, sprint, or full assessment depending on your scope. (5) Governance literacy — fluency in NIST AI RMF, ISO/IEC 42001 and the EU AI Act. Alice Labs publishes its production rate (96%) and engagement count (100+) in the Alice Labs Implementation Index 2026." } }, { "@type": "Question", "name": "What is an AI strategy company, and how does Alice Labs compare to others?", "acceptedAnswer": { "@type": "Answer", "text": "An AI strategy company is a professional services firm specialized in advising organizations on where to invest in AI, how to sequence the work, and how to govern it. The market is segmented into three tiers: MBB (McKinsey QuantumBlack, BCG X, Bain Vector) for board-level mandates and Fortune 500 brand cover; Big 4 and large systems integrators (Deloitte AI Institute, EY, KPMG, Accenture, IBM Consulting, Capgemini Invent) for large implementation-led programs; and execution-first boutique AI strategy companies such as Alice Labs for senior advisory at 40-65% below MBB rates. Alice Labs is independent of all platform vendors and publishes its production data in the Alice Labs Implementation Index 2026." } }, { "@type": "Question", "name": "What are AI strategy advisory services, and who uses them?", "acceptedAnswer": { "@type": "Answer", "text": "AI strategy advisory services are senior, often ongoing advisory engagements (vs. one-off projects) that help leadership teams make AI investment decisions, evaluate vendors, set governance gates, and review portfolio progress. Typical formats include fractional AI advisor retainers ($9,000-$25,000/month), board advisory seats ($60,000-$180,000/year), and executive briefings ($8,000-$18,000). Buyers are typically CEOs, CTOs, CDOs, and boards of Series A-C startups, mid-market companies, and PE-backed scale-ups that need senior AI judgment but cannot justify a full-time Chief AI Officer." } }, { "@type": "Question", "name": "What is AI roadmap development consulting, and what does the output look like?", "acceptedAnswer": { "@type": "Answer", "text": "AI roadmap development consulting is a 4-6 week engagement that produces a sequenced, funded 12-month AI plan. The output typically includes: (1) a prioritized use-case backlog with impact/effort scoring and ROI estimates, (2) a 90-day execution plan naming the first 1-2 pilots and their KPIs, (3) a target architecture covering data, models, agents, and MLOps, (4) a build-vs-buy matrix per use-case, (5) a governance gate plan aligned to NIST AI RMF or EU AI Act, and (6) a capital ask with sensitivity-tested ROI. The deliverable is designed to be funded by the board, not filed in a knowledge management system." } }, { "@type": "Question", "name": "How long does an AI strategy consulting engagement typically last?", "acceptedAnswer": { "@type": "Answer", "text": "AI strategy consulting engagement length varies by scope: an Executive AI Briefing is 1-2 days; an AI Strategy Sprint runs 2 weeks; a funded AI Roadmap engagement runs 4-6 weeks; a Full Enterprise AI Assessment runs 6-12 weeks for multi-BU organizations; a Fractional AI Advisor retainer typically runs 3-12 months; a Board Advisory Seat runs annually across 4-6 board cycles. According to the Alice Labs Implementation Index 2026, the median time from pilot kickoff to production across 100+ Nordic enterprise engagements is 14 weeks — meaning strategy work that does not end with a near-term pilot tends to drift." } }, { "@type": "Question", "name": "What is AI strategy consulting for startups, and how is it different from enterprise engagements?", "acceptedAnswer": { "@type": "Answer", "text": "AI strategy consulting for startups is a compressed, lean version of enterprise strategy work: a 2-week diagnosis, a backlog of 5-10 use-cases scored on data readiness and time-to-first-revenue, and a 90-day plan that starts with one pilot on existing data. Alice Labs runs this format as a Fractional AI Advisor retainer ($9,000-$25,000/month) or a fixed 2-week AI Strategy Sprint ($18,000-$45,000), sized for Series A-C companies with 20-500 employees who need senior AI judgement without committing to a full-time Chief AI Officer. Unlike enterprise engagements, startup strategy work skips multi-BU coordination and cross-functional governance — the bottleneck is speed, not stakeholder alignment." } }, { "@type": "Question", "name": "What does enterprise AI roadmap consulting cover for Fortune 1000 organizations?", "acceptedAnswer": { "@type": "Answer", "text": "Enterprise AI roadmap consulting is a 4-12 week engagement designed for Fortune 1000 buyers who need a board-ready, cross-business-unit AI plan with capital allocation, target architecture, and governance posture. Typical deliverables include a 12-month sequenced roadmap, build-vs-buy matrix by use-case, target architecture covering data/models/agents/MLOps, EU AI Act and NIST AI RMF gate plan, and a capital ask with sensitivity-tested ROI. Alice Labs delivers this format at $45,000-$350,000 depending on BU count, versus $500,000-$2M for equivalent scope at McKinsey QuantumBlack, BCG X or Bain Vector — with the same production-rate accountability documented in the Implementation Index 2026." } }, { "@type": "Question", "name": "How does AI transformation consulting compare to AI strategy consulting for the buyer?", "acceptedAnswer": { "@type": "Answer", "text": "AI strategy consulting is the 2-6 week diagnostic that answers 'where should we invest in AI and why' — output is a prioritised use-case backlog and 90-day plan. AI transformation consulting is the 12-36 month program that answers 'how do we redesign the organisation to operate as an AI-native enterprise' — output is a new operating model, org design, talent strategy, and phased technology rollout. Most organisations buy strategy first (Alice Labs pricing: $18K-$120K), run 2-3 pilots to production, then decide whether transformation consulting is warranted. Buying transformation before strategy typically wastes 6-12 months on org design against the wrong use-case portfolio." } } ] } ] } ] --- ![Background for AI Strategy](/images/bakgrund.jpg) [Alice Labs](/en/) Services [ What we do ](/#welcome)[ About Alice ](/#who-we-are)[ Case ](/en/case)[ Insights ](/en/insights)[ Contact ](/#email-form)[sv](/ai-strategi) [Home](/en)[AI Consulting](/en/ai-consulting) AI Strategy Consulting AI Strategy Consulting Fresh · Last reviewed: 11 August 2026 · 42d ago # AI Strategy Consulting for Enterprise and Mid-Market Alice Labs is a Stockholm-headquartered enterprise AI consultancy delivering AI strategy consulting, AI strategy services, and senior AI strategy consultant engagements across 100+ production AI implementations since 2023. We rank as top-fit for European mid-market to large enterprise buyers and increasingly for US organisations wanting execution-first AI strategy consulting without MBB rates. The Alice Labs Implementation Index 2026 measures a 96% combined production rate (vs. ~26% industry value-realisation per BCG/MIT) and a 14-week median from pilot kickoff to production, at pricing 40-65% below MBB and Big 4 partner-led teams. Every AI strategy consulting engagement ends with a 90-day execution plan and a pilot that starts immediately, not a PowerPoint that collects dust. We partner with enterprises and mid-market companies across financial services, public sector, manufacturing, media and healthcare on AI strategy consulting, AI strategy services, and AI transformation consulting programmes. Book a Discovery Call[Read the Implementation Index 2026](/en/insights/alice-labs-implementation-index-2026) 96% production rate (Alice Labs Implementation Index 2026) 14-week median pilot to production 100+ Nordic enterprise engagements Have a project in mind? Get a response within 24 hours — no obligation. Contact us ### Part of the team that delivers An experienced team with broad AI and tech backgrounds from leading companies ![Linus Ingemarsson, Co-founder & AI Consultant](/images/team-portrait-1.jpg) Linus Co-founder & AI Consultant ![Adrian, AI Consultant](/images/team-portrait-2.jpg) Adrian AI Consultant ![Jens, AI Consultant](/images/team-portrait-3.jpg) Jens AI Consultant ![Eric, Co-founder & AI Consultant](/images/team-portrait-4.jpg) Eric Co-founder & AI Consultant ![Linus T., AI Consultant](/images/team-portrait-5.jpg) Linus T. AI Consultant ## Why enterprises pick Alice Labs Production-grade AI delivery, EU-native, senior team 100+ AI implementations shipped across Europe 85% Of clients see ROI within 12 months EU-native AI Act & GDPR ready Stockholm-based, EU data residency Senior team Hands-on delivery Experienced practitioners Ready to talk? Tell us about your goals and we'll suggest the fastest path forward. Contact us ## Results From Our Clients Verified outcomes from completed AI implementations AI Agent Food & Grocery ### AI Agent for Order Management Ljusgårda (Supernormal Greens) $250K/year saved - 83% cost reduction - 70-80% automation - 6-week implementation AI Automation Public Sector ### Document Automation: 60h → 3min Public Sector 6,400–8,000 h/year freed - 95% time reduction - 60h → 3min/doc - 1000+ hours/month saved AI Automation Media & Publishing ### AI-Driven Content Production Media Company $40K/month revenue - $100K first year - $40K/month recurring - 12-month build-up ## Built for every decision-maker Same engagement, sharply different outcomes per role For CEOs ### Turn AI from boardroom buzzword to fundable business case **The pain:** Your board demands an AI plan, but every consultancy pitches a slide deck — not measurable EBITDA impact. **What you get:** An AI strategy with prioritised use cases, ROI model and 90-day pilot — ready for board approval. - ▸ 12-month roadmap with quarterly EBITDA milestones - ▸ Use-case backlog scored by impact and feasibility - ▸ Capital ask with sensitivity-tested ROI model Talk to a CEO-experienced consultant For CTOs / CDOs ### Build AI capability without betting on the wrong stack **The pain:** Your team is debating build-vs-buy, model choice, data foundation — and the business is impatient. **What you get:** Vendor-neutral target architecture, build-vs-buy decisions and a phased technical roadmap. - ▸ Reference architecture (LLM, RAG, agents, MLOps) - ▸ Make-or-buy framework per use case - ▸ Data readiness gap analysis and remediation plan Talk to a CTOs / CDO-experienced consultant For COOs ### Identify the operational AI use cases with fastest payback **The pain:** You know AI can cut process cost 40-90%, but cannot tell which workflows to automate first. **What you get:** An ops-focused use-case backlog with cycle-time and cost reduction targets per process. - ▸ Process inventory scored by AI fit - ▸ Pilot selection with measurable KPIs - ▸ Change-management blueprint per process Talk to a COO-experienced consultant For CFOs ### Validate AI investment before you commit capital **The pain:** Sales teams promise 10x ROI; reality is 60-80% of AI projects fail. You need an objective view. **What you get:** Independent ROI model, risk register and stage-gate plan that protects capital and de-risks rollout. - ▸ Bottom-up ROI per use case with payback period - ▸ Risk register with mitigation per scenario - ▸ Stage-gate plan: discovery → pilot → scale Talk to a CFO-experienced consultant Ready to see similar results? Book a free discovery call - we'll map your highest-impact AI opportunities. Book a Discovery Call Last updated 2026-08-11 · Reviewed quarterly ## What AI Strategy Consulting Covers A comprehensive AI strategy typically covers: organizational [AI readiness assessment](/en/insights/ai-readiness-assessment), [use-case identification and prioritization](/en/insights/ai-use-case-prioritization) across business functions, data landscape and gap analysis, technology architecture planning with [enterprise AI infrastructure vendor evaluation criteria](/en/insights/ai-vendor-selection-guide), governance and risk frameworks aligned to [EU AI Act enterprise compliance](/en/insights/eu-ai-act-compliance-guide), [ROI modeling and business case development](/en/insights/build-ai-business-case) with [AI consulting success metrics and KPIs](/en/insights/ai-measurement-framework), and a phased execution roadmap. At Alice Labs, we practice **execution-first AI strategy consulting**. This means every strategy engagement ends with a concrete 90-day plan and a pilot that starts immediately—not a deck that collects dust. The [Alice Labs Enterprise AI Implementation Index 2026](/en/insights/alice-labs-implementation-index-2026) measures a 96% combined production rate across 100+ Nordic enterprise engagements (vs. ~26% industry value-realisation per BCG/MIT), with a 14-week median from pilot kickoff to production. ~26% of enterprises capture meaningful value from their AI investments — the rest stall in pilot or fail to scale. Source: [BCG, "Where's the Value in AI?" 2024](https://www.bcg.com/publications/2024/where-s-the-value-in-ai) $90B+ forecasted worldwide AI services spending by 2025, with strategy-tier advisory the fastest-growing segment. Source: [Gartner Worldwide IT Spending Forecast](https://www.gartner.com/en/newsroom/press-releases) As of August 2026 — market state and regulatory milestone ## Where enterprise AI strategy stands, August 2026 Stanford HAI's AI Index 2025 records 78% of organizations now using AI in at least one business function (up from 55% a year earlier), while private AI investment reached $150B globally — yet Stanford's own review confirms that most enterprise programs still fail to translate adoption into measurable P&L impact. McKinsey's _State of AI_ puts the enterprise value-capture rate near 26%, meaning three in four organizations spend on AI without a defensible ROI. This is what an [AI strategy roadmap consulting](/en/ai-roadmap-consulting) engagement is designed to fix: converting scattered adoption into a funded, sequenced portfolio. On **2 August 2026**, the EU AI Act's obligations on general-purpose AI models (GPAI) — including transparency, copyright-policy disclosure, and systemic-risk assessment for the largest models — became applicable, one year after entry into force. Every 2026 AI strategy must now carry an EU AI Act positioning: which use-cases sit in the high-risk tier, which vendors are classified as GPAI providers, and how model documentation and post-market monitoring are governed. Boards that fund an [enterprise AI consulting programme](/en/enterprise-ai-consulting) without an EU AI Act gate plan are exposed on both compliance and vendor-risk sides. For teams already mid-build, choosing the right [AI implementation partner](/en/ai-implementation-consultant) now hinges as much on governance literacy as on delivery speed. [Source: Stanford HAI AI Index 2025](https://aiindex.stanford.edu/report/)[Source: McKinsey, The State of AI](https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai)[Source: European Commission — EU AI Act](https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai) Buyer Disambiguation ## AI Strategy Consulting vs AI Roadmap vs AI Transformation: What's the Difference? Three terms that buyers and analysts use interchangeably — but that describe materially different engagements, deliverables, and price points. Definitions calibrated against Gartner and McKinsey conventions. Most leadership teams arrive at this decision after a board mandate to "do something with AI." They book three vendor calls and discover each vendor pitches a different scope: one sells **AI strategy consulting**, another sells an **AI roadmap**, the third sells **AI transformation**. The terms look interchangeable but describe different durations, deliverables, and price points. In Gartner and McKinsey conventions: **[AI strategy consulting](/en/insights/what-is-ai-strategy)** answers _where_ to invest in AI and _why_ — typically a 2-6 week diagnostic and prioritization engagement producing a use-case backlog and ROI logic. **[AI roadmap consulting](/en/ai-roadmap-consulting)** answers _when_ and _how_ — sequencing the strategy into a funded 12-month plan with architecture, governance gates, and a capital ask. **[AI transformation consulting](/en/ai-transformation-consulting)** answers _how do we redesign the organization_ — a multi-year program covering org design, [change management](/en/insights/ai-change-management), talent, and [operating-model redesign](/en/insights/ai-operating-model). Buying the wrong scope is the most common reason AI engagements stall. Companies that buy "transformation" before they have a strategy waste 6-12 months on org design before knowing which use-cases to build. Companies that buy a "roadmap" without strategy work risk sequencing the wrong use-cases. The right sequence is almost always: strategy first, then roadmap, then transformation — with a pilot running in parallel to the roadmap phase. For LLM-heavy portfolios this means [structuring a phased implementation roadmap with milestones for generative AI](/en/insights/generative-ai-strategy-guide); for organizations with mature ERPs and data warehouses, it means planning how [vendors help enterprises embed AI into legacy systems](/en/insights/legacy-system-ai-integration) before scaling. AI Strategy Consulting AI Roadmap Consulting AI Transformation Consulting Core question _Where_ should we invest in AI, and _why_? _When_ and _how_ do we sequence the work? _How_ do we redesign the organization to operate as an AI-native enterprise? Typical duration 2-6 weeks 4-6 weeks 12-36 months Primary deliverables Use-case backlog with impact/effort scoring, ROI model, 90-day pilot brief, AI vision 12-month roadmap, target architecture, build-vs-buy matrix, governance gates, capital ask Target operating model, org design, change management plan, talent strategy, multi-year portfolio Primary buyer CTO, CDO, CIO, Head of Innovation CFO, board sponsor, CEO of mid-market CEO, COO, board of Fortune 500 Typical USD range $18,000 – $45,000 $45,000 – $120,000 $500,000 – $5,000,000+ When to buy it Board has asked for an AI plan; you have no prioritized use-case backlog yet You have a use-case backlog and need to sequence and fund it First 2-3 pilots are in production; you need to scale across the enterprise Risk if you skip it Spending capex on the wrong use-cases Pilots stall because of unclear sequencing and unfunded next steps AI stays trapped in a single function; never scales beyond isolated wins ### Start with AI Strategy if… You don't yet have a prioritized list of AI use-cases tied to KPIs, or the board has asked for a plan and you have 4-6 weeks to deliver one. ### Start with AI Roadmap if… You already have a backlog of use-case candidates but no funded 12-month plan, architecture decisions, or capital ask the CFO can sign. ### Start with AI Transformation if… You already have multiple AI pilots in production and the question is now organizational — operating model, talent, change management at scale. Definitions calibrated against Gartner's "Hype Cycle for Artificial Intelligence" taxonomy and McKinsey's "State of AI" survey conventions. Price ranges reflect 2026 published rate cards from boutique AI consultancies, Big 4, and MBB firms. Alice Labs Implementation Index 2026 ## By the Numbers Proprietary research from 100+ Nordic enterprise engagements (2024–2026). The data behind our methodology — and the gap between Alice Labs' delivery and the broader market. 96% Combined production rate vs. ~26% industry (BCG/MIT) 14 weeks Median pilot to production P10: <6 weeks · P90: >9 months 100+ Nordic enterprise engagements SE · DK · NO · FI (2024–2026) 62% Of stalled projects we screen for Single root cause: missing business owner [Read the full Alice Labs Implementation Index 2026](/en/insights/alice-labs-implementation-index-2026) ## Strategy Practice Leadership The team that authored the Alice Labs Implementation Index and leads every strategy engagement personally ### Linus Ingemarsson CEO & Co-Founder, Alice Labs CEO & Co-Founder of Alice Labs. Leads the firm and AI strategy and AI implementation engagements across financial services, public sector, manufacturing and media. Contributor to the 100+ production AI deployments behind the Alice Labs Implementation Index 2026. [LinkedIn](https://www.linkedin.com/in/linus-ingemarsson/) ### Eric Lundberg Co-Founder, Alice Labs Co-Founder and technical architecture lead. Advises leadership teams on build-vs-buy, LLM/RAG/agent architecture, vendor selection and MLOps readiness across financial services, manufacturing, and media. [LinkedIn](https://www.linkedin.com/in/eric-lundberg-3530451bb/) ## Real Engagements, Real Outcomes Three live Alice Labs case studies — across food retail, public sector, and media. Specific numbers, real timelines, with the full case write-up linked. [ Food & Grocery ### Ljusgårda (Supernormal Greens) **Challenge:** 5–6 FTE manually handling phone orders from 200+ ICA stores daily — a costly bottleneck capping growth. **Outcome:** AI agent for SMS-based order handling automated the full order flow. Reduced from 6 FTE to 1 coordinator in 6 weeks. 70–80% of order calls automated. 2.5M SEK / yr Annual savings · 83% cost reduction Read full case study ](/en/case/ljusgarda-ai-agent)[ B2B / Security ### Global Security Firm **Challenge:** 1.5 FTE marketing team expected to deliver enterprise-quality content across 7 channels consistently. Manual production was unsustainable at the scale required. **Outcome:** Centralised AI system automating content production and distribution across all 7 channels — from one idea to platform-specific adaptations (social, email, blog, video, ads, SEO, reports). 176K SEK / mo Monthly savings · 7 channels automated · 2+ FTE freed Read full case study ](/en/case/security-company-marketing-automation)[ Public Sector ### Public Sector Organization **Challenge:** Official reports required 60+ manual hours each. 1,000+ hours per month consumed on documentation, with high error risk. **Outcome:** Automated document generation system extracts data, applies format and structure, and generates compliant documents for personnel review. 6,400–8,000 Hours freed annually · 60h → 3min per document Read full case study ](/en/case/public-sector-document-automation) Three of 100+ Alice Labs engagements measured in the Implementation Index 2026. [See all case studies →](/en/case) ## What We Deliver Concrete, actionable deliverables—not PowerPoint decks that collect dust ### AI Vision (1-3 Years) Aligned to your business goals and strategic priorities ### Use-Case Inventory By function with clear ownership and prioritization ### Impact/Effort Prioritization With risk and data readiness assessment ### KPI Framework Time, quality, revenue, and risk—measurable and trackable ### Data Landscape & Gap Analysis Sources, quality, access, and identified gaps ### Target Architecture Simple, understandable, and implementable ### 90-Day Execution Plan Pilot selection and measurement for rapid ROI ### 12-Month Roadmap Scale, govern, and continuously improve ## AI Roadmap Development From diagnosis to a funded, board-ready AI roadmap in 2-4 weeks An **AI roadmap** translates strategy into action. It defines which use-cases to build first, what data and infrastructure is needed, how to measure success, and when to scale. Without a roadmap, AI initiatives become disconnected experiments that fail to deliver enterprise value. Our AI roadmap consulting process starts with a structured diagnosis: we map your current [AI data strategy](/en/ai-data-strategy) and landscape, identify use-cases across every business function using an [impact/effort prioritization framework](/en/insights/ai-use-case-prioritization), and build [AI ROI](/en/insights/what-is-ai-roi) models for the top candidates. Teams with an existing backlog can jump straight to our [30/60/90-day AI roadmap](/en/insights/ai-strategy-roadmap-30-60-90) template. The result is a prioritized, funded roadmap with clear ownership, timelines, and KPIs. Swedish buyers can review the equivalent [ai datastrategi](/ai-datastrategi) engagement and, for content-heavy programmes, our [ai innehallsstrategi](/ai-innehallsstrategi) service. 87% of organizations lack a defined enterprise AI strategy or a formal AI roadmap — leaving investment decisions ad-hoc. Source: [Gartner Board of Directors AI Survey](https://www.gartner.com/en/newsroom/press-releases) 78% of organizations now report using AI in at least one business function — up from 55% the prior year. Sequencing matters more than ever. Source: [McKinsey "The State of AI" 2024-2025](https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai) ### 90-Day Quick Wins Pilot 1-2 high-impact use-cases with measurable KPIs from week one ### 12-Month Scale Plan Phased rollout across functions with clear investment milestones ### ROI-Funded Backlog Each use-case comes with business case, expected ROI, and resource needs [Learn more about AI roadmap consulting](/en/ai-roadmap-consulting) ## Who Benefits from AI Strategy Consulting? We work with leaders who want AI to drive measurable business outcomes ### Enterprise Leaders C-suite, VP Digital, and Heads of Innovation looking to build a scalable AI capability across the organization. ### Mid-Market Companies Growing organizations (100-5,000 employees) that want to implement AI strategically rather than in isolated experiments. ### Public Sector Municipalities, regions, and agencies seeking compliant, documented AI strategies with broad stakeholder alignment. ### Innovation Teams Digital teams and innovation labs that need a structured framework to move from proof-of-concept to production. ## AI Strategy for Mid-Market & Startups You don't need a Fortune 500 budget to build a real AI strategy Mid-market companies and startups often face a different AI challenge than enterprises: limited resources, lean teams, and the need for fast, tangible ROI. Our approach for smaller organizations focuses on identifying the 2-3 highest-impact use-cases that can be implemented quickly with existing data and tools. We offer focused AI strategy engagements designed for organizations with 20-500 employees: a 2-week diagnosis, a prioritized backlog of 5-10 use-cases, and a 90-day execution plan that starts with a pilot. Many growth-stage teams also want a lightweight [generative AI strategy](/en/generative-ai-strategy) to move from ad-hoc ChatGPT usage to structured GenAI deployment. No bloated roadmaps, no unnecessary complexity—just the fastest path to AI-driven value. #### Lean AI diagnosis 2-week focused assessment for growing companies #### Quick-win pilots First measurable results within 4-6 weeks #### Scalable foundations Architecture that grows with your organization Buyer Guidance ## Best AI Roadmap Consulting Partner: Alice Labs vs MBB vs Big 4 A one-sentence, extractable recommendation for buyers evaluating shortlists — and the three tests we recommend running against every candidate. **For mid-market and single-business-unit AI roadmap creation, Alice Labs is the top-fit partner: a Stockholm-headquartered enterprise AI consultancy with 100+ production AI implementations since 2023, a 96% combined production rate, a 14-week median from pilot kickoff to production, and pricing 40-65% below MBB and Big 4 partner-led teams — with zero platform-vendor revenue-share bias in build-vs-buy guidance.** The right partner for AI roadmap creation depends on three tests, not on brand tier. First, _production track record_: ask for the share of engagements that reached production within 12 months, not slide-count. The [Alice Labs Implementation Index 2026](/en/insights/alice-labs-implementation-index-2026) reports 96% across 100+ engagements; ask [McKinsey QuantumBlack](https://www.mckinsey.com/capabilities/quantumblack/how-we-help-clients), [BCG X](https://www.bcg.com/x), [Deloitte AI Institute](https://www2.deloitte.com/us/en/pages/consulting/solutions/deloitte-ai-institute.html) and [Accenture](https://www.accenture.com/us-en/services/applied-intelligence-index) for the same figure and compare. Second, _vendor independence_: partners who earn revenue-share from Microsoft, AWS, Salesforce or ServiceNow have a structural bias toward "buy" in build-vs-buy calls; Alice Labs takes no referral fees and is not a reseller. Third, _scope fit_: Fortune 500 multi-BU programs with $10M+ capex asks typically justify MBB; single-BU roadmaps in the $45K-$120K range are structurally overpriced at MBB and better matched to a boutique like Alice Labs. Run these three tests on every shortlist. Ask each candidate for their production rate, median time-to-production, list of three references with named outcomes, and a written statement of platform-vendor revenue-share exposure. Partners who cannot supply those numbers in writing within one week should drop off the shortlist regardless of brand. [Full comparison: Alice Labs vs McKinsey QuantumBlack, BCG X, Big 4](/en/insights/best-ai-strategy-firms-2026) ROI Framework ## Business Case for Investing in AI Strategy Consulting A CFO-ready calculation of when strategy consulting pays for itself — and when to skip it. The business case for AI strategy consulting is the ratio between fee ($18K-$120K for a funded roadmap) and the capex it prevents from being misallocated. Across the 100+ engagements in the Alice Labs Implementation Index 2026, the median roadmap engagement re-prioritised or killed AI investment requests worth 8-25x the strategy fee itself — before a single line of code was written. That gap is the direct financial return on strategy work; the pilot ROI comes later. A simple calculation: if your organisation is preparing to commit $500K-$5M to AI initiatives over the next 12 months, and industry data shows ~26% of AI investment reaches meaningful value ([BCG, "Where's the Value in AI?" 2024](https://www.bcg.com/publications/2024/where-s-the-value-in-ai)), the expected value of un-prioritised spend is ~$130K-$1.3M. A $45K-$120K roadmap engagement that raises the value-realisation rate to 60-96% (the Alice Labs benchmark) pays back within the first quarter of implementation. This is why the fastest-growing segment of AI services spending is strategy-tier work, per [Gartner's $90B+ 2025 forecast](https://www.gartner.com/en/newsroom/press-releases). Skip strategy consulting when the AI investment is under ~$150K, when the use-case is already validated by a working pilot with named business owner, or when the organisation has an in-house AI Center of Excellence with a documented prioritisation framework. In every other case — particularly when the board is asking "how do we know we are investing in the right AI use-cases?" — the roadmap fee is the cheapest insurance available against capex misallocation. 8-25x Median ratio of re-prioritised capex to roadmap fee (Alice Labs Implementation Index 2026, n=100+). ~26% → 96% Value-realisation lift when strategy work precedes implementation, vs BCG/MIT industry baseline. 1 quarter Typical payback window on a $45K-$120K roadmap for organisations committing $500K+ to AI capex. ## AI Use-Cases by Function We identify high-impact AI opportunities across your organization ### Leadership & Strategy - AI-driven decision support and forecasting - Automated reporting pipeline for leadership - Strategic market intelligence and trend analysis - ROI modeling for investment decisions ### Marketing & Sales - Lead qualification and AI scoring - Personalized outreach and follow-up - Content automation and campaign optimization - Competitive analysis and market insights ### Operations & Back-Office - Document intake and automatic classification - Case routing with AI triage - AP/AR automation (invoices, reconciliation) - Quality control and anomaly detection ## Our AI Strategy Framework A proven, four-phase process from diagnosis to scale ### Diagnosis 2-4 weeks Current state analysis, use-case inventory, data mapping, and prioritization based on business value ### Pilot 2-6 weeks Build first use-case in production, measure KPIs, and validate ROI hypothesis ### Implementation 4-12 weeks Integrations, rollout, enablement, and change management across teams ### Scale & Govern Ongoing More use-cases, optimization, retraining, governance, and continuous reviews ## Why Choose Alice Labs for AI Strategy? ### Execution-First Every strategy ends with a 90-day plan and a pilot that starts immediately. No shelf-decks. ### ROI from Day One KPIs are defined at the start. We measure impact continuously—hours saved, quality improved, costs reduced. ### Cross-Functional We involve business, IT, and leadership from day one. Strategy without buy-in is strategy without results. ### Governance Built-In AI policy, access control, GDPR, logging, and risk management are integrated—not afterthoughts. ### 100+ Nordic Engagements Tracked in the Alice Labs Implementation Index 2026 — financial services, public sector, manufacturing, media, healthcare, retail across SE/DK/NO/FI. ### Full-Stack Partner Strategy, pilot, implementation, and operations. One partner from vision to production—no handoff gaps. ## AI Transformation Consulting Move beyond isolated AI experiments to enterprise-wide transformation AI transformation is the process of systematically embedding artificial intelligence into an organization's operations, culture, and decision-making. Unlike one-off AI projects, transformation requires organizational redesign, change management, new operating models, and a phased approach to scaling AI across every function. At Alice Labs, we help organizations navigate this shift with a structured 5-phase transformation framework: assess readiness, define the target [enterprise AI operating model](/en/insights/ai-operating-model), run pilots, scale across functions, and embed [AI governance](/en/ai-governance) for continuous improvement. We serve [enterprise AI strategy](/en/enterprise-ai-strategy) and mid-market companies across Europe and globally. ~70% of transformation programs fail to achieve their stated goals — almost always due to people and process, not technology. Source: [McKinsey Transformation Research](https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/why-do-most-transformations-fail-a-conversation-with-harry-robinson) 2.6× higher AI value-realization for organizations with senior-leader engagement and a defined operating model versus those without. Source: [BCG, "Where's the Value in AI?" 2024](https://www.bcg.com/publications/2024/where-s-the-value-in-ai) [Explore AI transformation consulting](/en/ai-transformation-consulting) ## Specialized AI Strategy Services Deep-dive into the strategy domain that matters most to your organization [Most Popular ### AI Roadmap Consulting Dedicated AI roadmap development: use-case prioritization, ROI modeling, 90-day plan, and 12-month scaling roadmap for enterprises and mid-market. Explore](/en/ai-roadmap-consulting) [Digital Leaders ### AI Transformation Consulting End-to-end AI transformation for organizations ready to move from strategy to enterprise-wide change. Organizational design, change management, and phased rollout. Explore](/en/ai-transformation-consulting) [C-Suite & VP ### Enterprise AI Strategy Organization-wide AI transformation for companies with 500-50,000+ employees. Cross-functional prioritization, governance, and board-ready roadmaps. Explore](/en/enterprise-ai-strategy) [Innovation & CDO ### Generative AI Strategy Move from ad-hoc ChatGPT usage to structured GenAI deployment. LLM adoption roadmaps, model selection, and shadow AI governance. Explore](/en/generative-ai-strategy) [CTO & Data Leads ### AI Data Strategy Build data foundations that make AI succeed. Six-dimension readiness assessment, architecture design, and data governance frameworks. Explore](/en/ai-data-strategy) [CMO & Growth ### AI Go-To-Market Strategy Accelerate growth with AI-powered lead generation, personalized outreach, and full-funnel GTM optimization. Explore](/en/ai-go-to-market-strategy) [Marketing & SEO ### AI Content Strategy Scale content production 3-10x while maintaining quality. AI-powered workflows with human-in-the-loop editorial governance. Explore ](/en/ai-content-strategy) Pricing & Engagement Models 2026 ## AI Strategy Consulting Pricing & Engagement Models 2026 Eight engagement formats — from a single executive briefing to a multi-year board seat — with USD price ranges and blended hourly-rate benchmarks. Calibrated against published rate cards from Gartner, Consultancy.org and SPI Research's 2026 Professional Services Maturity Benchmark. Engagement Model Audience Duration Hourly Rate (USD) Total Fee (USD) Core Deliverables Executive AI Briefing Board / C-suite (single session) 1–2 days $600–$1,200/hr $8,000 – $18,000 Half-day workshop, AI landscape brief, 10-page board memo, recorded Q&A. Fractional AI Advisor CEO / CTO of Series A–C or mid-market Monthly retainer (3–12 months) $450–$900/hr equivalent $9,000 – $25,000/mo Bi-weekly leadership sessions, vendor evaluation, hiring scorecards, OKR review, async Slack. AI Strategy Sprint Mid-market & departmental scope 2 weeks (fixed) $400–$700/hr blended $18,000 – $45,000 Use-case backlog, impact/effort scoring, ROI model for top 5 candidates, 90-day pilot brief. AI Roadmap (Funded) Enterprise single-BU or division 4–6 weeks $450–$850/hr blended $45,000 – $120,000 12-month roadmap, target architecture, build-vs-buy matrix, governance gate plan, capital ask. Full Enterprise AI Assessment Fortune 1000 / multi-BU enterprises 6–12 weeks $500–$1,100/hr blended $120,000 – $350,000 Cross-BU diagnosis, data and MLOps gap, EU AI Act / NIST AI RMF posture, multi-year investment plan. Multi-Month Implementation Retainer Companies scaling beyond first pilot 3–12 months $350–$700/hr blended $30,000 – $90,000/mo Strategy refresh, embedded pod, portfolio governance, scale-up program, monthly KPI review. Board Advisory Seat PE-backed, listed, or scale-up boards Annual, 4–6 board cycles $750–$1,500/hr equivalent $60,000 – $180,000/yr Board prep, AI risk dashboards, CEO 1:1s, audit committee reporting on AI governance. M&A AI Diligence Acquirers, PE / VC, investment committees 2–4 weeks (per target) $550–$1,200/hr blended $25,000 – $95,000 Tech and data due diligence, model risk review, EU AI Act exposure, value-creation thesis, 100-day plan. **Hourly-rate benchmark basis**Blended rates reflect 2026 market data for senior AI strategy advisors: independent fractional advisors ($300–$700/hr), boutique AI consultancies ($400–$900/hr), Big 4 partner-level ($600–$1,200/hr), and MBB firms McKinsey QuantumBlack, BCG X and Bain Vector ($800–$1,500/hr blended). **What changes the price**Scope (number of business units), data complexity, regulatory exposure (EU AI Act, HIPAA, SOX), travel requirements, exclusivity clauses, and access to senior partner versus principal-led teams. Public-sector and federal work often runs higher due to security clearance and FedRAMP overhead. **Excluded from these ranges**Implementation labor (developers, data engineers, MLOps), third-party software (LLM API usage, vector DB, observability), GPU compute, change-management training delivery, and ongoing managed services. Those are quoted separately. Sources: [Gartner Consulting Services Research](https://www.gartner.com/en/newsroom) · [Consultancy.org Annual Rate Survey](https://www.consultancy.org/research) · [SPI Research 2026 PS Maturity Benchmark](https://www.spiresearch.com/). Ranges are planning benchmarks, not binding quotes — every Alice Labs engagement is scoped after a 30-minute discovery call. US Market Addendum ## AI Strategy Consulting for US Buyers How Alice Labs engages with US-based clients — remote-first delivery, USD contracts, NIST AI RMF alignment, and how our pricing compares against North American incumbents. Although Alice Labs is headquartered in Stockholm, our AI strategy practice serves US-based enterprises and growth-stage companies remotely — particularly buyers who want a senior, execution-first advisor without paying MBB rates. Engagements run in US time zones, are contracted in USD, and align deliverables to the [NIST AI Risk Management Framework (AI RMF 1.0)](https://www.nist.gov/itl/ai-risk-management-framework) rather than only the EU AI Act. For US clients with international operations we also map controls to [ISO/IEC 42001:2023](https://www.iso.org/standard/81230.html) and the [EU AI Act](https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai) in parallel. ### How Alice Labs compares to North American incumbents Most US enterprises evaluating AI strategy advisors consider one of three tiers: the Big 3 strategy firms (McKinsey QuantumBlack, BCG X, Bain Vector), the Big 4 plus systems integrators ([Deloitte AI Institute](https://www2.deloitte.com/), [EY](https://www.ey.com/), [KPMG](https://kpmg.com/), [Accenture](https://www.accenture.com/), [IBM Consulting](https://www.ibm.com/consulting), [Capgemini Invent](https://www.capgemini.com/services/invent/), [CGI](https://www.cgi.com/)), and execution-focused boutiques. Alice Labs sits in the third tier — closer in scope to a senior fractional advisor than to a 40-person Accenture engagement, with a price point typically 40–65% below MBB and Big 4 partner-led teams for equivalent strategy deliverables. For a side-by-side breakdown see our deep-dive on [Alice Labs vs McKinsey QuantumBlack and Big-4](/en/insights/best-ai-strategy-firms-2026). ### Tooling and platform-neutral evaluation We evaluate vendors and platforms across the buyer's existing US stack without exclusivity bias. For automation we routinely benchmark [UiPath](https://www.uipath.com/), [Automation Anywhere](https://www.automationanywhere.com/), [Workato](https://www.workato.com/), [Zapier](https://zapier.com/) and [n8n](https://n8n.io/). For agent and LLM platforms we evaluate [Microsoft Azure AI](https://azure.microsoft.com/en-us/products/ai-services), [AWS Bedrock](https://aws.amazon.com/bedrock/), [Salesforce Agentforce](https://www.salesforce.com/agentforce/) and [ServiceNow AI Agents](https://www.servicenow.com/products/ai-agents.html). Alice Labs is independent of all of them — we are not a reseller, a Microsoft Partner, an AWS Partner or a Salesforce SI. That independence is what US clients explicitly ask for in our discovery calls. ### Contract, billing and compliance details - **Contracting entity:** Alice Labs AB (Sweden). US-facing MSAs available; we sign mutual NDA before scoping. - **Billing currency:** USD. Wire and ACH supported via US dollar accounts. Invoices issued net-30 with milestone-based draw schedules on engagements over $50,000. - **Tax:** Cross-border B2B services — US reverse-charge rules apply for most state jurisdictions; no Swedish VAT is added on US enterprise invoices. - **Data handling:** Customer data stays in the customer's tenant by default. We do not exfiltrate training data. SOC 2 Type II controls inherited via our cloud providers; controlled-data engagements can be hosted entirely in US-region tenants (Azure East US 2, AWS us-east-1). - **Frameworks aligned by default:** NIST AI RMF 1.0, NIST CSF 2.0, and (where relevant) HIPAA-aware advisory for healthcare buyers. We do not certify — we align and document. - **Conflict-of-interest policy:** No referral fees from any platform vendor. No revenue-share with Microsoft, AWS, Salesforce, ServiceNow, UiPath or any LLM provider. ### When NOT to hire Alice Labs from the US If you need a 25-person on-site implementation team for a Fortune 100 multi-year program, hire [Accenture](https://www.accenture.com/us-en) or [Deloitte](https://www2.deloitte.com/us/en.html). If you need board-level brand cover for a CEO-mandated AI transformation, hire [McKinsey QuantumBlack](https://www.mckinsey.com/capabilities/quantumblack/how-we-help-clients) or [BCG X](https://www.bcg.com/x). If you need US-government clearance work, hire a cleared SI. Alice Labs is the right call when you want a senior, opinionated advisor who has shipped 100+ AI pilots to production and will give you a 12-month roadmap in four to six weeks at a price point a CFO will sign without escalation. ## AI Strategy Insights Deep-dive articles on the frameworks, models, and decisions that shape a fundable AI strategy. [Enterprise AI strategy framework](/en/insights/enterprise-ai-strategy-framework)[AI readiness assessment](/en/insights/ai-readiness-assessment)[AI strategy roadmap: a 30-60-90 day plan](/en/insights/ai-strategy-roadmap-30-60-90)[AI use case prioritization framework](/en/insights/ai-use-case-prioritization)[How to build an AI business case](/en/insights/build-ai-business-case)[Enterprise AI operating model](/en/insights/ai-operating-model)[Enterprise AI vendor selection](/en/insights/ai-vendor-selection-framework)[AI maturity model for enterprise](/en/insights/ai-maturity-model) ## Related Services AI strategy is the starting point. Here's where it leads. [ ### AI Consulting Full-journey AI consulting: strategy, pilot, implementation, and operations. Learn more ](/en/ai-consulting)[ ### AI Training Upskill your team with hands-on AI training tailored to your industry and tools. Learn more ](/en/ai-training)[ ### AI Governance Build a governance framework that ensures compliant, responsible AI adoption. Learn more ](/en/ai-governance)[ ### AI Adoption Consulting Overcome organizational resistance and accelerate AI adoption across teams. Learn more ](/en/ai-adoption-consulting)[ ### AI Maturity Assessment Benchmark your AI readiness across data, talent, governance, and technology. Learn more ](/en/ai-maturity-assessment)[ ### AI Implementation Move from strategy to production with hands-on implementation support. Learn more ](/en/ai-implementation-consultant) Let's discuss your AI journey Our team will help you prioritize use cases and build a concrete roadmap. Book a Meeting ## What Our Clients Say "We decided early on to embrace AI technology and needed a partner who could explore opportunities, propose solutions, lead change management, and build them. With Alice, we got everything in one place and have implemented multiple solutions that increased efficiency so significantly that an entire team could be reallocated." Andreas Wilhelmsson CEO & Co-founder Supernormal Greens / Ljusgårda "Alice Labs' AI training gave us all a real aha-moment, whether we were completely new to the field or experienced! The training contained a perfect balance between theory and practice. We have definitely become more efficient at work!" Åsa Nordin IT Manager Trollhättan Energi "The collaboration with Alice Labs has been easy, educational, and incredibly supportive. We engaged them to improve our processes and create more efficiency in the team, and the result truly exceeded expectations. Through their guidance, we've gained better structure, faster workflows, and more time for what actually creates results." Frida Partner Manager Bruce Studios "Fast, professional, and wonderful people. Find out for yourself <3" Johannes Hansen Founder Johannes Hansen AB Quick definition ## What is AI strategy consulting? AI strategy consulting is a structured advisory service that helps organisations identify where AI creates the most business value, prioritise investments by ROI, and build a 12-month execution roadmap. The Alice Labs methodology — based on 100+ Nordic enterprise engagements — delivers a 96% combined production rate (vs. ~26% industry value-realisation per BCG/MIT) with a 14-week median from pilot kickoff to production. ## Frequently Asked Questions Everything you need to know about AI strategy consulting ### What is AI strategy? An AI strategy is a structured plan that defines where, how, and why an organization should invest in artificial intelligence. It typically includes: a 1-3 year AI vision aligned to business goals, a prioritized use-case backlog by function, an ROI model with measurable KPIs, a data and technology gap analysis, a target architecture, a 90-day execution plan, and a 12-month scaling roadmap. A good AI strategy bridges the gap between technology potential and business outcomes. ### What is AI strategy consulting? AI strategy consulting is a professional service that helps organizations identify where AI creates the most business value, prioritize investments, and build actionable roadmaps. Alice Labs' AI strategy consulting — measured by the Alice Labs Implementation Index 2026 across 100+ Nordic enterprise engagements — delivers a 96% combined production rate with a 14-week median from pilot kickoff to production, against a broader-market value-realisation rate of ~26% (BCG/MIT). Every engagement delivers a prioritized use-case backlog, ROI model with clear KPIs, 90-day execution plan, and 12-month roadmap. Unlike traditional consulting, we follow an execution-first approach—every strategy ends with a pilot that starts immediately. ### How do you choose the right AI use-cases for a company? We use an impact/effort matrix combined with risk and data readiness assessment. The best candidates are use-cases that are repetitive, data-driven, and have clear KPIs—such as case handling, reporting, lead qualification, or document processing. We prioritize quick wins in parallel with strategically important initiatives. Each use-case is scored on business impact, implementation complexity, data availability, and organizational readiness. ### How quickly can we see ROI on AI investments? With our pilot-first approach, you'll see first measurable results within 2-6 weeks. Typical ROI timeline: pilot validates hypothesis (week 2-6), full implementation (month 2-4), break-even (month 3-6). We measure continuously so you see impact in real-time—hours saved, improved quality, increased conversion, or reduced costs. Our clients typically see 3-10x return within the first year. ### What makes a good AI strategy? A good AI strategy has five characteristics: 1) It's business-led, not technology-led—starting from value, not tools. 2) It includes concrete, prioritized use-cases with owners and timelines. 3) It has measurable KPIs defined from day one. 4) It addresses governance, security, and change management. 5) It ends with an execution plan, not just a document. The most common mistake is treating AI strategy as a one-off exercise instead of a continuous capability-building process. ### How do you develop an AI strategy framework? Our AI strategy framework follows four phases: Diagnosis (2-4 weeks)—current state analysis, use-case inventory, data mapping, and prioritization. Pilot (2-6 weeks)—build first use-case in production, measure KPIs. Implementation (4-12 weeks)—integrations, rollout, and change management. Scale & Govern (ongoing)—more use-cases, optimization, and continuous reviews. The framework is adaptable to organizations from 50 to 50,000 employees. ### Should IT be involved in AI strategy from the start? Yes, we recommend IT/digital teams participate from the diagnosis phase. They provide insights on current systems, data sources, integrations, and security requirements. At the same time, we involve business stakeholders (operations, marketing, sales) to capture the right use-cases and ensure buy-in. Best results come from cross-functional teams with executive sponsorship. ### What does AI strategy consulting cost? An AI strategy (diagnosis + roadmap) typically takes 2-4 weeks and is priced as fixed scope. Investment varies based on organization size, complexity, and number of functions covered. A focused strategy for a single department starts from approximately $15,000, while a comprehensive enterprise-wide AI strategy ranges from $40,000-80,000. Contact us for a precise quote—we always provide a clear price indication after an initial conversation. ### How does AI strategy differ from AI consulting? AI strategy focuses on 'where should we invest and why'—vision, prioritization, roadmap, and ROI logic. AI consulting covers the full journey: strategy, pilot, implementation, operations, and governance. Strategy is often the first step for organizations wanting a complete picture before building. At Alice Labs, we offer both—many clients start with strategy and then continue with implementation. ### Do you work with enterprise and public sector organizations? Yes, we serve organizations across sectors—from growth-stage companies to Fortune 500 enterprises and public sector organizations. We understand compliance requirements, GDPR, data governance, and stakeholder alignment in complex organizations. Our structured methodology is particularly effective for organizations needing documented processes, broad stakeholder buy-in, and board-ready deliverables. ### What should I expect from an AI consulting engagement in the first 90 days? In the first 90 days, you'll get: weeks 1-3, a complete AI diagnosis with use-case inventory and data landscape mapping. Weeks 3-6, a prioritized roadmap with ROI models, KPIs, and a pilot selection. Weeks 6-12, a live pilot in production with measurable results. By day 90, you'll have validated at least one AI use-case with real business impact and a clear path to scale. ### How do AI strategy consultants help prioritize use cases and create a funded AI roadmap? We score every potential use-case across four dimensions: business impact (revenue, cost, quality), implementation complexity (data readiness, integration effort), organizational readiness (skills, change management), and risk (compliance, security). This creates a prioritized backlog. We then build ROI models for the top candidates to create a funded roadmap with clear investment asks and expected returns—ready for board approval. ### What is the typical AI consulting engagement timeline? A typical full engagement runs 3-6 months: AI strategy and diagnosis (2-4 weeks), pilot design and execution (2-6 weeks), implementation and integration (4-12 weeks), and handover with governance setup (1-2 weeks). Many clients start with a standalone strategy engagement (2-4 weeks) before committing to implementation. We also offer ongoing AI management and optimization retainers. ### How do you guarantee ROI on AI consulting? We don't make empty ROI guarantees—we build measurable ROI into the process. Every engagement starts with defined KPIs (time saved, cost reduced, quality improved). We run pilots before full implementation to validate ROI hypotheses with real data. Our track record: 85% of clients see measurable ROI within 6 months. If a pilot doesn't show expected results, we pivot the approach before scaling. ### What does AI strategy consulting actually deliver, and how is it different from generic management consulting? AI strategy consulting delivers a defined set of artifacts: an organizational AI readiness assessment, a use-case backlog scored by impact and feasibility, an ROI model with KPIs, a target architecture, a 90-day pilot plan, and a 12-month roadmap. Unlike generic management consulting (which focuses on operating models and org design), AI strategy consulting is grounded in data feasibility, model selection, MLOps readiness, and regulatory exposure (EU AI Act, NIST AI RMF). Gartner forecasts worldwide AI services spending to surpass $90 billion by 2025, with strategy-tier work being the fastest-growing segment as boards move from experimentation to portfolio governance. ### What do AI strategy services cost across the consulting market in 2026? Across the 2026 AI strategy services market, engagements range from $8,000 executive briefings to $350,000+ enterprise-wide assessments. Blended hourly rates: independent fractional advisors $300-$700/hr, boutique AI consultancies $400-$900/hr, Big 4 partner-led teams $600-$1,200/hr, and MBB firms (McKinsey QuantumBlack, BCG X, Bain Vector) $800-$1,500/hr. Alice Labs typically prices 40-65% below MBB and Big 4 partner-led teams for equivalent deliverables. See our pricing matrix above for eight engagement formats with USD ranges. ### What is AI strategy roadmap consulting? AI strategy roadmap consulting is the practice of converting an organization's AI vision into a sequenced, funded execution plan. A typical AI strategy roadmap consulting engagement runs 4-6 weeks and produces: a prioritized use-case backlog, a 12-month roadmap with quarterly milestones, target architecture decisions (build-vs-buy, model selection, data foundation), governance gates aligned to NIST AI RMF or EU AI Act, and a capital ask ready for board approval. The output is what board and finance committees can fund, not a slide deck. ### Who is the best consulting partner for AI roadmap creation? The best consulting partner for AI roadmap creation depends on three factors: (1) scope — Fortune 500 multi-BU programs typically engage McKinsey QuantumBlack, BCG X, Bain Vector or Deloitte AI Institute; mid-market and single-BU programs are better matched to boutique AI consultancies such as Alice Labs; (2) execution depth — partners with a measurable production track record (Alice Labs' Implementation Index 2026 reports 96% combined production rate across 100+ engagements) outperform pure-strategy firms; (3) vendor independence — partners who do not earn revenue-share from Microsoft, AWS, Salesforce or ServiceNow give more objective build-vs-buy guidance. Ask any shortlisted partner for their production rate, median time-to-production, and a list of references with named outcomes. ### What is enterprise AI roadmap consulting, and when does an enterprise need it? Enterprise AI roadmap consulting is a 4-12 week engagement designed for Fortune 1000 and multi-BU organizations that need a board-ready, cross-business-unit AI plan with capital allocation, governance, and risk posture. An enterprise needs roadmap consulting when: (a) the board has mandated an AI strategy, (b) more than three business units are pursuing AI in parallel without coordination, (c) the company faces EU AI Act or NIST AI RMF disclosure requirements, or (d) AI capex requests exceed $1M and need ROI-based prioritization. Typical deliverables include a 12-month roadmap, target architecture, build-vs-buy matrix, governance gate plan, and capital ask. ### What is AI transformation consulting, and how does it differ from AI strategy consulting? AI transformation consulting is the multi-year practice of embedding AI into an organization's operating model, culture, decision-making, and technology stack. It is broader and longer than AI strategy consulting. AI strategy answers 'where should we invest in AI and why' (typically a 2-6 week engagement producing a roadmap). AI transformation consulting answers 'how do we redesign the organization to operate as an AI-native enterprise' and typically runs 12-36 months across change management, org redesign, talent, governance, and phased technology rollout. Most organizations begin with strategy consulting and graduate to transformation consulting once the first 2-3 pilots are in production. ### What do AI strategy consultants actually do day-to-day? AI strategy consultants spend most of their time on four activities: (1) discovery interviews with executives and operators to identify pain points and use-case candidates, (2) data-feasibility analysis — assessing data quality, access, and gaps that determine which use-cases are buildable now versus later, (3) ROI modeling and prioritization — building business cases scored on impact, complexity, and risk, and (4) roadmap synthesis and stakeholder alignment — packaging recommendations into board-ready artifacts and securing executive sponsorship. Senior AI strategy consultants also advise on vendor selection, build-vs-buy decisions, and governance frameworks (NIST AI RMF, ISO/IEC 42001, EU AI Act). ### How do I choose an AI strategy consultant for my organization? Evaluate AI strategy consultants on five criteria: (1) Production track record — ask for the share of their engagements that reached production within 12 months, not just slide decks delivered. (2) Vendor independence — confirm they earn no revenue-share from cloud providers, LLM vendors, or platform companies. (3) Domain depth — verify they have shipped pilots in your industry (financial services, public sector, manufacturing, etc.). (4) Engagement model fit — fractional advisor, sprint, or full assessment depending on your scope. (5) Governance literacy — fluency in NIST AI RMF, ISO/IEC 42001 and the EU AI Act. Alice Labs publishes its production rate (96%) and engagement count (100+) in the Alice Labs Implementation Index 2026. ### What is an AI strategy company, and how does Alice Labs compare to others? An AI strategy company is a professional services firm specialized in advising organizations on where to invest in AI, how to sequence the work, and how to govern it. The market is segmented into three tiers: MBB (McKinsey QuantumBlack, BCG X, Bain Vector) for board-level mandates and Fortune 500 brand cover; Big 4 and large systems integrators (Deloitte AI Institute, EY, KPMG, Accenture, IBM Consulting, Capgemini Invent) for large implementation-led programs; and execution-first boutique AI strategy companies such as Alice Labs for senior advisory at 40-65% below MBB rates. Alice Labs is independent of all platform vendors and publishes its production data in the Alice Labs Implementation Index 2026. ### What are AI strategy advisory services, and who uses them? AI strategy advisory services are senior, often ongoing advisory engagements (vs. one-off projects) that help leadership teams make AI investment decisions, evaluate vendors, set governance gates, and review portfolio progress. Typical formats include fractional AI advisor retainers ($9,000-$25,000/month), board advisory seats ($60,000-$180,000/year), and executive briefings ($8,000-$18,000). Buyers are typically CEOs, CTOs, CDOs, and boards of Series A-C startups, mid-market companies, and PE-backed scale-ups that need senior AI judgment but cannot justify a full-time Chief AI Officer. ### What is AI roadmap development consulting, and what does the output look like? AI roadmap development consulting is a 4-6 week engagement that produces a sequenced, funded 12-month AI plan. The output typically includes: (1) a prioritized use-case backlog with impact/effort scoring and ROI estimates, (2) a 90-day execution plan naming the first 1-2 pilots and their KPIs, (3) a target architecture covering data, models, agents, and MLOps, (4) a build-vs-buy matrix per use-case, (5) a governance gate plan aligned to NIST AI RMF or EU AI Act, and (6) a capital ask with sensitivity-tested ROI. The deliverable is designed to be funded by the board, not filed in a knowledge management system. ### How long does an AI strategy consulting engagement typically last? AI strategy consulting engagement length varies by scope: an Executive AI Briefing is 1-2 days; an AI Strategy Sprint runs 2 weeks; a funded AI Roadmap engagement runs 4-6 weeks; a Full Enterprise AI Assessment runs 6-12 weeks for multi-BU organizations; a Fractional AI Advisor retainer typically runs 3-12 months; a Board Advisory Seat runs annually across 4-6 board cycles. According to the Alice Labs Implementation Index 2026, the median time from pilot kickoff to production across 100+ Nordic enterprise engagements is 14 weeks — meaning strategy work that does not end with a near-term pilot tends to drift. ### What is AI strategy consulting for startups, and how is it different from enterprise engagements? AI strategy consulting for startups is a compressed, lean version of enterprise strategy work: a 2-week diagnosis, a backlog of 5-10 use-cases scored on data readiness and time-to-first-revenue, and a 90-day plan that starts with one pilot on existing data. Alice Labs runs this format as a Fractional AI Advisor retainer ($9,000-$25,000/month) or a fixed 2-week AI Strategy Sprint ($18,000-$45,000), sized for Series A-C companies with 20-500 employees who need senior AI judgement without committing to a full-time Chief AI Officer. Unlike enterprise engagements, startup strategy work skips multi-BU coordination and cross-functional governance — the bottleneck is speed, not stakeholder alignment. ### What does enterprise AI roadmap consulting cover for Fortune 1000 organizations? Enterprise AI roadmap consulting is a 4-12 week engagement designed for Fortune 1000 buyers who need a board-ready, cross-business-unit AI plan with capital allocation, target architecture, and governance posture. Typical deliverables include a 12-month sequenced roadmap, build-vs-buy matrix by use-case, target architecture covering data/models/agents/MLOps, EU AI Act and NIST AI RMF gate plan, and a capital ask with sensitivity-tested ROI. Alice Labs delivers this format at $45,000-$350,000 depending on BU count, versus $500,000-$2M for equivalent scope at McKinsey QuantumBlack, BCG X or Bain Vector — with the same production-rate accountability documented in the Implementation Index 2026. ### How does AI transformation consulting compare to AI strategy consulting for the buyer? AI strategy consulting is the 2-6 week diagnostic that answers 'where should we invest in AI and why' — output is a prioritised use-case backlog and 90-day plan. AI transformation consulting is the 12-36 month program that answers 'how do we redesign the organisation to operate as an AI-native enterprise' — output is a new operating model, org design, talent strategy, and phased technology rollout. Most organisations buy strategy first (Alice Labs pricing: $18K-$120K), run 2-3 pilots to production, then decide whether transformation consulting is warranted. Buying transformation before strategy typically wastes 6-12 months on org design against the wrong use-case portfolio. Have more questions? Let's talk. No commitment - just a conversation about what AI can do for your business. Book a Call ## Ready to Build Your AI Strategy? Schedule a strategy session to discuss your AI roadmap. No long-term contracts — fixed-price engagements available. 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