--- title: "AI Feasibility & Validation Consulting | Independent AI Assessment - Alice Labs" description: "AI feasibility studies, validation, verification & testing services. Independent assessment before & after implementation. 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It produces an objective go/no-go decision basis covering: data readiness assessment, technical architecture options, vendor/build comparison, ROI modelling, risk register, and a fixed-price implementation plan if go-decision is reached." } }, { "@type": "Question", "name": "What is the difference between AI verification and AI validation?", "acceptedAnswer": { "@type": "Answer", "text": "AI verification answers 'are we building the system right?' (does it meet technical specifications and pass QA tests). AI validation answers 'are we building the right system?' (does it solve the actual business problem and produce intended outcomes in production). Both are required for production AI under the EU AI Act. Alice Labs delivers both as part of every implementation." } }, { "@type": "Question", "name": "When should we run an AI feasibility study before implementation?", "acceptedAnswer": { "@type": "Answer", "text": "Run a feasibility study when: (1) the use case is novel or unproven in your industry, (2) the investment exceeds €100,000, (3) data quality is uncertain, (4) the use case is high-risk under EU AI Act, (5) internal stakeholders disagree on viability. Skipping feasibility on these projects creates 60-80% failure rates. A €10,000 study can prevent a €500,000 mistake." } }, { "@type": "Question", "name": "What does an AI feasibility study include?", "acceptedAnswer": { "@type": "Answer", "text": "A complete AI feasibility study includes: (1) business problem framing and KPI definition, (2) data audit — availability, quality, governance, (3) technical feasibility — model options, infrastructure, integration paths, (4) vendor vs build vs hybrid comparison, (5) cost-benefit ROI model with sensitivity analysis, (6) risk register with mitigation plans, (7) regulatory assessment (EU AI Act, GDPR), (8) phased implementation roadmap with fixed-price proposal." } }, { "@type": "Question", "name": "How long does an AI feasibility study take?", "acceptedAnswer": { "@type": "Answer", "text": "A focused single-use-case feasibility study takes 2-4 weeks. Portfolio-level feasibility (3-5 use cases prioritised against each other) takes 4-6 weeks. Enterprise AI capability assessments take 6-8 weeks. We provide a complete deliverable — not a slide deck — including all data, models, and decision artifacts you need to commit budget with confidence." } }, { "@type": "Question", "name": "How much does an AI feasibility study cost?", "acceptedAnswer": { "@type": "Answer", "text": "Single-use-case feasibility: €10,000-€20,000 fixed price (2-4 weeks). Portfolio feasibility (3-5 use cases): €25,000-€45,000 (4-6 weeks). Enterprise AI capability assessment: €50,000-€80,000 (6-8 weeks). The fee is credited against full implementation if you proceed with Alice Labs as your delivery partner — making it effectively risk-free for committed buyers." } }, { "@type": "Question", "name": "What is AI testing and validation in production?", "acceptedAnswer": { "@type": "Answer", "text": "Production AI testing and validation includes: model performance testing (accuracy, precision, recall, F1), bias and fairness testing across demographic segments, adversarial testing (prompt injection, edge cases), load and stress testing, drift monitoring (data and concept drift), A/B testing infrastructure, and continuous validation against ground truth. EU AI Act high-risk systems require documented validation — we deliver compliant evidence packages as standard." } }, { "@type": "Question", "name": "Can you validate AI systems we built ourselves or with another vendor?", "acceptedAnswer": { "@type": "Answer", "text": "Yes. We offer independent AI validation and verification services for systems built in-house or by third-party vendors. Our independent assessment covers technical performance, bias and safety, security, compliance with EU AI Act and GDPR, and production readiness. Independent validation is increasingly required for AI procurement, board reporting, and regulatory submissions." } }, { "@type": "Question", "name": "What is AI problem management consulting?", "acceptedAnswer": { "@type": "Answer", "text": "AI problem management consulting addresses AI systems that are underperforming, drifting, generating incidents, or failing to deliver business value. We diagnose root causes (data, model, integration, change management), prescribe remediation (retraining, architecture changes, governance, user adoption), and implement fixes. Common engagements: chatbot accuracy decline, recommendation quality drop, vision system false positives, generative AI hallucination control." } }, { "@type": "Question", "name": "Do you offer ongoing AI validation and monitoring?", "acceptedAnswer": { "@type": "Answer", "text": "Yes. Post-deployment, we offer managed AI validation services from €5,000/month per system: continuous performance monitoring, drift detection, scheduled retraining, incident response, EU AI Act compliance reporting, and quarterly executive validation reviews. This is required for any production AI system you intend to operate at scale, especially in regulated industries." } }, { "@type": "Question", "name": "What is the primary output of conducting an AI feasibility assessment?", "acceptedAnswer": { "@type": "Answer", "text": "The primary output is a written go/no-go decision document — typically 40-60 pages — with a single-page executive recommendation on the cover. It bundles four artifacts a board can act on: (1) a quantified ROI model with 3 sensitivity scenarios, (2) a technical architecture recommendation, (3) an EU AI Act risk classification, and (4) a fixed-price phased implementation plan. Roughly 25% of Alice Labs feasibility studies conclude 'do not proceed' and save the client six-figure sums." } }, { "@type": "Question", "name": "How do AI feasibility consulting studies differ from a general AI strategy engagement?", "acceptedAnswer": { "@type": "Answer", "text": "A strategy engagement produces a 3-5 year portfolio vision across many use cases. A feasibility study answers one question about one use case in 2-4 weeks: does the data, tech, economics and risk profile support building this specific system? Feasibility outputs are quantitative (ROI ranges, error bounds, TCO figures with a ±15% confidence interval), not directional. Most enterprises need both, in that order — strategy to prioritise, feasibility to commit budget." } } ] } ] } ] --- ![Background for AI Feasibility Validation Consulting](/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) [Home](/en)[AI Consulting](/en/ai-consulting) AI Feasibility & Validation Independent AI Assessment Fresh Last reviewed: 15 July 2026 · 48d ago # AI Feasibility & Validation Consulting - Risk-Controlled AI Investment Alice Labs delivers independent AI feasibility studies, validation, verification and testing for enterprises that need objective analysis before committing capital. Fixed-price 2-4 week assessments. EU AI Act native. Fee credited if you proceed with full implementation. Book a Discovery Call[See What's Included](#deliverables) 2-4 week delivery Fixed-price assessment EU AI Act compliant 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 ![Alice, CEO & Co-founder](/images/team-portrait-2.jpg) Alice CEO & Co-founder ![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 ![Lisa, Project Lead & Implementation](/images/team-portrait-5.jpg) Lisa Project Lead & Implementation ## 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 Ready to see similar results? Book a free discovery call - we'll map your highest-impact AI opportunities. Book a Discovery Call ## What Is AI Feasibility & Validation Consulting? **AI feasibility consulting** is the structured assessment of whether a proposed AI investment is technically viable, economically sound, and strategically aligned — before significant capital is committed. **AI validation consulting** verifies that AI systems work as intended in production and continue to deliver business value over time. At **Alice Labs**, our independent assessment practice produces objective decision artifacts that CFOs, CIOs and boards trust. We have prevented €10M+ in misallocated AI spend across Europe by recommending stop or pivot decisions when the data didn't support proceeding. **2026 baseline:** Gartner forecasts that at least 30% of generative AI projects will be abandoned after proof of concept by the end of 2025 — driven by poor data quality, unclear business value and inadequate risk controls ([Gartner, 2024](https://www.gartner.com/en/newsroom/press-releases/2024-07-29-gartner-predicts-30-percent-of-generative-ai-projects-will-be-abandoned-after-proof-of-concept-by-end-of-2025)). A structured feasibility study catches these failure modes before capital is committed. Last reviewed: 2026-07-15 · Next review due: 2026-10-13 ## Our Assessment Services Independent AI evaluation across the full lifecycle — pre-investment to production ### AI Feasibility Studies 2-4 week structured analysis. Go/no-go decision basis with ROI model, risk register, and implementation plan. ### AI Verification Does it meet specs? Technical QA, code review, model performance testing, security assessment. ### AI Validation Does it solve the problem? Business outcome validation, bias testing, user acceptance, real-world performance. ### Independent System Audit Third-party assessment of AI systems built in-house or by other vendors. Compliance and performance audit. ### AI Problem Management Diagnosis and remediation of underperforming production AI. Root cause analysis to fix. ### AI ROI & Business Case Financial modelling, sensitivity analysis, total cost of ownership for AI investment decisions. ## What's Included in a Feasibility Study Every deliverable a board needs to approve or reject AI investment with confidence - Business problem framing with measurable success criteria - Data audit: availability, quality, governance, integration readiness - Technical feasibility analysis with 2-3 architecture options - Vendor vs build vs hybrid comparison with TCO modelling - Cost-benefit ROI model with sensitivity analysis (3 scenarios) - Risk register with mitigation plans and EU AI Act classification - GDPR data protection impact assessment (DPIA) - Phased implementation roadmap with fixed-price proposal - Executive presentation deck for board/investment committee - Independent recommendation: proceed, pivot, or stop ## Related AI Services From feasibility to full implementation under one accountable partner [ ### AI Discovery Sprint 2-4 week opportunity mapping ](/en/ai-discovery)[ ### AI Maturity Assessment Organisation-wide AI readiness ](/en/ai-maturity-assessment)[ ### AI Implementation Consultant Pilot to production delivery ](/en/ai-implementation-consultant)[ ### AI Governance EU AI Act compliance framework ](/en/ai-governance) ## AI Feasibility & Validation Research The evidence base behind our feasibility work: failure statistics, prioritisation, and tool selection. [Why do AI projects fail: statistics and reasons](/en/insights/why-ai-projects-fail)[AI readiness evaluation for enterprises](/en/insights/ai-readiness-assessment)[AI use case prioritisation framework](/en/insights/ai-use-case-prioritization)[Leading enterprise AI solutions 2026 for validation](/en/insights/best-ai-tools-for-enterprise-2026)[Claude vs GPT-4o vs Gemini strengths and weaknesses](/en/insights/gpt4o-vs-claude-vs-gemini)[Azure OpenAI vs AWS Bedrock: platform validation](/en/insights/azure-openai-vs-aws-bedrock)[EU AI Act for Swedish companies: risk validation](/en/insights/eu-ai-act-for-swedish-companies)[Enterprise AI strategy framework 2025-2026](/en/insights/enterprise-ai-strategy-framework) 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 an AI feasibility study? An AI feasibility study is a 2-4 week structured analysis that determines if a proposed AI use case is technically possible, economically viable and strategically aligned. It produces an objective go/no-go decision basis covering data readiness, architecture options, ROI model, risk register and a fixed-price implementation plan if go. ## Frequently Asked Questions Risk-averse executives ask these questions before committing AI budget ### What is an AI feasibility study? An AI feasibility study is a structured 2-4 week analysis that determines whether a proposed AI use case is technically possible, economically viable, and strategically aligned. It produces an objective go/no-go decision basis covering: data readiness assessment, technical architecture options, vendor/build comparison, ROI modelling, risk register, and a fixed-price implementation plan if go-decision is reached. ### What is the difference between AI verification and AI validation? AI verification answers 'are we building the system right?' (does it meet technical specifications and pass QA tests). AI validation answers 'are we building the right system?' (does it solve the actual business problem and produce intended outcomes in production). Both are required for production AI under the EU AI Act. Alice Labs delivers both as part of every implementation. ### When should we run an AI feasibility study before implementation? Run a feasibility study when: (1) the use case is novel or unproven in your industry, (2) the investment exceeds €100,000, (3) data quality is uncertain, (4) the use case is high-risk under EU AI Act, (5) internal stakeholders disagree on viability. Skipping feasibility on these projects creates 60-80% failure rates. A €10,000 study can prevent a €500,000 mistake. ### What does an AI feasibility study include? A complete AI feasibility study includes: (1) business problem framing and KPI definition, (2) data audit — availability, quality, governance, (3) technical feasibility — model options, infrastructure, integration paths, (4) vendor vs build vs hybrid comparison, (5) cost-benefit ROI model with sensitivity analysis, (6) risk register with mitigation plans, (7) regulatory assessment (EU AI Act, GDPR), (8) phased implementation roadmap with fixed-price proposal. ### How long does an AI feasibility study take? A focused single-use-case feasibility study takes 2-4 weeks. Portfolio-level feasibility (3-5 use cases prioritised against each other) takes 4-6 weeks. Enterprise AI capability assessments take 6-8 weeks. We provide a complete deliverable — not a slide deck — including all data, models, and decision artifacts you need to commit budget with confidence. ### How much does an AI feasibility study cost? Single-use-case feasibility: €10,000-€20,000 fixed price (2-4 weeks). Portfolio feasibility (3-5 use cases): €25,000-€45,000 (4-6 weeks). Enterprise AI capability assessment: €50,000-€80,000 (6-8 weeks). The fee is credited against full implementation if you proceed with Alice Labs as your delivery partner — making it effectively risk-free for committed buyers. ### What is AI testing and validation in production? Production AI testing and validation includes: model performance testing (accuracy, precision, recall, F1), bias and fairness testing across demographic segments, adversarial testing (prompt injection, edge cases), load and stress testing, drift monitoring (data and concept drift), A/B testing infrastructure, and continuous validation against ground truth. EU AI Act high-risk systems require documented validation — we deliver compliant evidence packages as standard. ### Can you validate AI systems we built ourselves or with another vendor? Yes. We offer independent AI validation and verification services for systems built in-house or by third-party vendors. Our independent assessment covers technical performance, bias and safety, security, compliance with EU AI Act and GDPR, and production readiness. Independent validation is increasingly required for AI procurement, board reporting, and regulatory submissions. ### What is AI problem management consulting? AI problem management consulting addresses AI systems that are underperforming, drifting, generating incidents, or failing to deliver business value. We diagnose root causes (data, model, integration, change management), prescribe remediation (retraining, architecture changes, governance, user adoption), and implement fixes. Common engagements: chatbot accuracy decline, recommendation quality drop, vision system false positives, generative AI hallucination control. ### Do you offer ongoing AI validation and monitoring? Yes. Post-deployment, we offer managed AI validation services from €5,000/month per system: continuous performance monitoring, drift detection, scheduled retraining, incident response, EU AI Act compliance reporting, and quarterly executive validation reviews. This is required for any production AI system you intend to operate at scale, especially in regulated industries. ### What is the primary output of conducting an AI feasibility assessment? The primary output is a written go/no-go decision document — typically 40-60 pages — with a single-page executive recommendation on the cover. It bundles four artifacts a board can act on: (1) a quantified ROI model with 3 sensitivity scenarios, (2) a technical architecture recommendation, (3) an EU AI Act risk classification, and (4) a fixed-price phased implementation plan. Roughly 25% of Alice Labs feasibility studies conclude 'do not proceed' and save the client six-figure sums. ### How do AI feasibility consulting studies differ from a general AI strategy engagement? A strategy engagement produces a 3-5 year portfolio vision across many use cases. A feasibility study answers one question about one use case in 2-4 weeks: does the data, tech, economics and risk profile support building this specific system? Feasibility outputs are quantitative (ROI ranges, error bounds, TCO figures with a ±15% confidence interval), not directional. Most enterprises need both, in that order — strategy to prioritise, feasibility to commit budget. Have more questions? Let's talk. No commitment - just a conversation about what AI can do for your business. Book a Call ## Need Independent AI Validation? Book a 30-minute scoping call. We'll quote a fixed-price feasibility study within 48 hours. 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