Alice Labs helps organizations move beyond isolated AI projects to full-scale AI transformation. We combine strategy, change management, and hands-on implementation to embed AI into how your organization operates—across every function, team, and process. Serving enterprises and mid-market companies across Europe and globally.
AI transformation consulting redesigns core business processes, organisational structure and technology stack so AI becomes a capability — not a project. It covers operating model redesign, change management, data foundation, AI governance and 12-24 month execution, typically generating 15-40% productivity gains in target functions.
An experienced team with broad AI and tech backgrounds from leading companies
Linus
Co-founder & AI Consultant
Alice
CEO & Co-founder
Jens
AI Consultant
Eric
Co-founder & AI Consultant
Lisa
Project Lead & Implementation
Production-grade AI delivery, EU-native, senior team
Verified outcomes from completed AI implementations
Ljusgårda (Supernormal Greens)
Public Sector
Media Company
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True AI transformation goes beyond deploying a few tools. It requires rethinking how your organization operates: redesigning processes, developing new capabilities, building data infrastructure, establishing governance, and managing the cultural shift that comes with AI-augmented work.
At Alice Labs, we use a proven 5-phase framework to guide organizations through this journey. Every transformation starts with a readiness assessment and ends with embedded AI capability—not just a pilot or a strategy document. We've supported over 100 AI transformations for enterprises and mid-market companies across Europe and globally.
Successful transformation requires change across every dimension
Clear AI vision tied to business outcomes with prioritized use-case backlog and ROI models
AI literacy programs, change management, new roles and skills development across the organization
Re-engineered workflows with AI augmentation, automation of repetitive tasks, and quality improvement
Scalable AI infrastructure, data pipelines, model management, and integration architecture
AI policies, access controls, GDPR compliance, EU AI Act readiness, and ethical AI frameworks
Continuous KPI tracking across efficiency, financial impact, capability building, and strategic value
From readiness assessment to embedded AI capability
2-4 weeks
Evaluate AI readiness across data, technology, talent, processes, and culture. Map the current state and identify transformation priorities.
2-4 weeks
Define target AI operating model, roles, governance structure, and technology architecture. Build the transformation roadmap with ROI models.
4-8 weeks
Launch 2-3 high-impact use-cases in production. Validate ROI hypotheses, refine approach, and build internal momentum.
3-12 months
Roll out AI across functions with change management, training, integration support, and continuous measurement.
Ongoing
Establish continuous improvement, AI governance frameworks, and build lasting organizational AI capability.
Signs your organization is ready for enterprise-wide AI transformation
You have multiple AI pilots and tools across departments but lack a unified strategy, governance, and operating model to scale them.
You're embarking on a broader digital transformation and want AI to be a core pillar—not an afterthought bolted on later.
You've invested in AI but can't demonstrate clear business value. Transformation consulting helps connect AI to measurable outcomes.
Your teams are skeptical or struggling to adopt AI tools. Transformation addresses the people and culture side that technology alone can't fix.
Concrete outputs at every phase of your transformation journey
AI transformation connects to every stage of your AI journey
Build the strategic foundation that drives transformation priorities and investment decisions.
Learn moreMove from roadmap to production with hands-on implementation and integration support.
Learn moreEstablish governance frameworks that ensure compliant, responsible AI adoption at scale.
Learn moreOvercome resistance and accelerate AI adoption with structured change management.
Learn moreLet's discuss your AI journey
Our team will help you prioritize use cases and build a concrete roadmap.
"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
Common questions about AI transformation consulting
AI transformation consulting helps organizations move beyond isolated AI experiments to enterprise-wide adoption. It covers organizational readiness, operating model redesign, change management, phased rollout, and governance—ensuring AI becomes embedded in how the organization operates, not just in a few tools.
AI strategy answers 'where and why should we invest in AI?' AI transformation answers 'how do we fundamentally change how our organization works with AI?' Transformation includes strategy but goes further: it encompasses organizational design, talent development, process re-engineering, culture change, and continuous scaling across all functions.
A comprehensive AI transformation roadmap includes: current state assessment with readiness scoring, target operating model definition, a prioritized use-case backlog with ROI models, organizational change plan (roles, skills, culture), technology architecture and data infrastructure requirements, governance framework, phased rollout timeline with milestones, and success metrics with continuous measurement.
Enterprise AI transformation typically unfolds in phases: initial assessment and pilot (2-3 months), first wave of scaled implementations (3-6 months), organization-wide rollout (6-18 months), and continuous optimization (ongoing). The first measurable results appear within 8-12 weeks. Full transformation is a 12-24 month journey depending on organization size and complexity.
The five biggest AI transformation risks are: 1) Starting with technology instead of business value. 2) Underinvesting in change management and training. 3) Lack of executive sponsorship and governance. 4) Poor data quality and fragmented infrastructure. 5) Trying to transform everything at once instead of phased rollout. Our framework addresses each risk systematically.
Yes, we serve enterprises and mid-market companies across Europe and globally. We understand EU-specific requirements including GDPR, the EU AI Act, and regional compliance frameworks. Our team works in English and Swedish, and we've delivered AI transformation projects for organizations across Scandinavia, DACH, Benelux, and the UK.
AI transformation creates the most value in data-rich, process-heavy industries: financial services (risk, compliance, customer experience), healthcare (clinical workflows, administration), manufacturing (supply chain, quality control), professional services (knowledge management, billing), and public sector (case handling, citizen services). We have experience across all of these.
We define success metrics across four dimensions: operational efficiency (hours saved, throughput increased, error rates reduced), financial impact (cost savings, revenue growth, ROI), organizational capability (AI literacy, adoption rates, number of AI-powered processes), and strategic value (competitive positioning, innovation speed, data-driven decision quality). KPIs are set at the start and measured continuously.
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