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Enterprise AI leadership
Senior Practitioners · Not Junior Analysts

The advisors who have actually built it

Every advisor on this team has spent 15 or more years deploying production AI systems at enterprise scale. Not studying them. Not advising on frameworks. Building, debugging, and shipping them across some of the world's most demanding technology environments.

15+yrs
Avg Advisor Experience
200+
Enterprises Advised
500+
Models in Production
4
Major Firm Backgrounds
Co-Founders

Built by practitioners, not consultants

AI Advisory Practice was founded in 2022 by Fredrik Filipsson and Morten Andersen — two practitioners who have been building AI-powered businesses since AI became practically deployable. They founded this practice to give enterprises access to the same quality of AI thinking they apply to their own ventures.

FF
Co-Founder · AI Strategy and Enterprise Transformation
Fredrik Filipsson
AI practitioner since 2022 · Building multiple AI-powered businesses

Fredrik co-founded AI Advisory Practice to bring genuine practitioner-level AI guidance to enterprises. He has been applying AI in commercial contexts since 2022, building multiple businesses with AI as a core operational advantage. His advisory focus is AI strategy, use-case prioritisation, and vendor selection.

He advises from direct experience making the same build versus buy decisions, facing the same data quality constraints, and navigating the same organisational resistance that enterprise AI leaders encounter daily. His writing takes a direct, contrarian stance against AI hype and focuses on what actually works in production.

AI Strategy Vendor Selection Generative AI AI Readiness Enterprise AI
2022
AI Practitioner Since
Multi
AI Businesses Built
100+
Articles Published
MA
Co-Founder · AI Implementation and Technical Strategy
Morten Andersen
AI practitioner since 2022 · Building multiple AI-powered businesses

Morten co-founded AI Advisory Practice with Fredrik Filipsson, bringing direct production AI experience to enterprise advisory. He has been building AI-powered businesses since 2022, giving him first-hand knowledge of what enterprise AI implementation actually requires beyond what frameworks and research papers describe.

His advisory focus covers AI implementation architecture, MLOps platform selection, data strategy, and the technical governance structures that allow AI programmes to operate reliably at scale. He bridges the gap between strategic intent and technical execution.

AI Implementation MLOps Data Strategy AI Architecture AI CoE
2022
AI Practitioner Since
Multi
AI Businesses Built
100+
Articles Published
Founders

The practitioners leading your engagement

Every engagement is led by a founder. No handoffs to junior analysts. The advisor you meet is the advisor who does the work.

FF
Co-Founder · AI Strategy and Advisory
Fredrik Filipsson
Enterprise AI strategist · Building AI driven businesses since 2022

Fredrik leads AI strategy, AI readiness assessment, and AI vendor selection engagements at this practice. His focus is helping enterprise leaders move from AI ambition to production programmes that deliver measurable business outcomes, without paying for vendor hype or junior analyst learning curves.

Before co-founding this practice, Fredrik spent fifteen years advising enterprise organisations on software strategy, technology vendor selection, and enterprise transformation programmes. His engagements have spanned financial services, manufacturing, retail, healthcare, and the public sector across Europe and North America.

AI Strategy Vendor Selection AI Readiness AI Governance Transformation
15+yrs
Enterprise Advisory
EU and NA
Geographic Reach
View
Full Bio
MA
Co-Founder · Implementation and Architecture
Morten Andersen
Enterprise AI implementation specialist · MLOps and architecture focus

Morten leads AI implementation, AI CoE design, generative AI, and data strategy engagements at this practice. His focus is moving AI systems from proof-of-concept into production, with the MLOps discipline, data foundations, and architectural choices that determine whether AI delivers business value at scale.

Before co-founding this practice, Morten spent more than a decade building enterprise data platforms, ML infrastructure, and production AI systems for organisations across financial services, manufacturing, and the public sector. He works across Azure, AWS, GCP, and hybrid cloud architectures, with particular depth in regulated industries.

AI Implementation MLOps AI CoE Data Strategy Architecture
10+yrs
AI Implementation
Multi-cloud
Azure, AWS, GCP
View
Full Bio
Specialist Bench

Domain specialists, selected per engagement

Founder-led engagements are extended with a vetted bench of senior specialists selected on a per-engagement basis. Where your programme needs depth we do not already carry in-house, we bring in a named specialist for that scope and name them in the statement of work.

A
AI Data Engineering
Senior data platform architects for AI-ready data infrastructure at enterprise scale. Azure Synapse, Databricks, Fabric, Snowflake, and hybrid cloud patterns for regulated workloads.
B
AI Governance and Regulatory
Senior advisors covering EU AI Act, DORA, NIST AI RMF, and sector-specific regulatory frameworks. Model risk, algorithmic bias assessment, and board-level AI governance.
C
Sector Depth
Named specialists in financial services, manufacturing, healthcare, public sector, retail, and professional services. Clinical informatics, HIPAA-compliant AI, and regulated deployment experience available on request.
D
AI Change Management and Adoption
Senior organisational change advisors for AI adoption programmes at scale. Workforce upskilling, operating-model redesign, and adoption measurement frameworks.
Specialist names, credentials, and references are shared at the statement-of-work stage so you can vet the exact people who will work on your engagement.
Engagement Model

How we staff client engagements

Our staffing model is designed around one principle: your organization deserves the senior practitioner on every call, not just the first one.

01
Named partner assigned at intake
Every engagement is assigned a named senior partner before work begins. That partner leads your engagement personally from assessment through delivery. No surprise handoffs after the sales call.
02
Partner access throughout the engagement
Senior partner availability is built into our engagement structure. You have direct access to your partner via scheduled working sessions, ad hoc conversations, and async review of materials. No routing through account managers.
03
Domain specialists on demand
When your engagement requires depth in a specific domain such as healthcare AI regulation or large-scale MLOps infrastructure, we bring in the relevant associate advisor. You benefit from the breadth of the practice without paying for the full bench.
04
Maximum 4 concurrent engagements per partner
Senior partners carry a maximum of four concurrent client engagements. This is a hard constraint, not an aspiration. It ensures your engagement receives the senior attention it deserves, and it protects the quality of our work.
05
No junior team members on delivery
We do not use junior analysts to reduce engagement cost and then claim senior oversight. If a deliverable is going to your organization, it was produced by a senior practitioner. This limits our scale intentionally. That is a trade-off we accept.
06
Knowledge transfer is built into every engagement
Every engagement includes explicit knowledge transfer sessions designed to leave your team more capable than when we arrived. We document decisions, build internal playbooks, and train your people. The goal is your independence from advisors, including us.
Work With Our Team

Every engagement led by a senior practitioner

Start with our free AI Readiness Assessment to understand where your organization stands, then connect with the partner best suited to your challenge.