What if the Best AI Team is not Yours?

European procurement teams are writing job descriptions for AI engineers who do not exist. Germany will see 70% of its AI positions remain unfilled by 2027, with hiring delays already stretching to six months (Bain, 2025; CBI, 2024). France watched hiring challenges surge from 19% in 2018 to 80% in 2023 (CBI, 2024). Ireland reports 81% of employers can't find AI talent (CBI, 2024). These are not temporary hiring challenges. The specialists organizations need simply are not entering the market fast enough.

Meanwhile, the conventional solution costs between €400,000 and over €1 million annually for a small in-house AI team (Coherent Solutions, 2024; DesignRush, 2025). By the time your team is operational, the competitive landscape has shifted and you're solving problems that may no longer be the right problems to solve.

If you've studied technology markets for any length of time, you recognize the pattern. Craigslist was once a single platform handling jobs, housing, services, and personal connections. Within a decade, that integrated offering had been carved into fifty specialized companies. Airbnb took housing while Indeed took jobs. Each unbundled piece proved more valuable than remaining inside the original bundle. The forces driving that unbundling were straightforward: the integrated solution had become too expensive, too slow, and too rigid for what the market actually needed.

The same dynamic transformed enterprise software into SaaS point solutions and on-premise servers into AWS. When maintaining an integrated solution becomes more costly than the flexibility it provides, markets unbundle. That gap, in the case of AI teams, has become impossible to ignore.

Why the bundle breaks

For the past decade, "we need AI capability" meant one thing: build a team. Recruit 4-6 people across multiple specializations, commit hundreds of thousands to over a million euros annually, and accept that hiring delays can stretch to six months per role in markets like Germany (CBI, 2024; DesignRush, 2025).

Three structural forces make that model increasingly unsustainable.

First, the talent market broke. Across Europe, organizations face severe shortages of AI specialists, from ethics researchers to data scientists and compliance experts. When candidates do surface, compensation has climbed dramatically. AI engineer salaries increased from $231,000 in August 2022 to $300,600 by March 2024 (Levels.fyi, 2024; Qubit Labs, 2025). Even at those rates, retention remains uncertain as professionals migrate to higher-paying opportunities elsewhere (CBI, 2024).

Second, the speed requirements changed. AI capabilities evolve on roughly six-month cycles. An organization working on an extended build cycle is structurally mismatched to that pace. By the time your team reaches operational capability, you're solving yesterday's problems with approaches that may already be outdated. If assembling your team takes extended periods, you're locked into perpetual catch-up where your planning cycle is longer than the technology cycle.

Third, the economics stopped working. The traditional model bills 40 hours per week, 52 weeks per year, per team member, yet AI needs a spike during new product development and plateau during optimization. When you map fixed costs to variable demand, you create systematic inefficiency, and each departure triggers another lengthy replacement cycle during which knowledge walks out and projects stall.

What's emerging

The market is responding. Fractional AI, founded in February 2024, positions explicitly around "AI transformation powered by engineering excellence" (Fractional AI, 2024). CloudKitect offers a "Fractional AI Team" product on AWS Marketplace, messaging directly against "$500K/year AI headcount" (AWS Marketplace, 2025). Across Europe, specialists have built businesses around this model. Here at AAI Labs, we've built our Deployed AI Engineering Teams offering around similar principles—European enterprises navigating GDPR and AI Act compliance alongside technical delivery.

The shift extends beyond AI. The global population of fractional leaders doubled from 60,000 to 120,000 in just two years (Frak Institute, 2024), while industry analysts project continued growth in fractional hiring adoption among businesses seeking flexible access to executive expertise (Umbrex, 2025). Traditional consulting itself is reorganizing around pay-for-outcome models rather than hourly rates (Expert Network Calls, 2025).

What unbundled looks like: organizations moving from owning AI talent to accessing AI capability. Converting substantial capital expenditure to monthly operational expenses scaled to actual usage. Matching capability to project phase rather than maintaining permanent teams sized for peak capacity. The parallel to cloud computing is direct.

The shift continues

Markets unbundle when structural economics shift. Talent scarcity and utilization mismatches have made permanent AI teams unsustainable for most organizations, and the market is responding to these conditions with increasing velocity. The talent gap persists and by most projections will widen, while speed advantages continue to compound for organizations that can deploy capability quickly. These fundamentals suggest the unbundling will deepen rather than reverse, which means AI teams will continue fragmenting into specialized services. Each organization faces the same question: how to position itself within that unbundled reality, and what capabilities to own versus access.

References

AWS Marketplace. (2025). Fractional AI Team - CloudKitect. Retrieved from https://aws.amazon.com/marketplace/pp/prodview-qklbmjs2evmia

Bain. (2025). AI Talent Shortage Report: Germany 70% job gap projection by 2027. Retrieved from https://aiwire.net/2025/03/26/ai-talent-shortage-threatens-corporate-ambitions-says-bain

CBI. (2024). The European market potential for AI software development services. Retrieved from https://www.cbi.eu/market-information/outsourcing-itobpo/artificial-intelligence-ai-and-machine-learning-ml/market-potential

Coherent Solutions. (2024). AI Development Cost Estimation: Pricing Structure, Implementation ROI. Retrieved from https://www.coherentsolutions.com/insights/ai-development-cost-estimation-pricing-structure-roi

DesignRush. (2025). How Much Does AI Cost in 2025? A Breakdown for Smarter Business Decisions. Retrieved from https://www.designrush.com/agency/ai-companies/trends/how-much-does-ai-cost

Expert Network Calls. (2025). Consulting Industry Trends and Outlook for 2025. Retrieved from https://expertnetworkcalls.com/71/consulting-industry-trends-outlook-2025

Frak Institute. (2024). State of the Fractional Industry Report: Global fractional leader growth data.

Fractional AI. (2024). About Us. Retrieved from https://www.fractional.ai/about-us

Levels.fyi. (2024). AI Engineer Compensation Trends Q1 2024. Retrieved from https://www.levels.fyi/blog/ai-engineer-compensation-q1-2024.html

Qubit Labs. (2025). AI Engineer Salary in 2025: Breakdown by Location, Experience, and Role. Retrieved from https://qubit-labs.com/ai-engineer-salary-guide/

Umbrex. (2025). Company Readiness: Deciding to Hire a Fractional Executive. Retrieved from https://umbrex.com/resources/fractional-executive-playbook/