From Pilot to System: Where Living Labs Break Down
Last updated: April 2026
Across EU projects, Living Labs are often treated as proof that a solution is ready to scale.
In reality, that’s rarely the case.
What Living Labs actually demonstrate
Living Labs are designed to test solutions in real-world settings, involve users and stakeholders, and bridge research and implementation.
They are effective at demonstrating feasibility, generating local engagement, and producing evidence under coordinated conditions.
Under these conditions, solutions work.
What they are often mistaken for
Successful pilots are frequently interpreted as proof of scalability and signals of system readiness.
In practice, they’re not. They demonstrate what works when alignment is engineered — not when systems operate under their own constraints.
What changes outside the lab
Scaling introduces conditions that Living Labs do not replicate: competing incentives, fragmented decision-making, cost exposure, and operational variability.
What works under coordination does not automatically work under real system conditions.
The structural limitation
Living Labs are built on temporary alignment, project-based funding, and defined timelines. Systems operate through persistent incentives, institutional constraints, and continuous decision-making.
The two logics don’t quite match.
Where scaling breaks
The problem is rarely technical. It appears when project coordination ends, funding support disappears, and responsibility shifts to system actors. At that point, continuation depends on who pays, who benefits, and who is accountable.
These questions are often deferred during pilot design — and become critical at scale.
The role of programmes
Programmes like Horizon Europe rely on Living Labs to validate approaches, demonstrate feasibility, and accelerate testing. They are effective at producing working examples, but are less effective at ensuring those examples persist beyond the project.
The implementation gap
Between pilot and scale, a different question applies: not “Does it work?” but “Does the system have a reason to keep it working?”. If incentives, ownership and operational responsibility are not aligned, results remain local — regardless of performance.
Why this matters
Living Labs are increasingly used as evidence of success, justification for replication, and signals of readiness. If scaling conditions are not addressed, these signals risk being misinterpreted.
Bottom line
Living Labs reduce uncertainty. They do not resolve system constraints.
Many successful pilots show coordination — not system readiness.
Until project design accounts for long-term incentives, ownership beyond funding cycles, and operational continuity, scaling will remain conditional — not automatic.