AI REDGIO 5.0: Building a sustainable European Ecosystem for AI-driven Manufacturing
As the AI REDGIO 5.0 project phase concludes, it leaves in place over six years of European collaboration to strengthen digital innovation in manufacturing. Over this period, the initiative has evolved from a network of Digital Innovation Hubs (DIHs) into a fully interconnected ecosystem comprising European Digital Innovation Hubs (EDIHs), Didactic Factories (DFs), and Testing and Experimentation Facilities (TEFs). At the heart of this evolution lies the METHODIH methodology and its D-BEST framework, which establish a shared structure for service delivery across Data, Business, Ecosystem, Skills, and Technology. This common approach enhances transparency, alignment, and collaboration across the ecosystem. The project also introduced Collaboration Corridors, enabling hubs to co-develop and scale services together, strengthening trust and reducing fragmentation within the innovation landscape. Long-term continuity and impact are supported through DIH4INDUSTRY and the AI REDGIO Ecosystem Portal, ensuring sustained visibility, exploitation, and collaboration well beyond the project’s duration.
Networks and People
The networks of European Digital Innovation Hubs (EDIHs) and Didactic Factories (DFs) developed within the AI REDGIO 5.0 project reach an important milestone as the project phase comes to a close. What ends, however, is not simply a project lifecycle, but a phase within a much longer journey of collaboration that began more than six years ago with the AI REGIO initiative.
AI REGIO laid the foundations for many of the concepts, relationships, and collaborative practices that later evolved into AI REDGIO 5.0. From its early experimental phase, a growing ecosystem emerged, gradually expanding in scope, ambition, and impact. Today, the EDIH and Didactic Factory networks bring together more than 50 partners working toward a shared objective: strengthening the digital transformation of European manufacturing.
Yet these networks are not defined by numbers alone. At their core are people and organisations committed to cooperation, knowledge sharing, and mutual support. Over time, collaboration extended well beyond initial project objectives. Professional relationships evolved into lasting partnerships, often underpinned by trust, shared values, and personal connections. These intangible elements, though difficult to measure, form the true foundation for long-term cooperation and future alliances.
Throughout the project, strategies for structured inter-regional collaboration were explored through the development of Collaboration Corridors. Discussions with network members consistently highlighted that while technical expertise is essential, trust and shared vision are equally critical to making collaboration effective and sustainable.
As AI REDGIO 5.0 transitions beyond its project phase, both networks remain active. The EDIH network continues through initiatives such as EDIH4MANU and the broader EDIH 2.0 framework, while the Didactic Factory network will sustain its activities and further strengthen connections with Testing and Experimentation Facilities (TEFs).
Origins: From AI REGIO to AI REDGIO 5.0
The origins of AI REDGIO 5.0 are deeply rooted in AI REGIO (2021–2023), which represented an experimental phase for collaborative AI-driven manufacturing innovation. At that time, the network comprised 13 Digital Innovation Hubs (DIHs), operating before the European Digital Innovation Hub framework was fully established.
Despite its relatively limited size, AI REGIO succeeded in validating a shared vision: effective digital transformation in manufacturing requires not only technological excellence, but also cross-regional cooperation and access to real-world experimentation environments. Trust was built, concepts were tested, and collaboration models were refined within a relatively compact ecosystem.
AI REDGIO 5.0 (2023–2025) marked the scaling phase. The network transitioned from DIHs to a broader, more formalised EDIH ecosystem aligned with the Digital Europe Programme. This transition was not merely semantic, but reflected a qualitative evolution in scope, responsibilities, and strategic alignment.
The EDIH network expanded from 13 to 22 members, bringing new regions, competencies, and thematic priorities. Many original DIH partners remained active, ensuring continuity and knowledge transfer, while new EDIHs joined as coordinators or key contributors. Several partners now directly coordinate operational EDIHs, embedding the project’s collaborative model into Europe’s long-term digital innovation infrastructure.
A similar evolution occurred within the Didactic Factory network. From 20 facilities in AI REGIO, the network grew to 33 in AI REDGIO 5.0, incorporating advanced infrastructures such as smart factories, circular production labs, additive manufacturing pilots, and energy-efficient production systems. This expansion combined continuity with diversification, reinforcing the role of Didactic Factories as shared European assets for experimentation and learning.
Together, these developments illustrate a clear trajectory: AI REGIO validated collaboration in a compact network, while AI REDGIO 5.0 scaled and consolidated this approach within a mature, pan-European ecosystem. This evolution does not represent an endpoint, but a foundation for future initiatives, including the next EDIH programming phase.
The role of EDIHs, Didactic Factories, and TEFs in the project Ecosystem
Within the AI REDGIO 5.0 ecosystem, EDIHs, Didactic Factories, and Testing and Experimentation Facilities play complementary and mutually reinforcing roles.
EDIHs act as access points and system integrators, embedded in regional ecosystems while connected at European level. Beyond service provision, they coordinate activities, align regional and European priorities, and facilitate the circulation of knowledge, resources, and opportunities. Through structured service portfolios, EDIHs support SMEs in navigating complex digital transformation pathways, offering expertise in AI, data, cybersecurity, and advanced manufacturing, alongside “test-before-invest” services.
Didactic Factories provide the experiential dimension of the ecosystem. These learning factories, pilot plants, and advanced laboratories enable hands-on experimentation, training, and demonstration in real or simulated industrial environments. They bridge theory and practice, allowing users to explore AI-enabled solutions safely, build skills, and gain confidence before deployment.
TEFs complement both by offering large-scale validationand industrial readiness. They support the testing and experimentation of AI and robotics solutions in real-world industrial conditions, enabling the transition from pilot to market-ready implementation.
Together, these three pillars create a continuous innovation journey: EDIHs identify needs and coordinate pathways; Didactic Factories enable learning and early experimentation; TEFs validate solutions at industrial scale. This integrated approach ensures that digital transformation is addressed holistically, encompassing skills, technology, and adoption.
A Methodology to sustain and strengthen the Ecosystem
Six years of collaboration highlighted a critical insight: innovation networks do not mature by chance. They require shared frameworks, structure, and tools to support growth, complexity, and sustainability. This need led to the development and refinement of the METHODIH methodology.
Originally conceived to support DIHs themselves, METHODIH provides a strategic and operational framework to analyse how hubs function, create value, collaborate, and sustain their impact. Rather than prescribing fixed models, it acts as a diagnostic and reflective tool, helping hubs understand strengths, gaps, and development priorities.
METHODIH evolved iteratively through multiple projects, including AI REGIO and AI REDGIO 5.0. Its application within AI REDGIO 5.0 was particularly significant, as it was tested across a network of mature EDIHs with complex structures, multiple service lines, and strong policy linkages.
To address this complexity, the methodology expanded from its original three pillars to five:
Service Portfolio
Customer Journeys
Service Pipelines and Success Stories
Collaboration Corridors
Business Model
This structure reflects a key lesson: effective ecosystems rely not only on services and funding, but also on shared impact narratives and structured collaboration.
The D-BEST framework: structuring services for a collaborative AI Ecosystem
At the core of METHODIH lies the D-BEST framework, which structures EDIH service portfolios across five dimensions: Data, Business, Ecosystem, Skills, andTechnology. D-BEST provides a shared language that enables comparability, transparency, and strategic alignment across hubs.
Internally, it helps EDIHs assess their positioning, identify strengths and gaps, and explore complementarities with peers. Externally, it simplifies access for SMEs and stakeholders, offering a clear overview of available services and reducing fragmentation in the innovation support landscape.
Data and Technology services are particularly critical in AI ecosystems, supporting the full data lifecycle and reducing investment risks through testing and validation. Skills services ensure organisational and human readiness, while Ecosystem and Business services enable scaling, financing, and long-term sustainability.
For Didactic Factories, the framework was extended to DR-BEST, adding a Remotizationdimension to capture services delivered remotely. These include Data Spaces, ICT as a Service, Digital Twins, and Assets as a Service, significantly expanding access to experimentation and training beyond physical constraints.
Collaboration Corridors: from service awareness to structured cooperation
Collaboration Corridors represent one of the most distinctive contributions of AI REDGIO 5.0. Building on service portfolio awareness, they provide structured mechanisms for inter-regional cooperation among EDIHs.
Rather than expecting hubs to offer all services independently, Collaboration Corridors leverage complementarities within the network. Three collaboration scenarios are defined: co-developing new services, jointly delivering existing services, and matchmaking customers to specialised hubs.
A structured methodology guides hubs through exploration, initiation, expansion, and consolidation phases, supported by data-driven compatibility analysis. This approach reduces uncertainty, reinforces trust, and enables scalable cooperation without fragmentation.
For SMEs, Collaboration Corridors improve access to mature, high-quality services regardless of location. For the ecosystem, they support specialisation, reuse, and long-term sustainability beyond project boundaries.
Two complementary Portals to sustain visibility and Exploitation of results
To ensure long-term visibility and exploitation, AI REDGIO 5.0 relies on two complementary digital platforms.
DIH4INDUSTRY is a public-facing portal focused on EDIH service portfolios. Designed for SMEs, public organisations, and innovation stakeholders, it presents services in a clear, accessible way, enabling comparison and matchmaking across hubs.
The Ecosystem Portal has a broader scope, integrating EDIHs, Didactic Factories, and TEFs, and showcasing the full application of METHODIH. It supports learning, governance reflection, and replication, serving policymakers, ecosystem builders, and innovation professionals.
Together, these portals transform project outputs into living resources that remain accessible, usable, and expandable.
Legacy: what remains and what comes next
As AI REDGIO 5.0 moves beyond its project phase, its legacy lies in a resilient ecosystem built on trust, shared tools, and sustained collaboration. Networks of EDIHs, Didactic Factories, and TEFs remain active, equipped with methodologies, digital platforms, and strong relationships.
METHODIH, D-BEST, and Collaboration Corridors provide reusable frameworks for future initiatives, while the portals ensure visibility and continuity. Most importantly, AI REDGIO 5.0 has demonstrated that digital transformation in manufacturing is strongest when technology, people, and structures evolve together.
What remains is not an ending, but a foundation: an ecosystem ready to adapt, collaborate, and grow, supporting Europe’s AI-driven manufacturing transformation well beyond a single funding cycle.