As artificial intelligence becomes increasingly integrated into healthcare, public administration, finance, and daily life, Europe faces a central challenge: how to scale AI systems that are not only powerful, but also trustworthy, transparent, and genuinely human-centric. This balance is difficult to achieve at small scale, and it becomes significantly harder when AI moves from controlled pilots into large, complex environments.
The TANGO project offers an instructive lens on this challenge. Combining cognitive science, explainable AI, and hybrid human–machine decision-making, TANGO aims to build systems where AI supports, rather than replaces, human judgement. Yet the project also highlights a broader truth: trustworthy AI cannot be scaled through technology alone. It requires a strong ecosystem around it.
Trustworthy AI at scale: where the real challenges lie
Through the TANGO case studies and partner collaboration, several ecosystem-wide obstacles become clear:
- Translating cutting-edge research into practical, usable tools
Innovative models and methods often begin in laboratory settings, supported by researchers with deep domain knowledge. But scaling trustworthy AI means simplifying complexity so that hospitals, banks, public agencies, or SMEs can adopt solutions confidently. This translation layer, turning theory into practice, is one of Europe’s most persistent challenges.
2. Building user trust through clarity and explainability
Human-centric AI is not only about what systems do, but how people feel about using them. Professionals making sensitive decisions, for example in health or social services, need to understand:
- what information the AI uses,
- why it suggests a particular action, and
- how much confidence they should place in its output.
TANGO’s focus on cognition-aware explainable AI directly addresses this need, but scaling such approaches requires training, documentation, and supportive interfaces.
3. Fragmented adoption pathways across Europe
Different sectors, countries, and institutions use different processes, regulations, and infrastructures. This fragmentation slows down adoption and makes it difficult to scale AI ethically and reliably across borders. TANGO’s consortium, which brings together universities, SMEs, public-sector partners, and research networks, shows how cross-country collaboration can mitigate this fragmentation.
Opportunities emerging from the TANGO ecosystem
Despite the challenges, several promising opportunities emerge from TANGO’s approach:
- Cross-disciplinary collaboration as a strength
TANGO’s mix of cognitive scientists, AI researchers, domain experts, and innovation networks creates a powerful environment for scaling responsible AI. Each discipline contributes part of the trust equation, helping shape solutions that are both technically advanced and socially grounded.
2. Real-world case studies as scaling blueprints
By deploying hybrid decision-making systems in healthcare, public policy, and financial inclusion, TANGO generates replicable patterns that other European organisations can follow. This helps Europe move toward practical, sector-specific pathways for AI adoption.
3. Alignment with Europe’s regulatory vision
The upcoming AI Act emphasises transparency, risk management, human oversight, and trustworthy design, all central to TANGO’s objectives. As a result, TANGO’s work can inform how organisations prepare for compliance while still innovating.
The role of innovation ecosystems, 28DIGITAL, and the project partners
Scaling trustworthy AI also depends on strong innovation ecosystems. Partners like 28DIGITAL, which connect research outcomes with pan-European networks of innovators, SMEs, and public organisations, help ensure that TANGO’s insights do not remain confined to academic environments. Their role in supporting adoption pathways, stakeholder engagement, and best practices for deployment strengthens the entire project.
Similarly, TANGO’s diverse partners, from leading universities such as UNITN and UPC to specialist SMEs and public institutions involved in the case studies, each contribute unique competencies. Together, they create an ecosystem where cognitive models, software engineering, domain knowledge, user needs, and deployment realities can converge. Without this range of expertise and infrastructure, scaling trustworthy AI in Europe would be significantly more difficult.
Looking ahead: the ecosystem mindset
Scaling trustworthy AI is not only a research challenge, it is an ecosystem challenge. It requires coordinated effort across policy, research, users, and deployment infrastructures, exactly the type of collaboration embodied in TANGO.
As Europe advances toward a more responsible AI future, the lessons and structures emerging from TANGO provide a valuable reference point for how human-centric AI can be scaled safely, effectively, and with meaningful impact.
Written by: Ben Colson, 28DIGITAL