Strategic AI Implementation & Complex Programme Leadership

​

My experience includes senior coordination and implementation roles in highly technical and interdisciplinary projects, such as:

 

Advanced Scientific and Technological Domains

​

• Advanced microelectronics and enabling technologies, supporting Europe-wide research and innovation ecosystems where precision coordination, structured reporting, and quality assurance were essential to ensure coherence across research institutions, industry actors, and public stakeholders.

• Climate change and sea-level impact research, contributing to large scientific initiatives analysing environmental risk, long-term modelling, and policy-relevant evidence generation, where rigorous data governance and methodological consistency were critical.

• Digital learning, education, and applied scientific methodologies, including the design and implementation of large-scale digital learning frameworks, evidence-based pedagogical models, and applied research dissemination across European networks.​

 

Across these domains, I was not acting as a subject-matter researcher alone, but as a systems architect and implementation lead, responsible for translating scientific ambition into operational reality.

 

Large-Scale Coordination & Networks of Excellence

​

In these scientific and technical programmes, my role consistently involved:

• Coordinating Europe-wide networks of excellence, bringing together universities, research institutes, industry partners, NGOs, and public authorities across multiple countries.

• Designing governance and coordination frameworks that enabled distributed actors to operate coherently while respecting institutional autonomy and disciplinary diversity.

• Creating quality management, monitoring, and reporting systems aligned with European Commission standards, ensuring traceability, accountability, and comparability across work packages and partners.

• Structuring knowledge flows, documentation practices, and shared operational tooling to support long-term collaboration beyond individual funding cycles.​

 

These experiences required advanced systems thinking, process engineering, and institutional coordination skills — competencies that directly translate into the challenges organisations now face when deploying AI at scale.

 

Participatory Democracy & Societal Systems (Continuity, Not Replacement)

​

Alongside scientific and technical programmes, I have led and contributed to participatory democracy and governance initiatives, including:

• Participation design and implementation for Europe-wide citizen deliberations, including the Conference on the Future of Europe.

• Development of inclusive engagement methodologies, foresight exercises, and youth participation frameworks.

• Deployment of digital platforms and data-supported participation tools, enabling large-scale qualitative input collection, synthesis, and reporting.

 

This work reinforced my expertise in human-centred systems, collective sense-making, and governance under political and societal constraints — a critical counterbalance to purely technical approaches to AI.

 

Transition to AI Automation & Agentic Systems

​

Over the past year, I have systematically extended my professional practice into AI automation, AI agents, and agentic workflows, beginning with the automation of my own complex professional activities.

This includes:

• Automating knowledge-intensive workflows involving documentation, analysis, reporting, and coordination.

• Designing AI agents that support task execution, information retrieval, structured synthesis, and workflow coordination.

• Building agent-orchestrated systems that mirror real organisational processes, including feedback loops, escalation logic, and performance monitoring.

 

This transition is not a career pivot, but a technical evolution of long-standing expertise in process design, coordination, and governed execution.

Current AI-Related Capabilities & Services

I now support organisations across sectors — including research consortia, public institutions, NGOs, and professional services — with:

 

AI Implementation & Operationalisation

• Embedding AI into existing organisational processes

• Designing automation pipelines aligned with governance requirements

• AI-augmented analytics, reporting, and decision-support systems

AI Agents & Orchestrated Workflows

• Design and deployment of AI agents for structured task execution

• Multi-agent orchestration for complex operational sequences

• Monitoring, evaluation, and improvement of agent performance

Governed & Accountable AI Systems

• AI systems designed with auditability and traceability

• Alignment with regulatory, ethical, and organisational constraints

• Documentation of decision logic and operational assumptions

Organisational Capability Development

• Readiness assessments for AI adoption

• Leadership and team support during implementation

• Progressive capability building through real operational use cases

 

Methodology & Way of Working

 

My approach integrates:

• Systems Thinking — treating AI as part of a broader organisational ecosystem

• Process Architecture — decomposing complexity into governable components

• Governance-First Design — accountability and compliance by design

• Data-Informed Iteration — continuous refinement based on evidence

• Collaborative Implementation — working with, not around, existing teams

​

Why This Background Matters for AI Today

​

European scientific and governance programmes represent some of the most demanding operational environments: multi-actor, regulated, high-accountability, and continuously evolving.

These are the same conditions under which AI must now operate.

My background ensures that AI systems are implemented as reliable, governed, and durable operational assets, not experimental add-ons.

 

Forward-Looking Practice: Continuous Improvement Through Client Engagements

I treat each engagement as both delivery and learning: refining architectures, strengthening methodologies, and building reusable components that improve future implementations.
 

I operate as a senior systems practitioner applying AI where it actually works — improving capability through real projects, measurable outcomes, and disciplined execution.