Mara Balestrini
Technology-first approaches to AI and digital transformation tend to produce systems that solve technical problems, not organisational or civic ones. When the people affected by those systems have no stake in how they are designed or governed, trust erodes and adoption fails. The gap between deployment speed and governance readiness is where most digital strategies break down.
When AI and data strategies outpace their governance, Mara Balestrini – HCI researcher, former AI policy advisor to the Spanish government, and former CTO of the Inter-American Development Bank’s innovation lab – helps organisations design the governance frameworks needed to sustain them.
Full Profile
Why organisations work with Mara Balestrini
- Her governance frameworks are not conceptual – the Bristol Approach and the City Commons Framework (published at ACM CHI 2017) were developed with real institutions, in real urban systems, and have influenced urban data policy beyond their original contexts. Organisations get tested models, not white papers.
- She has operated at the level of national AI policy, serving as cabinet advisor to Spain’s Secretary of State for Digitalization and AI. That gives her a direct, non-theoretical understanding of how regulatory and governance frameworks are made – and where they typically fall short.
- Her tenure leading digital transformation and responsible AI at IDB Lab, including the fAIr LAC+ initiative, means she has applied these frameworks inside a multilateral institution managing large-scale technology programmes across 23 countries. The challenges she addresses are not hypothetical.
- Her research sits at the intersection of HCI, IoT, and responsible AI governance – cited over 1,500 times and recognised by ACM CHI, ACM CSCW, and Ars Electronica. That academic grounding gives organisations the analytical vocabulary to move from AI deployment to AI accountability.
- As co-founder of SalusCoop, the first Spanish cooperative for citizens’ health data, she has demonstrated that the data governance models she advocates are viable as operating organisations, not just policy positions.
Biography highlights
- PhD in Computer Science, Intel Collaborative Research Institute on Sustainable Connected Cities (ICRI-Cities), University College London
- Former CTO and Digital Transformation Lead, IDB Lab (Inter-American Development Bank Innovation Laboratory); contributor to fAIr LAC+, a dedicated initiative on responsible AI adoption across Latin America and the Caribbean
- Currently CEO of LNET, the global blockchain infrastructure nonprofit and executing agency for IDB Lab, operating across 23 countries
- Former cabinet advisor to Spain’s Secretary of State for Digitalization and Artificial Intelligence
- Former CEO and Partner, Ideas for Change; originator of the City Commons Framework (ACM CHI 2017) and co-developer of the Bristol Approach with Bristol City Council
- Co-founder, SalusCoop, the first Spanish cooperative for citizens’ health data
- Over 30 academic publications; 1,584+ citations on Google Scholar; awards from ACM CHI, ACM CSCW, and Ars Electronica
- Covered by BBC, The Guardian, the Financial Times, and El País; TEDx speaker (TEDxCordoba, 2018); Research Fellow, ESADE EsadeGov Center for Public Governance
Biography
Mara Balestrini’s core argument is that AI and digital transformation strategies fail not because the technology is wrong, but because the governance is built after the fact, not before. From European Commission-funded research to Spain’s national AI policy office to the Inter-American Development Bank, she has spent two decades building the frameworks to reverse that sequence.
Her doctoral work at UCL’s Intel Collaborative Research Institute on Sustainable Connected Cities produced the City Commons Framework, published at ACM CHI 2017 – a model for embedding citizen governance into data-driven systems from the design stage. She co-developed the Bristol Approach with Bristol City Council and KWMC, a commons-based methodology for participatory sensing that reframes smart city investment around citizen priorities rather than technical capability. She also coordinated Making Sense, a European Commission H2020-funded project that turned community-owned environmental sensors into a platform for civic action at scale.
From that research base she moved into national policy, serving as cabinet advisor to Spain’s Secretary of State for Digitalization and AI – one of the few HCI researchers to have held a position at that level of government. She then took the role of CTO and Digital Transformation Lead at IDB Lab, where she contributed to fAIr LAC+, the Inter-American Development Bank’s initiative on responsible AI adoption across Latin America and the Caribbean. She is currently CEO of LNET, the global blockchain infrastructure nonprofit that evolved from LACChain and now connects governments, multilateral organisations, and the private sector across 23 countries.
Her research, cited over 1,500 times, spans HCI, IoT, and responsible AI governance. It has been recognised by ACM CHI, ACM CSCW, and Ars Electronica, and covered by the BBC, the Financial Times, The Guardian, and El País.
Key speaking topics
- Responsible AI governance and institutional accountability
- Digital transformation strategy for public and civic institutions
- Civic technology and citizen participation in technology design
- Smart cities and urban data governance
- Data rights and cooperative data models
- Emerging technology governance (blockchain, Web3) for institutions
- AI policy and regulation from a practitioner perspective
Ideal for
- Chief Digital Officers and Chief Data Officers navigating AI governance, data strategy, and responsible technology deployment
- Public sector executives and government leads managing AI policy, digital transformation, or regulatory frameworks
- Boards and senior leadership teams weighing institutional accountability in large-scale AI or data programmes
- Transformation leads and innovation directors in multilateral organisations, development banks, or international institutions
Audience outcomes
- A working distinction between AI deployment and AI governance, and why confusing the two produces predictable failures at scale
- Familiarity with tested, named governance frameworks (Bristol Approach, City Commons Framework, fAIr LAC+) that can be adapted beyond urban or government contexts
- A clearer understanding of where current AI and digital transformation strategies most commonly break down, and what designing governance in from the start actually looks like in practice
- An informed view of how national AI policy is being shaped, drawn from direct government advisory experience rather than secondary analysis
- Practical reference points for designing responsible AI strategies that are accountable to stakeholders before they are deployed, not after