Future Literacy AI
From AI ambition
to implementation.
Strategic AI advisory for governments, public institutions and industry.
We help decision-makers determine where AI creates real value, what capabilities and infrastructure are required, how it should be governed, and how to move from experimentation to implementation at scale.
From national AI policy and sector transformation to corporate use-case prioritisation, data and infrastructure readiness, governance and ecosystem development.
Fig. 01 — The AI stack
- 01Data
- 02Compute
- 03Models
- 04Organisations
- 05Infrastructure
- 06Economic & social value
Selected customers, partners & institutional environments
- 01
Deutsche Telekom
Next-generation telecom infrastructure pilot prioritisation across 6G and quantum technologies.
- 02
NTT DATA
Leading public-sector consortia delivering Spain’s National AI Strategy programmes and Spain Digital 2026, integrating NextGenerationEU digitalisation investments across government and strategic economic sectors.
- 03
Government of Spain
AI strategy, governance and implementation — from sector impact assessments and public-sector use-case mapping to AI governance architecture, industry consultation and support to Spain’s European AI policy work.
Selected engagements across commercial work, strategic partnerships and institutional programmes. Detailed track record below.
01 — The implementation gap
AI is no longer a technology question.
The challenge is execution.
Governments are defining national AI ambitions while trying to understand how adoption should happen across sectors.
Industry is under pressure to invest — but must decide where to invest, which use cases matter, what to build internally, what to procure, which risks to accept and how to scale beyond pilots.
At the same time, AI decisions increasingly create dependencies across data, compute, cloud, connectivity, talent, cybersecurity, regulation and technological sovereignty.
The question is no longer whether to adopt AI.
It is how to turn AI into productive capacity, institutional capability and measurable economic value.
That is where Future Literacy works.
02 — From experience to execution
We worked on AI strategy
before the generative AI cycle.
Future Literacy's capabilities originate in more than a decade of work at the intersection of emerging technology, government, industry and strategic transformation.
Our leadership has contributed to Spanish and European initiatives spanning AI policy, national digital transformation, AI governance, public-sector adoption, sector transformation, industrial strategy and frontier technologies.
Selected AI & digital policy track record — evidence index
01
National digital strategy
Spain Digital 2026
Members of the Future Literacy leadership team worked inside Spain's national digital-transformation environment, contributing to the update and implementation of Spain's national digital strategy.
Work included coordination across ministries, telecommunications operators and public-sector stakeholders, and the development of policy-monitoring and implementation mechanisms.
Government of SpainNational digital transformationPublic policy → execution02
National AI ecosystem & social consensus
Human-centred AI governance
Future Literacy led ecosystem, narrative and stakeholder work around a proposed national social consensus on artificial intelligence.
The initiative explored how citizens, experts, socioeconomic actors, industry and government could participate in defining acceptable boundaries and principles for AI deployment.
The work included analysis of international participatory-governance models — including approaches developed in Taiwan — and the design of mechanisms connecting public deliberation with Spain's emerging AI governance architecture.
This was not simply a communications exercise. It addressed a fundamental AI-policy problem:
How can technological adoption maintain public legitimacy while moving from abstract ethical principles towards operational governance?
03
AI regulation & European governance
From principles to institutions
Members of our team supported Spain's emerging AI governance and regulatory environment, including work connected with the institutional architecture surrounding Spain's AI supervisory capability and public-sector support during the development of the European AI regulatory framework.
This experience provides Future Literacy with a practical understanding of the interface between regulation, governance, institutions, industry and adoption.
RegulationGovernanceInstitutionsIndustryAdoption04
Sector AI transformation
What does AI actually change?
Future Literacy's team has worked on sector-level analysis of the impact of AI across strategically important parts of the economy.
The methodology examined short-term, medium-term and long-term transformation, AI use cases, business-model implications, productivity, employment and socioeconomic impact, privacy and digital rights, and implementation and policy implications.
Work included detailed analysis of the information and communications ecosystem, including telecommunications, digital information, information processing and media. Additional sector work has addressed strategic industries including energy and other major areas of the Spanish economy.
Methodology
- 01Sector
- 02Structural change
- 03AI use cases
- 04Short / medium / long term
- 05Economic + social + operational impact
- 06Policy / investment / implementation
05
AI for government
From use cases to public value
Our experience includes ecosystem orchestration around AI use cases for public services.
Future Literacy leadership also coordinated European ecosystem-building involving approximately 30 universities and public institutions around AI governance and public-sector transformation, contributing to work towards a European Centre of Excellence in AI for Public Services.
This gives us experience not only analysing AI adoption but working across the institutional ecosystem required to make adoption possible.
~30 universities & public institutionsEuropean ecosystemPublic services
03 — Two sides of the same transformation
One technology transformation.
Two decision environments.
Track A
For governments & public institutions
AI strategy & implementation
We help governments translate national AI ambition into sector priorities, institutional capability and executable programmes.
- 01
National & sector AI roadmaps
Translate strategic ambition into priorities, programmes, responsibilities and implementation pathways.
- 02
Sector AI impact assessments
Understand how AI will transform priority sectors across short-, medium- and long-term horizons.
- 03
Public-sector AI use-case mapping
Identify, structure and prioritise applications across ministries, agencies and public services.
- 04
AI governance & adoption frameworks
Move from high-level principles towards practical governance that enables responsible deployment.
- 05
AI ecosystem & capability mapping
Map domestic research, technology, industry, data, compute, talent and investment capabilities — and identify critical gaps.
- 06
Data, compute & sovereignty strategy
Determine what capabilities should be owned, controlled, accessed or partnered — and understand the strategic dependencies created by each choice.
- 07
Industry consultation & consensus building
Create structured mechanisms through which industry, research, citizens and government contribute to implementable AI policy.
- 08
International benchmarking
Translate lessons from European and international AI policy, regulation and deployment into local institutional realities.
Track B
For industry & strategic corporates
AI adoption & strategic transformation
Before investing in AI, decide where it actually matters. We work with boards, strategy teams, innovation functions and business units to determine where AI creates value and what it will take to deploy it responsibly at scale.
- 01
AI opportunity & use-case prioritisation
Map potential applications across the organisation and prioritise them according to business value, strategic relevance, implementation feasibility, data availability, technology maturity, risk, capability requirements and time to impact.
- 02
Build · buy · partner
Determine which AI capabilities should be built internally, procured, co-developed, accessed through partners or integrated into existing systems.
- 03
Data & infrastructure readiness
Assess whether the organisation has the data, compute, connectivity, architecture and organisational foundations required for deployment.
- 04
Governance & risk
Translate regulatory, operational, security and reputational requirements into practical AI decision frameworks.
- 05
Pilot → scale
Identify why promising pilots fail to become operational capabilities — and design the organisational, technical and ecosystem conditions required to scale them.
- 06
Technology & capability scouting
When the required capability does not exist internally, Future Literacy identifies and qualifies relevant technology providers, research partners and strategic capabilities internationally.
- 07
Government & ecosystem alignment
For strategic industries, AI transformation increasingly intersects with national infrastructure, regulation, incentives, standards and public policy. We help companies structure their requirements and translate operational experience into evidence-based engagement with government and ecosystem institutions.
- 08
Executive briefings & leadership sessions
Senior-level strategic sessions for boards, executive committees and strategic business units — framing what AI, compute, infrastructure and frontier technologies mean for the organisation's position, investment choices and decision agenda, and aligning leadership on priorities before capital and teams are committed.
04 — From use case to system
We don't start with the technology.
We start with the decision.
AI programmes fail when these decisions are treated separately.
Future Literacy works across the complete decision architecture — connecting business value, technology, infrastructure, governance, ecosystem and implementation.
Fig. 02 — Decision architecture
- 01Strategic priority
- 02Use case
- 03Value
- 04Data
- 05Compute / infrastructure
- 06Governance
- 07Build / buy / partner
- 08Deployment
- 09Scale
05 — AI, sovereignty & strategic value
AI investment is also
a sovereignty decision.
AI decisions create dependencies.
Future Literacy approaches technology investment through a broader strategic lens.
Dependency questions
- Q01Where is data stored?
- Q02Who provides compute?
- Q03Which models are used?
- Q04Who controls critical infrastructure?
- Q05Where does intellectual property accumulate?
- Q06Which capabilities remain domestic?
- Q07What happens when a foreign supplier becomes strategically indispensable?
Framework
Proven methodology for strategic investment
In 2026, Future Literacy contributed expert work to a Cotec-led framework developed and validated with 41 public and private organisations to evaluate strategic investment beyond conventional financial return.
- 41
- Public & private organisations
- 6
- Dimensions of strategic value
- 4
- Levels of analysis
- 38
- Types of value
Value dimensions
Where value is captured
The framework was designed to support ex-ante and ex-post investment decisions and to understand how strategic investments generate capabilities, knowledge, infrastructure, territorial effects and strategic autonomy beyond their immediate financial return. Future Literacy brings this broader understanding of value to emerging-technology investment and AI transformation.
06 — Industry connection
Connected to the industries
building the digital economy.
Future Literacy operates inside the technology and industrial ecosystems in which AI is being deployed.
Our founder serves as Vice President of the Innovation Commission of AMETIC, Spain's leading digital-industry association.
Through this ecosystem, and through Future Literacy's wider international work, we engage technology companies, telecommunications operators, infrastructure actors, research institutions, investors, government agencies and European institutions.
Our work has created engagement channels between startups, industry, public institutions, the European Commission, European technology ecosystems and strategic infrastructure actors.
This matters because AI transformation cannot be designed in isolation from the industries expected to deploy it.
Ecosystem domains
- 01AI
- 02Telecommunications
- 03Cybersecurity
- 04Digital infrastructure
- 05Strategic investment
- 06Quantum technologies
- 07Dual-use technologies
- 08Technological sovereignty
07 — Beyond today's AI
AI is becoming infrastructure.
We work on what for, how & what comes next.
The next transformation will not be driven by AI in isolation.
It will emerge from the convergence of artificial intelligence, advanced compute, telecommunications, energy systems, quantum technologies, cybersecurity, autonomous systems and critical infrastructure.
These systems are becoming increasingly interdependent. Compute requires energy. AI reshapes networks and infrastructure. Automation changes industrial systems. New architectures create new dependencies across technology, resources, security and sovereignty.
Future Literacy works across these intersections, applying a systems approach to understand not only what a technology can do, but the infrastructure, energy, capabilities and sustainability conditions required to deploy it at scale.
Fig. 03 — Convergence
- 01AI + advanced compute
- 02AI + telecommunications
- 03AI + quantum
- 04AI + cybersecurity
- 05AI + critical infrastructure
- 06Future networks
Convergence
From the frontier
From fiber to quantum:
The next generation of network capabilities
Future Literacy at Mobile World Congress 2026
María Luque, Founder & CEO of Future Literacy, joins experts from Deutsche Telekom T-Labs, Qunnect and TU Dresden to explore the transition of quantum networking from research to deployable telecommunications infrastructure.
The discussion examines entanglement-as-a-service, distributed quantum computing and sensing, security, field deployment and the roadmap towards scalable quantum networks.
Official session — Deutsche Telekom · MWC 2026
Field context
From research to deployed infrastructure.
The MWC 2026 discussion was contextualised by a real-world quantum teleportation demonstration by Deutsche Telekom T-Labs and Qunnect across 30 km of deployed fibre infrastructure, achieving more than 90% teleportation fidelity.
The demonstration provided a practical backdrop to the discussion: how quantum technologies move from laboratory research into existing telecommunications infrastructure — and what that transition means for future networks, distributed computing, security and new services.
30 km
Deployed fibre
>90%
Teleportation fidelity
Real telco infrastructure
Research → deployment
Demonstration conducted by Deutsche Telekom T-Labs and Qunnect. Future Literacy participated in the strategic discussion.
Quantum & post-quantum infrastructure
Future Literacy has worked for more than seven years across European quantum technology ecosystems, connecting research, industry, telecommunications, public institutions and strategic infrastructure.
- 01MadQCI
- 02Spain's National Quantum Communications Plan (PC3) — €22M
- 03EuroQCI / European Quantum Communications Infrastructure
- 04European quantum ecosystems
- 05Post-quantum security
- 06Quantum communications
Our work has connected startups, research centres and institutional actors and has included engagement with European environments including the Quantum Flagship, European institutions and investment ecosystems.
Telecommunications & future networks
Future Literacy works at the intersection of connectivity, AI and emerging infrastructure. In 2026, our work reached Mobile World Congress through executive-level engagement around quantum telecommunications infrastructure involving Deutsche Telekom and Qunnect.
- 01Telecommunications resilience
- 02Quantum-secure communications
- 03Post-quantum security
- 04Advanced connectivity
- 05Distributed networks
- 06Sovereign infrastructure
- 07Space and interplanetary communications
Future Literacy leadership has also worked on strategic Internet and space-network architectures alongside international ecosystems connected with NASA, JAXA, ESA, Google, Airbus and the Internet Society. These are ecosystem and collaborative environments, not commercial client relationships.
08 — Why Future Literacy
We work between the layers
others treat separately.
Technology
What is becoming possible?
Industry
Where does it create value?
Government
What conditions enable adoption?
Infrastructure
What does deployment depend on?
Governance
What should be permitted, controlled or protected?
Ecosystem
Who needs to work together?
Capital
What deserves investment?
Future systems
What comes after today's architecture?
Our role is to turn those questions into decisions, and decisions into executable pathways.
09 — International execution
European experience.
Southeast Asian execution.
Future Literacy operates internationally from Europe and is expanding its on-the-ground capability across Southeast Asia.
We bring experience from European AI governance, industrial transformation, sovereign technology and frontier-tech ecosystems into dialogue with governments and industry navigating their own AI transition.
We do not export a European template. We identify what is transferable, what is not, and build around local industrial, institutional and technological realities.
Where is AI creating value —
and what is stopping you from capturing it?
Whether you are defining a national AI programme, prioritising corporate investments, designing governance, mapping sector transformation or determining the infrastructure and capabilities required for the next stage of adoption, Future Literacy can help structure the decision.
Government & public institutions
- AI strategy
- Governance
- Sector transformation
- Public-sector adoption
- Ecosystem design
- Sovereignty
Industry & strategic corporates
- Use cases
- Investment prioritisation
- Build / buy / partner
- Governance
- Technology scouting
- Pilot-to-scale
- Government alignment