Building tech and trust: How Azerbaijan is scaling AI through co-creation

As part of the Government AI Campus, Apolitical is publishing a series of articles featuring leaders from the 2026 Government AI 100, a list recognising public servants around the world who are pioneering AI adoption, capacity building and regulation.

Apolitical spoke with Laman Ibrahimova, Head of the ASAN AI Hub, Azerbaijan's national platform that brings together government, business and academia to transform real-world challenges into AI-powered solutions.

Tell us about the ASAN service and why you decided to create the ASAN AI Hub

To understand why we created the ASAN AI Hub, it helps to start with ASAN itself. Launched in 2012, the ASAN service fundamentally redesigned how public services are delivered in Azerbaijan. “Asan” means “easy” in Azerbaijani, and that is exactly the promise of the model: making government easy for people. Before ASAN, receiving a public service often meant visiting multiple offices, navigating complex procedures and waiting in long queues. ASAN replaced this with a single channel service delivery model, where citizens access services from multiple public and private agencies in a single location, under a unified set of standards, with performance continuously monitored and optimised.

Today, ASAN provides more than 400 services through 28 service centres, mobile ASAN buses handling around 40,000 applications a day and a citizen satisfaction rate of 99.8%, based on continuous feedback collection.

The model’s success has received wide international recognition. ASAN is a two-time recipient of United Nations accolades — the UN Public Service Award and the UN Special Award for promoting innovation in digital public service delivery — and was also recognised as the World’s Best Government Service at the Annual World Government Summit in 2023. The model has also become a distinctive intellectual export: more than 30 cooperation agreements have been signed, and countries such as Indonesia, Uzbekistan, Ethiopia, Uganda and Pakistan have adopted it to streamline their own public services.

The ASAN AI Hub was created because digital challenges are becoming more complex, and the public sector alone cannot generate all the solutions it needs. We wanted to create a platform where public institutions, startups, researchers, private companies and citizens could work together to solve real-world problems through AI.

At its core, the Hub is built around the idea of open innovation. Instead of limiting innovation to internal processes or a single institution, the platform allows organisations to announce challenges openly and receive solutions from startups, researchers, students and companies that may otherwise never have access to decision-makers.

From your experience, what are your key learnings from working with stakeholders with different perspectives and priorities?

"Working with government institutions, startups, private companies and researchers has shown that alignment does not happen automatically; it must be deliberately designed."

Public institutions are naturally risk-averse and accountable to citizens. Startups are agile and growth-oriented. Academics prioritise rigour and research integrity, while private firms often focus on operational value and return on investment. These differences create friction if expectations are not clearly managed.

One of our biggest learnings is that collaboration only works when participants trust the process. We need clear rules, transparency and protection of intellectual property to create a safe environment for cooperation. When organisations or innovators join an open innovation challenge, they need confidence that their ideas will be respected, their work will not be misused and that participation can lead to real opportunities.

For example, on the ASAN AI Hub, challenges are announced together with pre-defined conditions and prize mechanisms. Participants understand from the beginning what they are working toward and how the process will function. This level of clarity is especially important for startups, young researchers and smaller teams that may not have the same access or resources as larger organisations.

We have also seen that many institutions initially approach open innovation cautiously. There is often a habit of trying to solve problems internally rather than opening them to external contributors. However, once organisations see practical outcomes and successful collaborations, their mindset begins to shift. In some cases, challenge owners who initially had doubts later became interested not only in the winning solutions, but also in working directly with the innovators behind them.

Another important lesson is that innovation ecosystems become stronger when they are connected and accessible. The Hub acts as a bridge between challenge owners and problem-solvers, helping both sides collaborate with greater clarity and accountability.

How do insights from your research on responsible AI stewardship inform real-world AI initiatives and pilots?

One key finding is that governments need to shift how they think about AI. It should be institutionalised and embedded into operational processes. One of the significant gaps today is AI literacy in the public sector. Many risks do not come from malicious intent but from insufficient understanding and unclear guidance.

Responsible AI requires training, practical guidance and continuous upskilling across the workforce, not just high-level policy statements. Entry-level public servants should receive AI training and clear guidance on how to use AI in their roles. Stewardship must be operational, not abstract. Ethical principles alone are insufficient, without concrete mechanisms such as guidelines, impact assessments, monitoring frameworks and iterative review processes.

Responsible AI also depends heavily on institutional culture. Cultural resistance is one of the biggest barriers to adoption, which is why AI champions within institutions are important. They help shift mindsets, build confidence and introduce practical tools and workflows.

What is one lesson other governments or innovation hubs could take from Azerbaijan's approach?

The lesson I would highlight first is the principle of leaving no one behind, which sits at the heart of the UN Sustainable Development Goals and which ASAN has integrated into its core mission. Innovation only matters if it reaches everyone. That is why, alongside our service centres, we operate mobile ASAN buses that travel to remote regions and villages, delivering the same quality of services to citizens who live far from any centre. We have even taken this model beyond our borders, with mobile ASAN serving our citizens in Georgia and Türkiye.

Another lesson is that innovation should not be confined to a single department or isolated unit. It needs to become systemic and embedded across government operations and sectors. When innovation becomes part of institutional culture rather than a standalone initiative, transformation becomes more sustainable.

Another important lesson is that citizens should be viewed not only as users of public services but also as contributors and co-creators of solutions. Some of the most valuable ideas come from people who directly experience public challenges in their daily lives. At ASAN, we built on an already existing culture of citizen engagement through initiatives such as the Idea Bank and ASAN Appeal systems, where citizens and public officers could submit suggestions and report issues. The AI Hub expands this participatory approach by turning real challenges into opportunities for collaborative innovation.

Most importantly, countries do not need to be among the world’s largest economies to build meaningful AI ecosystems. Strong ecosystems can also emerge when countries focus on trust, accessibility, collaboration and practical implementation.

What excites you most about governments using AI, and what concerns you?

AI has the potential to democratise access to high-quality public services. It can make government services more personalised, efficient and accessible, regardless of geography or socioeconomic background. It can help governments process large volumes of information, anticipate citizen needs, reduce waiting times and allocate resources more intelligently.

What excites me most is the possibility of making innovation more inclusive. AI should not belong only to large technology companies or wealthy markets. Smaller countries, startups, researchers and local innovators should also have opportunities to contribute to solving real-world challenges and developing meaningful products.

At the same time, governments need to separate real transformation from hype. Many organisations are adopting AI tools quickly, but far fewer are integrating them successfully into workflows and institutional systems. AI adoption is not primarily a technology challenge; it is an organisational and governance one. Deploying a chatbot is relatively easy; redesigning systems, processes and decision-making around AI is much harder and in government, even a small failure rate can have serious consequences for citizens.

"If we approach AI with ambition and discipline, I think it can become one of the powerful public goods of our generation rather than a source of fragmentation or inequality."

In the end, successful AI adoption is not only about technological capability. It is also about creating environments where people trust the process enough to participate, collaborate and innovate together.