Artificial intelligence takeaways from Innovation 2025
By GGF reporter on 28/04/2025 | Updated on 28/04/2025
Image by Gerd Altmann via Pixabay
Global Government Forum has used an artificial intelligence tool to analyse all the sessions at Innovation 2025 for takeaways on how governments around the world are using AI to streamline their own operations and to deliver better public services.
Key issues discussed at Global Government Forum’s Innovation conference include AI skills in government, the need to build public confidence in the use of AI, data quality and accessibility, the opportunity for AI in decision-making, the barrier of legacy IT infrastructure, and the importance of strong leadership in driving adoption.
Key issues relating to the use of artificial intelligence in government
- Public sector readiness: There is a question of whether the public sector is truly ready to embrace AI. While some are excited about its potential, others may be anxious about the scale and pace of change required.
- Skills gaps and talent: A major concern is the lack of sufficient AI-related skills within the civil service. This includes a need for more machine learning engineers and upskilling existing staff. Skills data related to AI is also considered “really messy”.
- Ethical considerations and trust: Ethical challenges arise with AI, particularly concerning the automation of decision-making. Building public confidence in the use of AI in government is crucial.
- Data quality and governance: Effective use of AI relies on good quality data. Poor data quality can hinder AI implementation and impact its effectiveness. Clear data labelling at the source is important.
- Pervasiveness and impact: There are varying views on the pervasive impact of AI. While some see it as revolutionary, others suggest its impact will be focused on specific areas like automation and speed.
- Risk of over-reliance and reduced critical thinking: Concerns exist that heavy reliance on AI could lead to a reduction in critical thinking.
- Energy costs: The increased computing power required for AI, particularly large data centres, raises questions about energy consumption and its impact on net-zero targets.
- Defining AI: A fundamental issue is a lack of a clear and consistent definition of what ‘AI’ means across different government organisations.
Key areas where governments are using AI
- Efficiency and automation: AI is seen as a tool to make government more efficient by automating tasks and processes.
- Data analysis and insights: AI can help government better gather and analyse large amounts of data to improve decision-making. It can also be used for sentiment and customer contact analysis.
- Internal operations: AI can be used within government for tasks like managing skills through AI-enabled HR software, recommending training and promotion opportunities.
- Service delivery: AI has the potential to improve service delivery by summarising complex information for judges, and potentially for diagnostics (as seen in healthcare examples).
- Citizen engagement: AI-powered tools like chatbots can help engage with citizens and answer their questions. The potential for creating digital twins for synthetic research to understand audience needs is also being explored.
Opportunities and challenges to deploying AI in public services
Opportunities:
- Increased efficiency: AI can automate repetitive tasks, freeing up public servants for more complex work.
- Improved decision-making: Analysing large datasets with AI can lead to more data-driven and potentially better decisions.
- Enhanced service delivery: AI can enable more personalised and responsive services for citizens.
- Better resource allocation: AI can assist in forecasting and managing resources more effectively.
- Unlocking insights from data: AI can help identify patterns and insights from vast amounts of government data.
Challenges:
- Data quality and accessibility: Poor quality, fragmented, and inaccessible data is a significant barrier to effective AI deployment.
- Skills and capability: Lack of in-house AI expertise and the need to upskill the existing workforce pose a major challenge.
- Legacy systems and infrastructure: Integrating AI with outdated government IT systems can be complex and difficult.
- Ethical considerations and bias: Ensuring AI systems are fair, unbiased, and ethically sound is crucial.
- Public trust and adoption: Addressing public concerns about data privacy and the use of AI in decision-making is essential for successful adoption.
- Security risks: AI systems and the data they use need robust security measures to prevent breaches and misuse.
- Procurement of AI solutions: Government needs to develop effective strategies for procuring AI technologies and services. The data required to assess the effectiveness of AI in procurement is currently lacking.
- Potential job displacement: Concerns exist about the long-term impact of AI on employment and the need to adapt to potential job losses.
- Maintaining human connection: While AI can automate tasks, it is important to ensure it doesn’t diminish the human element in public service delivery, especially for vulnerable individuals.
How leaders in government can help drive adoption in their organisation
- Strong leadership buy-in: Clear commitment and a ‘call to arms’ from senior leaders and ministers are essential to empower innovation and AI adoption. The UK prime minister Keir Starmer’s focus on digital and data transformation provides a significant opportunity.
- Setting a vision and communicating it clearly: Leaders need to articulate a clear vision for how AI can benefit the organisation and communicate this effectively to the workforce.
- Investing in skills and talent development: Prioritising training programmes and initiatives to build AI literacy and specialist skills within the civil service is crucial. This includes upskilling existing staff and attracting new talent.
- Creating enabling structures and processes: Establishing clear governance frameworks and ensuring CDIOs have sufficient influence within departments are important structural changes.
- Fostering a culture of innovation and experimentation: Leaders should encourage a test and learn approach, where experimentation and calculated risk-taking are accepted. Creating ‘slack’ or dedicated units for discovery and prototyping can help.
- Promoting collaboration: Leaders should foster collaboration across departments, with the private sector, and with academia to share knowledge and best practices in AI adoption.
- Addressing ethical concerns proactively: Leaders must ensure that ethical considerations are at the forefront of AI deployment, building public trust through transparency and accountability.
- Focusing on user needs and mission delivery: AI adoption should be driven by the desire to improve services for citizens and achieve government missions, rather than adopting technology for its own sake.
- Leading by example: Senior leaders should engage with AI tools and training to demonstrate their commitment and understanding. In Slovenia, ministers participate in conversations about AI skills development.
- Empowering the workforce: Trusting and empowering civil servants to identify and implement AI solutions within a clear framework can drive adoption from the ground up.
- Recognising and sharing successes: Highlighting successful AI implementations can build confidence and encourage wider adoption across government.
Overall, the conference discussions indicate a strong belief in the transformative potential of AI for government, but also a recognition of the significant challenges that need to be addressed in terms of skills, data, ethics, and leadership to realise these opportunities effectively.
This summary was generated using Notebook LLM, based on the following prompt from GGF: Provide a summary of the key issues relating to the use of artificial intelligence in government from Global Government Forum’s Innovation conference. Provide a summary of the key areas where governments are using AI in both how they work and in the delivery of public services; the opportunities and challenges to deploying AI in public services; and how leaders in government can help drive AI adoption in their organisation.
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