Beyond the hype: real-world AI and data insights from the Government Transformation Summit

by Neil Gladstone - Data & AI Practice Director
| minute read

I recently attended the Government Transformation Week Data and AI Summit in London. With a focus on government digital transformation, the Data and AI Summit explores data and AI in the public sector, bringing together policymakers, leaders, technology providers, and experts to discuss using analytics and AI to enhance decision-making, efficiency, and social impact. 

The event was a valuable opportunity to engage with key technology players across the public sector. David Wilde, founder of Government Transformation Magazine, opened the day, and the well-curated programme included keynotes by Philip Orumwense on AI for trust and fairness, and Dr Christopher Royles on responsible AI in public-sector projects. 

Throughout the day, panel discussions covered a range of topics, including transforming public data with AI, balancing innovation and ethics, and AI's role in next-generation public services. Notably, Sue Bateman from DEFRA shared insights on how data analytics and AI are advancing environmental management and sustainability. 

I had the privilege of co-chairing four discussion tables with my colleague, Gary Craven, Head of UK Data & AI Consulting - Delivery at Sopra Steria Next. Together with a number of stakeholders including local government, central government bodies, and transport operators, we explored how predictive analytics can enhance policymaking and service delivery, while addressing practical and ethical considerations. 

Our discussions highlighted several common themes, including the need for improved data sharing, the challenges posed by poor data quality, and the constraints imposed by budgets during economic downturns. But three main takeaways stood out for me: 

AI can transform services, but also redefine them 

The growing volume of data held by government on services and their users presents a significant opportunity. The group was excited about the potential for predictive analytics to identify which services will deliver maximum citizen benefit from every pound of investment. 

Generative AI needs a reality check 

A recurring topic was the hype surrounding generative AI over the past two years. While there has been a lot of excitement and the potential is clear, the reality is that there are still very limited use cases that have made it into production with viable business cases. From my experience, this serves as a crucial reminder for both government and suppliers to prioritise business outcomes first, rather than starting with AI technology and then seeking ways to implement it. 

Government adoption of AI isn’t without its challenges – and that’s slowing adoption 

It was clear that data and AI are major focus areas across all government departments to deliver their strategies, and there’s a strong consensus that AI is an essential step in delivering operational efficiency and fostering better services for citizens. But many departments face significant challenges in making these plans a reality, such as integrating advanced analytics into existing systems, ensuring data quality, and of course, budgetary constraints. 

Despite the challenges, at Sopra Steria, we know that AI adoption in the public sector is possible, and will be transformative. We advocate an approach where organisational outcomes are king. What the organisation is trying to achieve – the problem statement – should be the starting point. AI is one piece of the transformation puzzle, and, if implemented properly, it can ultimately deliver better services for citizens. As we move forward, it is essential to keep the focus on outcomes and ensure that our strategies are driven by practical and ethical considerations. 

To read more about our AI approach and ethos, we have a wealth of blogs covering a range of related topics – from hyperautomation to ethics. Check them out here

I look forward to continuing these important conversations and contributing to the transformative potential of data and AI in the public sector. 

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