Building future-ready governments – with strong foundations and information ‘integrity’ at the core

Ways of working are changing significantly. As public sector organisations navigate digital transformation, complex policy challenges, and changing citizen expectations, the question of how to prepare for the future has never been more pressing. With budgetary pressure, resourcing gaps and rapid technology changes, necessity will drive change differently than previous innovation waves.

Ahead of our upcoming DigitalScotland panel discussion, “Shaping the Future of Government: An Exclusive Panel on AI, Innovation and Governance”, we spoke with our panel moderator, Cassandra Bisset, VP Strategy at Objective Corporation, to explore how to build a strong foundation for information integrity, and the ideas shaping public sector reform, innovation and excellence.
 

What excites you most about the intersection of AI, innovation, and public sector governance right now?

Whilst organisations focus on digital services, productivity improvement and transparency, AI is a significant tool for the public sector to deliver outsized advantage. CIOs are under pressure to deliver short-term efficiency improvements in public services and operations, but the folks that build a scaffolding to scale for many demands are going to stand out from the pack. Demand for information to fuel AI strategies is critical – but organisations also need to pass audit and get trustworthy outcomes. Information and governance are critical enablers to deliver the vision and mission of government.  

From your perspective, what’s the biggest misconception people have about using AI in government?

Innovation is moving so rapidly in this space. I find people hold on to things they may have heard or experienced early on and haven’t looked for new approaches or even known they could solve issues that came up. This was true of hallucinations – I would sit in meetings and hear people say ‘you can’t use it for real work because of the hallucinations’. This problem was solved with techniques fairly quickly and we saw the rise of curating purposeful small data to ground models, data optimisation, chunking and embedding and vectorisation to give context and better-quality results through RAG and a number of other controls. Though people hold on to the experience they had or what they hear, I would have people challenge things like auto-classification of unstructured information and how technology could understand what something was about, especially with nuanced information or sensitivity because they used ML six years ago. The reality is GenAI, LLMs and multimodal capabilities have been a game changer, and many things of exceptional quality are possible now.   

I also hear the phrases ‘AI won’t take your job, but someone with AI skills will’. I have really mixed feelings about this.  I don’t think alarm is the right strategy – I think we all need to consider that if we really did introduce AI well, what would it feel like at work in a couple of years and how would it feel to be a member of the community – what are the experiences we would want people to have... it’s not about the gadget.  We already have a lot of productivity tools and don’t feel productive – how can we look at problems with fresh eyes and solve them differently today?

In your experience, what distinguishes public sector organisations that successfully embrace innovation from those that struggle to move beyond traditional ways of working?

This may sound simple, but I have seen some remarkable innovation coming from government through human centred design principles and putting people at the centre. When we put our heads together on what really needs solving and how to go about it for the best outcomes, the solution can be very surprising.  Public sector has some real muscle here and it needs to be used now more than ever to put the right plans in place.  
I’ve heard some interesting ideas around access to technology – if you can demonstrate good data stewardship and governance and risk understanding, you can access more capabilities. If you are curious and a change agent, you may be seconded on to innovative projects. If you really care about transformation, skills development must be at the heart of your transformation plan. It’s useful to think about your organisational culture to know how much innovation you can expect to have signed off. Very few organisations will remove human interactions from service delivery – that's not what government is about.

I think it’s interesting to see the ‘fail fast’ ideas coming in – no one historically wants failure; we're allergic to it. Access to SaaS capabilities, trials and communities in government mean you can actually get experience relatively cost effectively, though we can’t afford to have every department ‘have a go’. Organisations forming strong working groups of people who are interested in new ways of working and who establish committees on what should be prioritised, circulate success and prioritise what to elevate with AI are getting better outcomes and scaling faster.

If you could introduce one bold structural reform tomorrow to make government more adaptive and future-focused, what would it be – and why?

There’s still work to do on legislation and sharing across agencies for information. I think the initiatives that are being funded need to be looked at in a different light now – how could we address problems in a different way and how do we prioritise initiatives that set organisations up for the next five years, not just with short term gains. When I see things like Google Pixel Buds – fascinating that concepts we saw in Star Wars as kids are now here – but this could be transformative to connection and time critical service delivery. We need funding to stand behind skills development, and innovation that is transformative. This may mean more co-design or cross-functional development to uplift several similar capabilities in one go. There’s a lot to think about here. 

You’ll be moderating a panel of senior public sector leaders, what are you hoping to draw out in the discussion?

I feel so compelled to share the goodness going on and also challenge why and what is focused on. Above all, there are some really inspiring activities under way, and I want everyone to hear about it. With AI, I see a real maturity in the thinking and planning around risk, governance, environmental and people aspects being considered – as well as the opportunity. I want people to feel the optimism for what’s ahead and have a better sense of what’s going on and where to target some extra energy. Folks in the public service make a difference every day; I see that in a big way with the effort going into innovation, but we need to move beyond FOMO and to really tackle the big stuff. That’s what I think people will enjoy most in this session.

Any final thoughts?

There are some key lessons when we look at the statistics on failure and why pilots aren’t moving to production:

• People have raced to use capability, with less focus on whether the capability is fit for purpose for their use case. For example, Generative AI isn’t a capability you’d use for predictive concepts and capability for medical research is different from sensitive data detection. Organisations need to plan to have a number of AI hammers for different scenarios and know the boundaries of GenAI;
• Regardless of which capabilities you leverage, you will need fit for purpose, curated views from many different systems to answer questions holistically with approved content to fuel your AI initiatives. Specialist, optimised collections give better quality answers, conserve resources and provide the scaffolding to meet governance obligations, risk screening, current information, and pass audit. People spent years sorting out structured data with warehouses, lakes and master data management, yet haven’t put strategies in place to prepare unstructured information for AI initiatives;
• If people aren’t putting effort into solving scenarios that are valuable, when it comes to funding, is the juice worth the squeeze? Return on investment and total cost of ownership will come up – prioritising use cases and how to solve them is foundational project work. Knowing your organisation’s persona and ambition can help guide where to focus initiatives that will be supported.

Vendors will be doing these projects hundreds of times and there is a lot of value still working out buy vs build vs experiment. Collaboration will be critical to scale this well and avoid wastage.

Join us at DigitalScotland 2025

Objective’s “Shaping the Future of Government: An Exclusive Panel on AI, Innovation and Governance” takes place 12:00-12:30 in Lennox Suite 2 & 3 at DigitalScotland 2025. 

Cassandra will be joined by representatives from Scottish Government and Welsh Government to discuss how innovation and AI can deliver smarter, faster, and more transparent services. Find out more here.