Operationalising Generative AI: ‘The key is this transformation will be a co-evolutionary process’
The Generative AI revolution is picking up pace - with its potential to improve data accessibility and democratisation while reducing administrative complexity; eliminating backlogs and enhancing services.
As governments increasingly look at how this technology can improve and challenge their operations, Bryan Rich, AI Lead for Accenture Health and Public Sector, discusses how to successfully operationalise it.
"The key to this transformation will be a co-evolutionary process - where industry gets better, the tools and applications get safer, and government institutions get the trust and security to accelerate the way this technology can impact processes.”
Against this backdrop, Accenture is launching the Data and AI Studio for Public Service Europe in Brussels to help test and develop AI solutions in the European and UK public sector. This dedicated space - set to officially open in September - will include a team of 25 people based on site and an additional 90 people externally who will offer their expertise on AI, computer vision, natural language processing, responsible AI, and statistical modelling.
The Data and AI Studio is part of a $3bn AI investment announced by Accenture in June to stay at the forefront of what it calls the next decade-long “mega-trend”. Generative AI forms an integral part of that vision: Accenture has already established the Generative AI and Large Language Model (LLM) Center of Excellence and has published a study of generative AI/LLM - advising businesses on the use of the technology.
“Generative AI is becoming a way for departments to unlock the value of the data that they have available to them. It has the potential to massively improve the latency and precision of decision-making within government,” Rich said.
A co-evolutionary process
While there is a growing appetite to adopt Generative AI, it is still relatively new ground for government procurement teams, Rich explains. The new studio, which acts "as an indicator of interest and maturity in terms of how teams want to adopt this technology", can help them to buy and take advantage of AI-based services. At the same time, it can give suppliers a better understanding of how to sell and price these products, he said.
It is less about selling a service and more about building a partnership with the customer to figure out what is required, he adds. “The goal is to create and strengthen this co-evolutionary relationship where we're learning what the needs of the public sector are and at the same time we're sharing what we're learning as we test and evaluate solutions.”
Like any disruptive technology, the challenge with Generative AI is "moving from niche prototypes" to deliver the scale required to have meaningful impact in the public sector, Rich explains. “There's lots of people fostering and investing in innovation, but we’re looking at how these technologies can actually be implemented at scale.”
Accenture’s Data and AI Studio will strengthen the quality of teams and talent when it comes to AI, he explains. “We're able to attract top talent because data scientists love to work on hard problems. This allows public sector organisations to tap into this wealth of knowledge.”
Benefits and risks
Generative AI is supercharging the entire AI discussion, Rich says. “But like electricity, it has a positive and a negative charge; you've got to figure out how to balance the good with the bad through responsible design and implementation”
As an example, he points to how it can be used in social services, where there is a huge backlog of claims, to create a system that prioritises the most vulnerable cases. Likewise, in the health sector, Generative AI can significantly optimise time intensive administrative procedures.
Another example is immigration applications, where Generative AI is already being piloted to improve the quality of the experience of the person seeking information and obtaining the forms that they need. This is estimated to create a 60% reduction in time and effort, Rich notes.
However, there is still a significant amount of risk in terms of organisations adopting Generative AI without having created the right roles and responsibilities to assure governance, security and privacy. “Organisational structure is a really critical dimension of having a secure by design mindset that will allow them to use and scale AI solutions,” Rich says. “It still requires a lot of thought and strategy to get right.”
“What we see currently among public sector organisations is a sense of curiosity where AI and Generative AI use cases are being applied in pocketed ways for specific business impacts,” Rich explains.
However, he expects this to evolve and broaden over time. As the demand for AI services in government grows, some of the biggest opportunities will be finding solutions for existential challenges around climate, healthcare, energy and food security, Rich says.
“We’re in a time sensitive situation to solve some of these problems and make important policy decisions around these issues. AI and Generative AI has the potential to unlock the value in the volume, variety and velocity of data in organisations.
“I think there's a huge opportunity there and that transformation is going to be accelerated by this co-evolution between industry and the public sector.”