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• Generative AI could save the public sector billions in the next 5 years
• More routine tasks could be automated to free up time for creatives
• More than half of public sector jobs will be changed in some way in coming years

New research has revealed the UK public sector could save billions in expenditure by fully embracing generative AI technology.

The ‘AI & The Public Sector’ commissioned by Google Cloud has highlighted the ways the public sector could save around £38bn over the next 5 years by adopting more GenAI adoption.

Perhaps unsurprisingly, the report predicts that ‘automating routine tasks’ will be the future of AI tools in the workplace, and that over a third of daily tasks in the public sector could be performed by generative AI.

A new way forward

The report rightly points out many public sector organizations are under huge pressure, with 61% of public administration workers overworked, and 70% of respondents agreeing that employee morale has decreased.

To combat this, generative AI solutions should be embraced by public organizations, the report suggests. Currently, only 12% of public administrators say they have significantly deployed AI tools.

By letting generative AI automate administrative work, the public sector could unlock an extra 3.7 million GP appointments, the equivalent of 160,000 police officers, and a 16% increase in student to teacher ratio - a cumulative value of £358bn by 2034. This would free up 8.3% of the budget for re-investment into our public services, the report says.

“Now the digital centre of government, my department is testing how we can put AI to work in the public sector, whether that’s speeding up finding information on GOV.UK or empowering teachers by reducing administrative burdens, allowing them to dedicate more time to what they do best,” said UK Technology Secretary Peter Kyle.

Job augmentation

Over half of public sector jobs (56%) are likely to be ‘augmented’ in some way by AI adoption, the report claims, optimistically predicting workers will be allowed more time for creative focus.

Even with full AI implementation, the report estimates that 38% of roles are ‘insulated’ and won’t be affected by AI adoption thanks to their inherent sensitivity. The remaining 6% of jobs will be ‘displaced’ or phased out.

However Google Cloud says the demand for public sector labour will grow, so displaced workers will simply be reallocated into new roles. This echoes other recent studies, which for example have shown IT service desks could ‘go extinct’.

Early stages of adoption

The study shows there are barriers to AI implementation that need to be addressed before the public sector is ready to embrace AI. Applicability is part of the concern, with over half of respondents (55%) agreeing they would need different or better structured data sets to use AI effectively.

Many workers are also uncertain about the security, legal liabilities, and costs of AI tools, and before workplaces take full advantage of AI, more education is needed, as over a third (34%) say they don’t have the skills to benefit from AI tech just yet.

There are significant concerns about the reliability of AI output too, but Google Cloud reassures these worries are ‘likely to fade on their own as the technology becomes more mature’.

Governments leading the way

Google Cloud has identified public sector AI adoption as a key driver to wider AI adoption across all industries. As part of Government commitments to using AI in public services, organizations should conduct AI adoption assessments in key sectors such as health, transport, and education.

This will allow agencies to identify barriers to AI deployment and address any roadblocks. Procurement teams should be 'empowered and upskilled' on the importance of AI adoption so that they can effectively assess their needs.

An overhaul of government IT systems is needed to efficiently adopt AI, says Google Cloud. Legacy IT systems, data storage capacity, and an absence of advanced cloud data analytics are all hindering the development of AI in the public sector, it says.

Untold costs

What the report doesn’t address, is the cost of generative AI adoption. The costs are multi-faceted, with AI demanding a huge amount of energy to run, and also an enormous amount of water to cool high performing hardware.

The AI industry is already in the midst of a serious sustainability crisis, so large-scale adoption in both the public and private sectors could have disastrous consequences for climate protection goals.

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The finance sector, widely regarded as a trend-setter for new and emerging technologies, is once again leading from the front. Since the rollout of the “open banking” initiative, which allows financial data to be shared between banks and third-party service providers, the pace of innovation in the sector has skyrocketed.

Credit scoring has become streamlined, anti-money laundering (AML) techniques have become more advanced, real-time trading is the new standard, and financial services companies like banks are competing to provide the best customer experience.

It's not just consumers that stand to benefit either. In the UK, where the concept of open banking experienced its first real breakthrough, the NatWest Group reports that 66% of businesses save roughly 150 hours every year on operational tasks thanks to open banking initiatives.

All of this is made possible through the use of Application Programming Interfaces, or APIs. APIs are software-based intermediaries that allow different applications to communicate and share data securely and efficiently. Not only does this create a more “joined up” financial ecosystem for business and customers, it paves the way for innovative new services, solutions and business cases.

Financial institutions like Standard Chartered have even established API marketplaces to streamline the integration of third-party services, promoting a more competitive and customer-centric financial ecosystem. This interconnectedness ultimately leads to improved user experiences and operational efficiencies, as well as a competitive edge for those finance companies with the ambition and resources to take advantage.

Payments and transactions

APIs have already revolutionized the way payments and transactions are handled in the financial sector, enabling smoother, faster, and more secure processes. For instance, companies like PayPal now release APIs to allow developers to integrate payment gateway services seamlessly into various platforms, allowing users to initiate transactions directly from apps or websites without being redirected.

This not only enhances user convenience but also boosts transaction speed and security. Real-time credit card processing, instant fraud detection, and integration with multiple payment gateways also significantly improves the overall transaction experience for both businesses and consumers. This is a perfect example of the flexibility and scalability that APIs can facilitate to allow businesses to change to meet market demands and customer expectations.

Trading and investments

Significant advancements in the trading and investment sector are also being driven by APIs, making services more accessible and efficient. Robinhood's launch of a crypto trading API is a prime example, offering users the ability to trade cryptocurrencies seamlessly through third-party platforms.

This innovation democratizes access to trading apps, allowing for real-time data exchange, automated trading strategies, and integration with financial advisory services. APIs enable traders to connect with multiple markets and data sources, ensuring they have the most accurate and up-to-date information to make informed investment decisions.

Anti-Money Laundering (AML)

APIs are quickly becoming essential tools in the fight against money laundering, offering real-time capabilities to detect and prevent fraudulent activities. By integrating APIs into their systems, financial institutions can quickly analyze large volumes of transaction data, identify suspicious patterns, and comply with regulatory requirements.

These APIs facilitate the seamless exchange of information between different platforms and databases, ensuring that potential money laundering activities are flagged and investigated promptly. Advanced machine learning algorithms can also be integrated via APIs to enhance the accuracy and efficiency of anti-money laundering efforts, safeguarding the financial ecosystem against illicit activities.

Credit scoring and the customer experience

Thanks to APIs, traditional credit scores, which often rely on limited financial data, are now being supplemented with alternative data from utilities, rent payments, and even social media activity. This creates a more holistic view of a customer's creditworthiness for lenders and reduces the time it takes to get approved.

APIs are also enhancing the customer experience by enabling personalized financial services, integrating customer data across various touchpoints and providing tailored advice and products that meet individual needs. The way is also being paved for the development of intuitive mobile apps and online platforms that allow customers to access and manage all their finances in one place, giving people greater control and flexibility over how they manage their money.

APIs are not just driving innovation in the financial sector; they are setting new standards for efficiency, security, and customer satisfaction. As long as financial institutions continue to leverage the power of APIs, opportunities for growth and transformation will follow.

We list the best personal finance software.

This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

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