The necessary convergence of AI, CX and public services
Government and wider Public Sector organisations have little choice but to embrace innovative technologies; not only to survive, but to eventually thrive
Over the past decade, the public sector has been navigating significant constraints on funding and staffing levels - a trend that seems set to continue under Labour. The quality of services has inevitably been impacted while demand continues to rise. If this trajectory doesn't change, something will eventually break, and when a public service collapses, the consequences can be severe.
Everything is a service with customers - even in the public sector.
Police forces deliver the vital service of keeping us safe. New passports or visas are managed by the Home Office. Booking a GP appointment or undergoing surgery is handled by the NHS. Departments like the DWP oversee universal credit, HMRC manages our taxes, the MOJ oversees the courts and prisons, the list of services the public sector provides is enormous.
We all rely on these services every day.
Yet there's a disconnect. Despite delivering a vast number of essential services, public sector organisations often don't adopt a customer experience (CX) mindset. Users aren't always treated as customers.
What if the goal was to make the experience of booking a GP appointment as seamless and quick as ordering an item off Amazon, or renewing your drivers license as straight forward as opening a bank account with Revolut, or applying for a business permit as simple as ordering a meal on Deliveroo?
For these goals to be achieved, leaders and civil servants need to believe they are possible.
Whichever north star a public sector organisation wants to work towards, it's clear that traditional methods are no longer sufficient to get there. Embracing new technologies like machine learning (ML), artificial intelligence (AI), and automation is essential for increasing operational leverage and achieving the crucial outcome: boosting productivity without escalating costs.
However, adopting new technologies is challenging. It requires a significant shift in operating models, mentality, and organisational culture to fulfil their potential.
It also necessitates dedicated and targeted investment in L&D to nurture and grow talent within the civil service in high-value skills such as software engineering, machine learning engineering, data science, and artificial intelligence specialisations. By investing in the development of these competencies, the public sector can build an internal workforce capable of driving and sustaining technological innovation.
This has been an area under-funded and overlooked for too long, creating a relationship of critical reliance on the private sector rather than mutual collaboration as peers.
Rather than focusing on grand plans like replacing thousands of staff with chatbots overnight, we should concentrate on increasing the efficiency of the human workforce.
Reducing the administrative burden that consumes much of people's time will also have the added benefit of increasing staff satisfaction and retention levels, as employees spend more time on tasks they enjoy that also enable a better customer experience.
Incremental improvements compound over time to create significant advancements. Much like how British Cycling achieved Olympic gold through 1% performance enhancements by making numerous small, manageable changes.
Mitigate risk and foster a culture of continuous improvement.
In the private sector, companies have successfully leveraged AI and ML to address challenges similar to those faced by the public sector.
For example, Bank of America introduced an AI-driven virtual assistant named Erica, which helps customers with routine enquiries and transactions, providing personalised financial guidance. This automation reduced wait times and improved customer satisfaction, allowing human staff to focus on more complex customer needs.
IBM's Watson Health has been employed by healthcare organisations to analyse vast amounts of medical data. Watson assists in diagnosing medical conditions and suggesting treatment options by processing unstructured data from medical records and research papers. Demonstrating how AI can handle large volumes of documentation and provide actionable insights, enhancing interoperability and data sharing in a secure manner.
HSBC implemented AI solutions to combat financial crime, including money laundering and fraud. By utilising machine learning algorithms, the bank automated the analysis of transactions and customer data to identify suspicious activities more efficiently than manual processes allowed. This not only improved the speed and accuracy of detection but also enabled compliance with regulatory requirements, addressing issues of interoperability and data processing at scale.
Think about how the creation of semi-automated, interoperable, efficient, and hyper-personalised services could significantly enhance 999 call centres, complaints processes, tax queries, and other critical public sector functions. By implementing AI and ML technologies, public sector organisations could provide real-time sentiment analysis and gain concrete data insights for improvements. This would not only improve the user experience but also enable faster response times, better resource allocation, more effective decision-making and increased staff satisfaction levels.
So how can IGS help?
We partner exclusively with expert SMEs in their respective fields and compliment their skills by leveraging our ecosystem of experienced ex-Big 4-8 management consultants to deliver, providing a premium service at competitive prices.
We focus on practical solutions and building sophisticated systems that seem simple, with you and for you.
If you'd like to learn more about how you can increase your operational leverage cost-efficiently, you can schedule a consultation via Liam.Barber@investigo.co.uk or IGS@investigo.co.uk.
Author: Liam Barber