At Oscar’s Krane Excellence in Central Government conference in February, Airwalk Reply Partner Alex Hammond delivered an insightful presentation on Artificial Intelligence (AI), the opportunities for public sector organisations and what they need to have in place to leverage all that AI promises and avoid its pitfalls. Here, we distil the presentation’s central themes.
Why is AI a hot topic?
Everyone is talking about AI. In almost every conversation we have with our clients, the two-letter acronym pops up in conversation. So, why is AI now a hot topic? What has changed?
The term Artificial Intelligence was coined in 1956, but AI has become more popular today thanks to increased data volumes, advanced algorithms, and improvements in computing power and storage. Many subsets of AI date back to the 1950s, including cognitive computing, computer vision, neural networks, machine learning, deep learning, and natural language processing. Today, AI is everywhere and embedded in everyday life. However, the excitement and recent step change is about Generative AI (GenAI), which is the product of various AI capabilities. GenAI is a subset of AI that involves creating models capable of capturing training data's underlying patterns and structures to generate new content.
Whilst GenAI has been possible for years, the investment by the major Cloud Service Providers (CSPs) means that the data, compute, and, importantly, the Graphics Processing Units (or specific neural engines) required to use it are now accessible to everyone globally at a cost and performance that makes GenAI commercially viable.
In the UK’s public sector, it’s already widely used – albeit perhaps not in an officially sanctioned capacity. In January 2024, when surveying 1,000 public-sector professionals, the Alan Turing Institute found that 22% already use GenAI in their work, 47% know it is used at work, and 61% trust GenAI outputs. Public sector professionals were optimistic about both the current use of the technology and its potential to enhance their efficiency and reduce bureaucratic workload in the future. For example, those working in the NHS thought that time spent on bureaucracy could drop from 50% to 30% if generative AI were properly exploited, an equivalent of one day per week, which would impact efficiency enormously. So, what are the really interesting and emerging opportunities within AI? And what could this mean for the public sector?
Opportunities for the Public Sector
The opportunities for AI in the public sector are significant and should be seen as a game-changer.
Document processing, unstructured data processing, data summarisation, and data/content generation will save time and money by allowing people to do much more with their time.
There is a massive shortfall in critical skills such as data science, software engineering, etc. AI moves us to a world where scaling through people is no longer the necessary strategy. Does this mean we’re all going to lose our jobs to AI? No, we don’t think so. It could mean that the seemingly exponential relentlessness of working life may finally become surmountable.
Solving Big Problems
GenAI is groundbreaking in several areas, but particularly in comprehension and generation.
Comprehension
This category involves tasks where Generative AI needs to understand or interpret complex data inputs. It includes:
- Language Understanding: Grasping the context, sentiment, or nuances in textual data
- Image and Video Recognition: Identifying objects, themes, or activities in visual content
- Data Analysis: Extracting insights or patterns from structured or unstructured data sets
Generation
Here, the focus is on creating new content or ideas based on learned patterns or instructions. This encompasses:
- Content Creation: Producing text, images, music, or videos that are novel and contextually relevant
- Design and Prototyping: Generating designs for products, architecture, or user interfaces based on specific criteria
- Problem-Solving: Proposing innovative solutions or approaches to address complex challenges
The ability of GenAI to process, "understand", and produce content is highly relevant to the work of government and can be used to:
- Speed up delivery of services: retrieving relevant organisational information faster to answer citizen digital queries or route email correspondence to the right parts of the business
- Reduce staff workload: Suggest first drafts of routine email responses or computer code to allow people more time to focus on other priorities
- Perform complicated tasks: helping to review and summarise vast amounts of information
- Improve accessibility of government information: improving the readability and accessibility of information on webpages or reports
- Perform specialist tasks more cost-effectively: summarising documentation that contains specialist language like financial or legal terms or translating a document into several different languages
These are only a few examples of how AI offers a bright future for the public sector and ensures it can deliver more efficiently and effectively for its citizens. There are also emerging opportunities that could provide even more benefits.
Emerging Opportunities
Technology is ever-evolving, so what are AI's attractive and emerging opportunities? And what could this mean for the public sector?
- Digital engagement and the digital human concept already exist. They can take on so much of the burden of customer service and engagement, allowing staff to focus on the important work that adds value to their organisation
- The democratisation of development, in which the dominant programming language will be the language you speak, gives stakeholders the power to revolutionise how they use technology. This allows skilled engineers to focus on the complex and foundational elements that enable this and the high-value interventions that add the most value
- Initial task processing, triage and potential execution of automated revisions and updates of policies and standards
- Enhanced and interrogable handling of Management Information (MI) is taken to the next level
Exciting, right? But, as with most things, it’s rarely as simple as that. While some emerging tech, such as GenAI, is eminently accessible and relatively simple to plug in, the challenge is that you’re not operating out of your spare room. As government entities, there are essential things to consider, and we broadly separate these into technology and organisational foundations, which are necessary to avoid getting stuck or in very hot water.
What do we need to consider in the Public Sector?
Government departments have already woken up to the pitfalls of using AI without guardrails. Only this month, the Department of Work & Pensions issued guidance outlawing its civil servants from using ChatGPT in their work or accessing it on any government-issued devices. It comes less than three weeks after the Cabinet Office and its subsidiary unit, the Central Digital and Data Office, published the GenAI Framework for HMG, which sets out ten principles to guide the safe, responsible and effective use of generative AI in government organisations.
Technology Foundations
Enabling public sector organisations to use AI in a controlled, well-governed environment can be complex. Organisations with modern architecture and the use of the cloud have a significant advantage in leveraging AI safely. You will need to consider:
- Patterns for applications – best practices on how to build applications
- Observability – ensuring applications (and LLMs) are working as expected
- Safety – monitoring for bias, misinformation, and privacy
- Governance – understanding the risks
- Developer Onboarding – enabling developers to start developing quickly
- LLM and Model Onboarding – ensuring only appropriate models and systems are used
Organisational Foundations
Not only having the right technology in place but effectively exploiting AI also requires the right organisational foundations. You will need to focus on:
- Security of data
- Environmental costs
- Fostering an AI culture
- Validating technical maturity
- Adapting the operating model
- Business case justification
- Ideation and experimentation
Take a Risk-based Approach
Use cases should be tightly controlled to understand the risk and compensating controls that may be required. Using GenAI in some scenarios can be challenging and needs robust control. Cautionary tales so far include Google, which suffered a $100 billion stock price crash after its chatbot shared inaccurate information in a promotional video. The delivery firm DPD disabled part of its chatbot after it swore at a customer, called itself useless, and criticised the delivery company. A prankster tricked the car manufacturer Chevrolet’s chatbot into agreeing to sell him a new car for one US dollar. These expensive and brand-damaging events could have been avoided by putting observability, testing, and good architecture in place.
AI Centre of Excellence (CoE)
Similar to a Cloud Centre of Excellence, which you may be familiar with, an AI CoE promotes and embeds AI within an organisation at scale whilst maintaining quality and safety.
AI CoE Key Elements
1. AI Ideation, Prioritisation and Business Cases
Generate AI innovation appropriately assessed and prioritised against organisational needs and strategy. Focus on developing a solution and producing proof of concepts. Ensure that you have a robust business case. Is the solution justified and viable? How mature is your environment? Consider assessing your organisation’s digital maturity.
2. Governance and Enablement
Implement structured frameworks and guardrails for AI deployment to ensure data security and prevention against unintended consequences. Focus on your AI strategy, framework, and opportunities for collaboration and influence in all areas of your organisation. You would do well to set up an AI Governance Board with clear roles and responsibilities. Consider ethical, environmental and regulatory compliance. Focus on pattern creation, governance, quality management and data security protection.
3. Delivery
Deploy AI solutions with the required tools, skills and frameworks in a controlled environment. Focus on ensuring you have the technical capability for tooling, modelling and observability and baseline those technical prerequisites. In delivery, ensure that you have change management processes in place. Communication is key, so do so transparently and frequently with all stakeholders.
4. Operation and Continuous Improvement
Once you’re up and running, to leverage any emerging opportunities in AI, you would do well to adapt the operating model when necessary and foster a continuous improvement culture. Focus on reviewing your operating model, taking into account lessons learned. Continually monitor AI trends and developments, and ensure you upskill your people so that they have the required capability to take advantage of those new developments. Communication and knowledge sharing should be at the forefront. Consider implementing AI champions so everyone in your organisation can reap its benefits safely. Finally, ensure that you have FinOps firmly in place to monitor your costs, maintaining value for money.
Outcomes of an AI Centre of Excellence
By implementing an AI CoE, you will have the assurance that your organisation can fully exploit AI safely. You can deploy cutting-edge solutions quickly, consistently, and flexibly while maintaining robust structure and governance. You can provide value-added solutions and take advantage of emerging opportunities. Ultimately, you can provide more for less and deliver a measurably improved service for your citizens.
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