top of page
Solirius Reply - LOGO RGB.png

Insights

AI in action 2: Supporting Service teams through the Service Standard Operational foundations

  • Writer: Matt Hobbs
    Matt Hobbs
  • Jul 17
  • 9 min read
AI in action 2: Supporting Service teams through the Service Standard Operational foundations by Matt Hobbs.
AI in action 2: Supporting Service teams through the Service Standard Operational foundations by Matt Hobbs

In this second post in the series, we begin to explore how artificial intelligence can directly support teams in meeting the UK Government Service Standard. If you missed it, you can read the first article here (opens in a new tab). By aligning the capabilities of current AI tools, and those on the horizon, with the needs of service teams, we can start to see a clear path where AI acts as a multiplier for quality, consistency, and speed.


We’ll examine the first five points of the Service Standard, which focus on understanding users, solving whole problems, providing joined-up experiences, simplifying services, and ensuring accessibility for all. These points sit at the very heart of designing inclusive and effective public services.


While AI is not a silver bullet, its responsible and deliberate use can free up a team's precious time and resources to focus more deeply on strategy, empathy, and continuous improvement. The use of AI can do this by taking on the “heavy lifting” of data analysis, pattern recognition, and user insight generation. Let’s look at where AI is already making an impact, and where future innovation could lead us next.


Where AI can help


Point 1. Understand users and their needs


Service Standard summary: This point of the GOV.UK Service Standard emphasises the importance of developing an in-depth understanding of users and the issues they face. By focusing on the user's context and the issues they are trying to solve, rather than preconceived solutions, service teams can effectively meet user needs in a simple and cost-effective manner. This approach involves conducting user research, creating quick prototypes to test hypotheses, and utilising data from various sources to gain comprehensive insights into user difficulties.


In the sections below, I outline solutions service teams can use now, along with future opportunities for AI to support them.


Existing AI tooling:

  • AI-Powered User Research Analysis: AI-driven tools like Dovetail and Affectiva can analyse qualitative user research data (interviews, surveys, feedback etc) to identify patterns and trends.

  • Chatbots and Conversational AI: Tools like ChatGPT, Intercom, or Drift can collect real-time user queries, providing insights into common pain points and unmet user needs.

  • AI-Driven Sentiment Analysis: AI tools like Lexalytics or MonkeyLearn can analyse social media, feedback forms, or customer support interactions to detect emerging issues.

  • Predictive Analytics for User Behaviour: Platforms like Google Analytics with AI insights or Amplitude use AI to predict user needs based on past behaviours.

  • A/B Testing Optimisation: AI-powered A/B testing platforms like Optimizely can help refine service designs by automatically analysing user interactions and determining the best-performing options.


Future AI innovations:

  • AI-Generated User Personas: Instead of manually creating personas, AI could dynamically generate data-driven personas based on real-time user interactions.

  • Autonomous User Research Assistants: AI-driven digital assistants could conduct real-time user research, asking adaptive questions based on previous responses.

  • AI-Powered Prototyping: Future AI tools could automatically generate prototypes based on user behaviour data, helping teams iterate on designs more quickly and efficiently.

  • Emotion Recognition and Adaptive UX: While AI technologies like facial recognition or voice analysis could potentially detect user frustration or satisfaction and adapt the service experience, it is essential that the privacy implications of such data collection are rigorously evaluated before any implementation is considered.

  • AI-Enhanced Accessibility Testing: AI could simulate how users with disabilities interact with a service, automatically reporting improvements for accessibility back to the service team.



Point 2.  Solve a whole problem for users


Service Standard summary: This section of the GOV.UK Service Standard focuses on designing services that address users' complete needs by collaborating across teams and organisations. This approach ensures services are intuitive and cohesive, minimising the complexity users face when interacting with multiple government services.


Service teams are encouraged to understand constraints, scope services appropriately, and work openly to promote collaboration and reduce duplication. The goal is to create user journeys that make sense without requiring users to understand the internal structures of government.


Existing AI tooling:


Future AI innovations:

  • Cross-Agency AI Integration: AI could unify multiple government services into a single, user-friendly interface, so citizens don’t have to navigate separate systems.

  • Voice-Enabled Government Services: AI-powered voice assistants could allow users to access services through speech, making services more accessible.

  • AI for Policy and Decision Support: AI could analyse patterns in service usage and citizen feedback to recommend improvements or policy changes.

  • Proactive Citizen Support: AI-driven services could anticipate user needs (e.g., reminding users about expiring licences or upcoming payments) and send timely notifications.

  • Bias Detection and Ethical AI: AI systems could be developed to ensure fairness and reduce biases in government services, improving trust and inclusivity.



Point 3. Provide a joined up experience across all channels


Service Standard summary: Point 3 of the Service Standard emphasises designing government services that seamlessly integrate across all channels, online, phone, paper, and face-to-face, to ensure accessibility and a consistent user experience. It highlights the importance of empowering service teams to address issues across any channel, involving frontline staff in user research, and utilising data from both online and offline interactions to drive continuous improvements. Additionally, it stresses that strategies to promote digital adoption should not hinder access to traditional channels.


Existing AI tooling:


Future AI innovations:

  • Context-Aware AI Agents: Future AI assistants could remember user interactions across channels (web, phone, in-person) and pick up conversations where they left off, offering a truly seamless experience.

  • AI-Powered Real-Time Translation and Accessibility: AI tools could automatically translate conversations across languages in real-time (e.g., advanced Google Translate AI) and enhance accessibility by transcribing voice conversations to text instantly for deaf users.

  • Personalised AI Service Recommendations: AI-driven recommendation engines could analyse a user's past interactions and predict their next needs, proactively suggesting the best service channels and steps to take.

  • Unified AI-Powered Digital Identity Verification: Future AI systems could securely verify users across different platforms using biometric authentication, facial recognition, and behavioural analysis, allowing for a smooth transition between online and offline services.

  • AI-Driven Predictive Support: AI could analyse historical data to predict when users might need assistance and proactively offer solutions before they even reach out for help.



Point 4. Make the service simple to use


Service Standard summary: 'Make the service simple to use' emphasises designing government services that are intuitive, accessible, and easy for users to navigate. It stresses the importance of understanding user needs, removing unnecessary complexity, and ensuring services work for everyone, including those with disabilities or low digital skills. Services should be tested with real users, provide clear guidance, and avoid technical jargon to create an intuitive experience.


Existing AI tooling:


Future AI innovations:

  • Emotionally Aware Chatbots: AI could detect frustration or tone and adjust responses accordingly.

  • Context-Aware Search: AI could understand past interactions to auto-filter irrelevant results.

  • Dynamic Accessibility Adjustments: AI-powered interfaces could adapt layout and readability based on cognitive load or disabilities.

  • Predictive and Adaptive Forms: Forms could dynamically adjust based on user needs, for example: reducing unnecessary form fields on digital interfaces.

  • Fully Adaptive Interfaces: AI could modify interface layouts, font sizes, and navigation based on user behaviour.

  • AI-Driven Digital Assistants for Task Completion: AI could submit documents and complete applications on behalf of users.

  • AI-Powered Nudges: AI could guide users to complete key tasks based on previous behaviour patterns.

  • Multimodal AI Interactions: AI could seamlessly switch between voice, text, and gestures depending on user preference.

  • Real-Time Emotion Detection for Support Teams: AI could alert teams when users are struggling, allowing instant intervention.

  • Biometric AI for Seamless Security: AI could enable password-free authentication through facial recognition or speech recognition.



Point 5. Make sure everyone can use the service


Service Standard summary: The GOV.UK Service Standard's fifth point, "Make sure everyone can use the service," emphasises designing services that are inclusive and accessible to all users, including those with disabilities, legally protected characteristics, limited internet access, or low digital skills.


Service teams are advised to meet accessibility standards for both online and offline components, conduct user research with diverse participants, and provide appropriate support to ensure no user is excluded.


Existing AI tooling:

  • Automated Accessibility Testing: Tools like axe, WAVE, and Google's Lighthouse, enhanced with AI, help detect accessibility issues in real time (e.g., missing alt text, poor contrast).

  • AI-Powered Transcription & Captions: Services like Google Speech-to-Text, Otter.ai, or Microsoft Azure can provide real-time subtitles and transcripts for audio/video content, improving accessibility for deaf or hard-of-hearing users.

  • Language Translation & Simplification: AI tools like DeepL or Google Translate assist by translating content into multiple languages, while GPT-based tools can simplify complex text, making information more accessible to users with low literacy levels or cognitive impairments.

  • Voice Assistants & Conversational Interfaces: AI-driven chatbots (e.g. on GOV.UK or NHS sites) can guide users through processes using plain language or voice interaction, helping those with visual or motor impairments.

  • Personalisation Engines: AI can adapt interfaces to user preferences, like increasing font sizes, contrast, or offering keyboard-only navigation modes, based on learned behaviours.


Future AI innovations:

  • Real-Time Inclusive Design Feedback: AI design assistants could offer proactive suggestions during development to flag accessibility concerns or recommend more inclusive design patterns.

  • Emotion and Intent Detection: Advanced AI could detect user frustration or confusion through sentiment analysis (e.g. tone of voice, facial expressions) and offer adaptive support instantly.

  • Dynamic UI Generation: AI could auto-generate personalised interfaces based on a user’s device, environment, or abilities, creating a “design-for-one” approach at scale.

  • Augmented Reality (AR) for Navigation: AI-enabled AR could help users with visual or cognitive impairments navigate complex public spaces or digital services using voice-guided overlays.

  • Multimodal Accessibility Agents: Future AI assistants may seamlessly switch between text, voice, visual, and gesture inputs/outputs to match users' preferred interaction mode in real time.


As we’ve seen, AI is already playing a role in how service teams understand users, simplify experiences, and deliver inclusive services. Whether it’s enhancing user research, supporting accessibility, or helping create joined-up services, AI has clear potential to amplify the points behind good service design.


In the next article, we’ll turn our attention to the next group of Service Standard points, those that deal with team structure, agile practices, iteration, and security. These are the operational foundations that support successful delivery, and we’ll explore how AI can support multidisciplinary collaboration, continuous improvement, and safe, secure digital services.


Join me again in the next article as we continue to map the intersection between AI and service excellence, coming soon.


Contact information

If you have any questions about our AI initiatives, Software Engineering services, or you want to find out more about other services we provide at Solirius, please get in touch (opens in a new tab).

Comments

bottom of page