What keeps our personalised AI answers accurate?

Personalised AI answers need room to respond to individual circumstances, but recommendations should remain grounded in trusted knowledge. For UST, NavigatorAI combined generative flexibility with carefully structured rules and trusted content, rather than relying on predetermined outcomes or unaided generation. UST's proprietary AI expertise kept recommendations aligned with the company's services, while publicly available firmographic and demographic data made interactions relevant to each user. The practical distinction is between information that personalises a journey and expertise that grounds its recommendations. In its 2026 observations of UK financial services firms, the Financial Conduct Authority described firms constraining chatbots to approved source material and adding checks and escalation routes. Define the knowledge and service boundaries before allowing the model to vary its answers.

Human oversight should be part of designing and running a personalised AI experience, not a substitute for careful development. For UST, NavigatorAI progressed from a functional prototype developed in two weeks to a refined, tested and launched experience within six weeks. Human creativity remained central to prompt design and optimisation, while recommendations drew on UST's AI playbook and expertise. Human oversight helped keep the experience accurate, engaging and valuable throughout the journey. The practical lesson is to combine hands-on knowledge of generative tools with professional expertise: access to a model alone does not produce quality output. Keep experts involved in refining prompts, testing the experience and judging whether personalised answers remain aligned with the organisation's knowledge, services and values.