FINx Your Questions Answered: AI

Alan Brown: I believe we are witnessing a very significant shift in technical capability. The speed of the technology advancement and its adoption are remarkable. There is no doubt that, in many areas, AI-driven technologies are in many cases already operating at, or beyond, human capability (e.g. in some health diagnostics areas). This will increase in the coming months. Jersey, like others, will need to find ways to cope with these changes and understand the implications for all aspects of business and society. Greater focus on building more agile change mechanisms will be vital.

Alan Brown: AI covers a broad area of technology. I usually distinguish three broad overlapping categories.
Generative AI is LLM based and aimed at simple predictions based on large amounts of training data. The responses are refined over time as the system learns from feedback.
Predictive AI uses historical data and a variety of data science techniques to analyse new situations and predict their characteristics. It is being widely used in areas such as health, science and manufacturing.
Physical AI addresses many physical devices being controlled and operated by AI. They learn from their surroundings and improve operation through feedback. For example, in warehouses and car assembly plants.

Alan Brown: I don’t think there is any doubt we are in an AI bubble. The over-hype and commercially-driven excitement about AI is inevitable due to the massive investments taking place. The key question, as with all bubbles, is what remains after the bubble bursts? And how can that be leveraged to best effect? For AI, the new algorithms, data analytics techniques and data sources will remain and offer great value to organisations as they move forward.

Alan Brown: As with all digital transformation, strong governance approaches are needed to be successful. The adoption of new technologies always demands change management to be used as a key element of the governance approach. AI is no different in this regard. Equally, expectations must be managed to align with the reality of adopting and scaling new technology. We have enough experience to know that this will take time and require careful management to be successful.

Digital Jersey: Yes, there is a manageable risk. Jersey must remain product agnostic and ensure local developers complement (rather than replace) globally competitive solutions. Digital Jersey can mitigate this by maintaining open procurement principles, encouraging multi-vendor ecosystems and supporting local developers to upskill and partner with international firms.

Digital Jersey: Jersey can be digitally competitive, but not by being fully independent of external tools. Instead, competitiveness comes from becoming a rapid adopter, integrating best-in-class global technologies and building unique value through local specialisation, regulatory nimbleness and talent.

Digital Jersey: Financial services can manage fragmentation through standardised AI governance, shared best practice frameworks and cross industry upskilling. Digital Jersey is providing structure by chairing the AI Council, producing shared guidelines, running AI skills programmes and connecting organisations with vetted global and local vendors.

Digital Jersey: There are three Government of Jersey representatives on the AI council, leading on all parts for the Government. Additionally, Digital Jersey is working with CYPES and Skills Jersey to develop the Digital Jersey STEM Pathway, which coordinates opportunities in and after education.

Digital Jersey: Digital Jersey will educate people through formal training (AI Leadership training), accessible public learning (AI Insight Series), online resources, and partnership-driven programmes that raise AI literacy across the Island.

Digital Jersey: Some traditional entry level tasks will be automated, which may reduce conventional internships. However, new opportunities will emerge in AI augmented roles, including data work, AI operations, prompt engineering and digital process oversight. The challenge is redesigning early career pathways, not eliminating them.

Digital Jersey: Yes. As organisations embed AI into operations, hiring strategies will shift toward roles such as AI support analysts, prompt engineers, context engineers, data stewards and automation coordinators. AI assisted roles may become the new entry level norm, combining business understanding with AI tool interaction.

JFSC: We are not introducing any specific regulations or rules regarding using AI in business. We will be publishing some guidance, following consultation with Jersey’s AI Council, which we hope will be helpful and support businesses that want to use AI. We expect this to be issued in Q1 of 2026.

JFSC: We’ve taken a practical, people first approach. All staff now have access to Copilot Chat and we’re trialling full Copilot with senior leaders. We’ve also onboarded a dedicated AI resource to help the JFSC develop AI-enabled process improvements, such as early HR and Comms agents.

JFSC: We’ll be transparent about the principles and safeguards behind any AI we use in examinations, but we won’t publish proprietary technical models. What firms can expect is clarity on how AI supported decisions are governed, the factors we consider and the human oversight built in to decision making because explainability and accountability are essential to our approach.

JFSC: We are not currently using AI to integrate supervision visit data. We are exploring where AI may assist in future supervisory analytics, but any such use would follow a risk based, transparent and proportionate framework. If we were to deploy AI in this area, we would ensure firms understand the purpose, governance and safeguards involved, consistent with our commitment to openness and responsible adoption.