1. AI Skills Are Moving Beyond the Technology Department

AI capability is increasingly relevant within existing professions, not only technology teams. Compliance may use AI-assisted regulatory research and document analysis; Finance may use automation, forecasting and reporting; Payments may use transaction analysis and fraud monitoring; Risk may use scenario modelling and data analysis; Marketing may use AI-assisted research and campaign optimisation; and Technology teams may focus on integration, automation, data infrastructure and governance.

For employers, the practical implication is to reconsider job descriptions across the organisation rather than simply creating an isolated “AI team.”

2. Do Not Recruit AI Skills at the Expense of Industry Knowledge

In regulated financial services, deep professional expertise still matters. A Compliance Officer needs to understand AML/CFT and regulatory obligations. A Dealer still needs execution, liquidity and risk knowledge. A Payments Manager still needs experience with payment flows, PSPs, reconciliation and fraud. A Finance professional still needs accounting and reporting expertise.

The strongest candidate may not be the person with the longest list of AI tools, but the professional who can explain how technology makes them better at the job they already understand.

3. Employers Should Start Interviewing Differently

Instead of asking only “Do you have experience using AI?”, employers can ask for a real example of a task the candidate improved using AI or automation, how the candidate verified the output, and what information they would never enter into a public AI tool.

These questions test practical capability, professional judgement and awareness of risk – all essential in businesses handling client information, trading data, payment information and regulatory documentation.

4. Upskilling Existing Employees May Be as Important as External Hiring

Recruitment should not automatically be the first response to every new skills requirement. A strong Compliance Officer can learn AI-assisted research. An experienced Accountant can learn analytical and automation tools. A capable Payments professional can strengthen data-analysis skills.

Employers should map skills into three categories: skills already available internally, skills existing employees can realistically learn, and skills that genuinely need to be recruited externally.

5. The Job Description Needs to Change Before the Candidate Does

One common mistake is looking for 2026 skills using an older job description. Update vacancies to reflect real business needs, but avoid unrealistic wish lists.

Organise requirements into core expertise, technology capability and adaptability. The long-term skill is not knowledge of one particular tool; it is the ability to adapt professional expertise as technology changes.

Building Your Forex or FinTech Team?

FXCareer specialises in recruitment across Forex, CFD, FinTech and financial services, including Csuite executives and senior leadership, Compliance, Dealing, Payments, Finance, Risk, Technology, Operations and Marketing.

Sources

• PwC – “The AI workforce planning gap in financial services” (3 August 2026):
  https://www.pwc.com/us/en/industries/financial-services/library/ai-workforce-gap-financial-services.html
• Cambridge Centre for Alternative Finance – “The 2026 Global AI in Financial Services Report”:
  https://www.jbs.cam.ac.uk/wp-content/uploads/2026/04/ccaf-2026-04-28-global-ai-in-financial-services-report.pdf
• CFA Institute – “What Employers Want: A New Skills Blueprint” (6 March 2026):
  https://www.cfainstitute.org/insights/articles/employers-new-skills-blueprint