For candidates in Forex, CFD, FinTech, payments, investment firms and other regulated financial-services businesses, the AI conversation is moving into a new phase.

Until recently, much of the career advice around AI focused on learning how to use the tools. That is no longer enough.

New research published by CFA Institute on 16 September 2026 says investment firms are beginning to redesign entire roles and workflows around AI rather than treating it simply as another technology tool. At the same time, firms continue to emphasise human judgment, analytical rigour, interpretation and communication rather than moving directly towards full automation.

For financial-services professionals, this creates an important career question:

If AI can perform more of your current tasks, what will make the remaining part of your job more valuable?

1. Stop Measuring Your Value by How Much Work You Produce

Many traditional financial-services roles contain significant amounts of processing.

Preparing reports. Collecting information. Checking documents. Reconciling data. Researching regulations. Producing first drafts. Creating management information.

AI and automation can increasingly accelerate parts of this work.

That does not necessarily make the employee less important. It changes where the value sits.

The valuable employee becomes the person who can determine what the information means, whether it can be trusted and what the business should do next.

CFA Institute’s latest research says demand is increasing for analytical and interpretation skills, critical thinking, judgment and decision-making as AI changes financial workflows.

Action for you: look at the five activities that consume most of your working week. For each one, ask: Am I mainly producing information, or am I interpreting it and helping someone make a decision? Try to move gradually towards the second category.

2. Become the Person Who Can Check the Machine

One of the most useful skills in an AI-enabled financial organisation may be the ability to recognise when technology is wrong.

That is particularly important in regulated businesses.

A Compliance professional cannot simply accept an AI-generated interpretation of a regulation. Finance cannot automatically trust an unusual calculation. A dealer or risk professional cannot accept a model output without understanding its assumptions. Legal professionals need to verify citations and contractual conclusions.

CFA Institute’s 2026 employer research says firms want AI, machine-learning, data and coding capabilities, but still expect professionals to validate, interpret and improve AI-generated outputs.

This creates an interesting career advantage for experienced professionals. The more deeply you understand your subject, the better positioned you may be to use AI safely because you can recognise questionable results.

Action for you: when using AI professionally, don’t only record what it helped you produce. Develop a repeatable method for checking its sources, assumptions, calculations and conclusions. Be prepared to explain that verification process during an interview.

3. Build a Combination of Business + Technology Expertise

The strongest career opportunity may not be becoming an AI specialist.

It may be becoming the person who understands both the business and the technology affecting it.

CFA Institute’s September research says demand is growing for cross-functional finance-and-technology expertise as investment firms redesign their operating models.

That principle translates particularly well to Forex and FinTech.

Think about combinations such as:

Compliance + technology – understanding regulation as well as automated monitoring, data and AI governance.

Payments + analytics – understanding PSPs and payment flows while being able to analyse approval rates, fraud and performance data.

Finance + automation – understanding accounting and treasury while improving reporting and reconciliation workflows.

Dealing + data – combining genuine market and liquidity knowledge with stronger quantitative analysis.

Legal + FinTech – understanding contracts and regulation alongside payments, digital assets or technology infrastructure.

Action for you: choose one adjacent capability that strengthens your existing expertise. You do not need to change profession. Make your existing profession harder to replace.

4. Human Skills Are Becoming More Important Alongside AI

There is an apparent contradiction in the current market.

Employers want more AI capability – but they are simultaneously placing significant value on distinctly human skills.

CFA Institute research involving 500 finance managers found that soft skills were considered the largest skills gap among new finance professionals, ahead of AI and quantitative skills. Sixty-seven percent identified soft skills as contributing to employability, compared with 49% for AI skills.

That makes sense.

As technology produces more analysis and information, somebody still needs to explain it, challenge it, persuade colleagues, manage disagreements, communicate with clients and ultimately take responsibility for decisions.

This becomes even more important as you progress towards management.

Action for you: prepare examples showing how you influenced a decision, explained something complicated, resolved a disagreement, coordinated departments or persuaded somebody to change approach. These are skills. Treat them like skills.

5. Don’t Ask Only ‘Will AI Replace My Job?

That question may be too broad to be useful.

A better question is:

Which parts of my job will AI probably perform – and which parts should I become exceptionally good at?

PwC’s 2026 Financial Services AI Jobs Barometer finds that financial services has one of the highest rates of skills transformation across the sectors it examined, with AI exposure associated with substantial changes in the skills employers request.

Separately, PwC’s Financial Services Workforce AI Survey reported in August that nearly eight in ten financial-services leaders surveyed expect their workforce to shrink by at least 20% over the next five years, although PwC warns that simply modelling headcount reductions is different from designing the workforce organisations will actually need.

For candidates, this is a reason to prepare – not panic.

The objective should be to migrate towards the parts of your profession involving greater judgment, accountability, relationships, interpretation and business impact.

Action for you: write down three things AI could realistically automate in your current job. Then identify three higher-value responsibilities you could develop with the time saved. That becomes your personal career-development plan.

What Should You Do During the Next 30 Days?

Don’t sign up for ten AI courses.

Choose one genuine workflow from your existing job.

Learn how AI or automation could improve it. Test the process safely without exposing confidential company or client information. Understand where the technology performs well and where human checking remains necessary.

Then document:

The problem -> the tool -> your process -> how you validated it -> the result.

That gives you something much more valuable than another line saying ‘Proficient in AI’ on your CV.

It gives you a real interview story.

Conclusion

AI is unlikely to affect every financial-services profession in exactly the same way.

But the direction is becoming clearer.

Routine execution is becoming easier to automate, while judgment, interpretation, cross-functional expertise, communication and accountability become increasingly important.

The strongest career strategy is therefore not competing with AI at the tasks technology performs best.

It is learning to use the technology while developing the capabilities that allow you to challenge it, interpret it and turn its output into better business decisions.

Ready for Your Next Career Move?

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Explore relevant opportunities or submit your CV through FXCareer.eu to be considered for suitable positions.

Key Sources

CFA Institute – How the Investment Industry Is Rethinking the Operating Model in the AI Era, 16 September 2026
https://www.cfainstitute.org/insights/articles/how-investment-firms-are-organizing-for-ai

CFA Institute – What Employers Want: A New Skills Blueprint, 6 March 2026
https://www.cfainstitute.org/insights/articles/employers-new-skills-blueprint

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