The biggest question many industries face: will AI take jobs from humans?
We spoke to the course leader of MSc Finance and Investment and BA (Hons) International Finance (Top-up), Xiehua Ji, about the emergence of AI in the fields of Accounting, Finance and Economics. Xiehua has been making an effort to integrate AI into his teaching since 2024.
If someone is considering a career in Accounting, Finance and Economics, should AI’s increased capability make them worried or excited about the future?
The worry is real: AI is absorbing routine tasks like data entry, reconciliation, and basic research, so traditional entry-level roles are shrinking.
But judgment matters more, not less. AI cannot sign off, take responsibility, or know when its own output is wrong. People who can interrogate and validate AI results will stay in demand.
The career ladder is changing shape, not disappearing. Build technical fluency, learn to question AI output, and develop judgment machines cannot copy. Those who do should be excited - AI will make their judgment more valuable, not less.
Is it possible that AI could create more opportunities rather than taking jobs? If so, what roles or opportunities might emerge?
Yes. AI can create more opportunities than it removes, though it may push some conventional low-end jobs to high-end jobs. Based on my view, some potential future opportunities could be (1) AI configuration specialist – builds and refines finance AI workflows. (2) AI governance and risk officer - ensures AI-driven decisions meet regulatory and ethical standards. (3) AI supervisor - provide guidance to employees who will use AI for work.
Which tasks in Accounting, Finance and Economics are most likely to be automated and which ones will still need a human?
Automated: routine, rule-based tasks - data entry, invoice processing, reconciliations, standard tax returns, audit evidence matching, and first-draft disclosures.
Human: judgment and accountability - exception handling, policy and control design, sign-off responsibility, contextual interpretation, client relationships, and advisory work.
What advantages do graduates have over automated systems?
Graduates still have a real edge over machines. They can make judgment calls when situations are unclear, take responsibility and sign off on decisions, understand people and office dynamics, spot when a system's output is wrong, and explain and defend choices to clients and regulators. Machines handle what is known and repeatable; graduates handle what is unclear, what needs accountability, and what involves people.
Will employers look increasingly look for graduates who are confident with AI tools?
That is for sure, given above expectation of future careers’ changes. The future AFE posts will mostly include AI’s parts, so employees with proper AI skills are needed.
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What skills should students develop alongside their degree to make themselves more employable in an AI-driven world?
Students should learn to use AI tools well but also learn to question what those tools produce. Alongside their degree, they need practice at thinking through messy problems, explaining their ideas clearly to others, adapting when things change, and knowing when a human needs to step in and take responsibility. It also helps to build a portfolio of real work they can show and explain to employers, because a list of grades alone no longer stands out. In short: use AI confidently but build the judgment and accountability that make it useful rather than risky.
Which human skills will be more valuable as AI advances?
As AI handles more routine work, the most valuable human skills are judgment in messy situations, critical thinking to spot when AI is wrong, communication and relationship-building, empathy, ethical responsibility, and adaptability. These are the things AI cannot reliably do—and the more it advances, the more they matter.
What will the next 10 years of industry look like? How about education?
Accounting, Finance and Economics in Industry: Routine transactional work becomes largely automated. Human value moves to managing AI agents, resolving exceptions, interpreting context, and advising on strategy. Accountants will spend much more time either managing AI at scale or doing business partnering.
Accounting, Finance and Economics in education: Shift from teaching technical execution to teaching judgment, AI oversight, and business partnering. Routine knowledge is already embedded in tools, so curricula must build professional understanding of how AI work and the ability to interrogate AI outputs.
How are BCU preparing students for a career in Accounting, Finance and Economics alongside AI?
Currently BCU is moving stably from a non-AI period to AI-embed period. Suggestions from me will be like BCU can try to encourage and even push AI skills to be embedded in most relevant modules’ teaching and learning.
What advice would you give to a student to prepare for an AI driven workplace?
Use AI tools fluently but learn to question what they produce, because the real skill is knowing when the output is wrong. Build judgment by practising messy, real-world problems rather than just textbook ones. Be good at explaining your thinking clearly to others, since communication and trust will matter more as routine work disappears. Keep a portfolio of real projects you can show and defend. And stay adaptable - the tools will keep changing, so the ability to learn and update your thinking matters more than mastering any single tool.
