Financial Specialists, All Other

Financial work today is partly supported by technology. For example, routine tasks like processing invoices, reconciling accounts and generating basic reports are commonly automated with software ^[1]. Even charting and number‐crunching in spreadsheets can be done quickly by computer tools ^[2].

Likewise, people increasingly ask AI chatbots for money advice – one 2025 survey found 66% of Americans did so ^[3]. But experts warn these tools can give misleading answers on finance ^[3], so human oversight remains important. In short, many mathematical or data tasks in finance can be aided by AI or automation, but jobs that need judgment, communication and ethics (like giving trusted advice or interpreting complex cases) are still hard to automate.

AI is becoming more available for finance, but its spread may be gradual. On the plus side, research shows big cost savings with AI: Morgan Stanley estimates full AI use could save U.S. companies ~$920 billion a year (mostly by lowering labor costs) ^[4]. Many finance leaders agree AI will be common soon – a Deloitte poll found ~81% expect AI-driven tools to be standard in finance within five years ^[5].

However, today only about 13–14% of finance teams actually use advanced AI agents ^[5]. Key barriers are trust, integration and expertise – for example, 21% of surveyed finance pros cited trusting AI as a top concern ^[5]. Also, finance firms face strict rules and data privacy needs, so they move carefully.

Encouragingly, the Bureau of Labor Statistics projects modest growth (3–4%) in these finance jobs by 2034 ^[2]. That means there will still be demand for human specialists. In short, AI can speed up and improve many finance activities, but it will take time, money and training to adopt it fully.

While AI handles some routine work, human skills – especially critical thinking, communication and ethical decision–making – will remain valuable in these careers.