As AI becomes more capable, affordable and autonomous, it is changing the cost of cognitive work, what professionals can achieve and which new services become possible. For banks, this raises strategic questions about workflows, workforce capabilities and competitive advantage.
AI is changing the time, expertise and cost required for cognitive work. Across software, mathematics and science, it is making some tasks more efficient, helping people achieve more and opening up new possibilities.
Developers can use AI to accelerate first prototypes, explore alternatives and test ideas more quickly. Production-quality software still requires testing, security review and human judgement.
AI systems have demonstrated the ability to solve difficult mathematical problems, including gold-medal-level performance at the 2025 International Mathematical Olympiad.
AI can contribute to exploring new algorithms and scientific possibilities, not only retrieving known information or following instructions.
The significance extends beyond doing existing tasks faster. Where can AI strengthen human expertise, and which entirely new services and forms of work might become possible?
The gains from AI-assisted development vary by task, tool and human review. For the mathematical reasoning example, see Google DeepMind's 2025 IMO result ↗.
CDE distinguishes three effects of innovation: making existing work cheaper, better or faster; enabling something genuinely different; and enhancing what professionals can achieve. Each has distinct implications for strategy, technology and skills.
CDE helps leaders distinguish different opportunities for work and value creation. The outcomes depend on where and how an institution applies the technology.
Consider credit analysis in a bank. AI might make routine analysis more efficient, enable a different lending proposition or strengthen an analyst's judgement. CDE helps distinguish these opportunities.
AI can extract data, draft initial assessments and accelerate standard checks. Human effort shifts towards reviewing exceptions and critical decisions.
Banks might build new kinds of ongoing, tailored assessment or serve cases that were previously too costly to evaluate.
Analysts can investigate more scenarios, test assumptions and concentrate on complex risk questions, with appropriate validation.
Illustrative scenarios of how AI could reshape credit analysis in a bank.
These effects will not be uniform. Their consequences depend on the work, the individual and the choices made by institutions.
The same technological shift creates two connected sets of choices: how banks redesign work and how they develop the people who will do it.
Start with a critical function. Map the tasks AI could change, identify where domain expertise and human judgement will matter most, and examine how employees, including new joiners, will continue to develop those capabilities. Use this to prioritise workforce development.
Select a high-value business workflow. Use CDE to find opportunities to improve efficiency, strengthen decisions and create new value. Then prioritise experiments with clear commercial outcomes, governance requirements and workforce implications.
Explore the research and frameworks behind this perspective, and their implications for jobs, skills and business models.
How AI may change professional work and employment.
Explore the book ↗How people, organisations and nations can prepare for an AI-enabled future.
Read the whitepaper ↗A lens for understanding substitution, enhancement and new value creation.
Explore the framework ↗The changing economics of work raises connected questions about professional skills, AI proficiency and how organisations build competitive advantage.
Tell us which workforce and business questions are most pressing. We can explore where work is changing, the capabilities your people need and a practical starting point for your institution.