Mathematics: The future of AI as an important foundation for generations

The World Economic Forum 2025 reports AI, Big Data, Science and Technology as a fast-warming skill group. BLS estimates that in 2024-2034 the employment of information scientists grew by 34 per cent and mathematicians and statisticians by 8 per cent; The DSAI programme of the Nanyang Polytechnic University also places statistics, computing and AI training in the same degree structure. The language behind AI is still math. Large language models, machine learning, referral systems, financial controls, medical images, semi-directional processes, quantitative transactions, actuarial models, which appear to be the technological industry, are all too far away from mathematics to go deep. Mathematics, not just the subject.

It trains a person in the ability to turn chaos into formulas, models, logic and inferences. The stronger AI, the more people need to understand math, the more many students think that the AI tool will make math less important, the more opposite it is. The question of the evolution of AI will end up in mathematics. Linear algebra: AI model, image recognition, vector database calculus: in-depth learning, optimization, gradient decline probability statistics: information analysis, risk prediction, A/B testing discrete mathematics: algorithms, passwords, information security Math modelling: finance, medicine, transportation, energy, business decision-making AI generation missing people who can judge tool results, design models, dismantle problems.

The way forward for mathematics has been broader than in the past, with many first impressions of teachers, institutes and candidates for public office. Today's mathematics department is aligned with AI, information science, finance technology, actuarial, semiconductor, software engineering. Mathematics students can move in these directions in the future: 1 Data Science assists enterprises in decision-making with statistics, machine learning and data analysis. 2 AI / Machine Learning study models, algorithms, optimization and information structure. 3 FinTech enters quantitative transactions, risk models, investment analysis, credit ratings. 4 Actuarial Science calculates insurance, pensions and long-term risks using probability and statistics.

5 Processing process information, good performance analysis, optimization and simulation. 6 Data security is protected by discrete mathematical, mathematical and algorithms. Math is like a million-dollar key. It connects AI, finance, engineering, actuarial, research and education. In an era of rapid technological change, the core asset of mathematics to students is the ability to think deep and cross-cutting transformation.