What must change in mathematics education for the data and AI-driven age?

By Winifred KOTIN

For many of us, mathematics was not a subject to love—it was a subject to pass so we could progress to the next academic stage. Through years of conversations with executives, educators, parents, and aspiring technology professionals, one troubling question keeps returning: What if we have been teaching mathematics the wrong way all along?

This is not a question born out of theory alone but from lived experience and repeated observation. Like many people, I did not enjoy mathematics in school. It felt abstract, intimidating, and largely unrelatable to my real life. I passed my exams—mostly through memorization and sheer willpower.

For many learners, mathematics has been a source of anxiety, frustration, and exclusion. It has shaped academic confidence, influenced access to higher education, and quietly determined who feels “smart enough” to pursue certain paths. For some, mathematics became the gatekeeper that closed doors long before potential could be fully realized. In an age defined by data and artificial intelligence—should mathematics still be feared in a world where its relevance has never been more visible? My answer is an emphatic no.

Rethinking what mathematics really is

One challenge lies in how mathematics has traditionally been defined and presented. Often, it is described as the science of structure, order, and relationships, rooted in counting, measuring, and abstract reasoning.

I prefer a more understandable and relevant definition.

Mathematics should be renamed Decision Making Science and defined as a problem-solving and decision-making science that utilizes numbers, patterns, and formulas to facilitate more precise and accurate decisions.

This reframing is particularly important in the field of technology. In my book, The Ultimate Beginner’s Guide to Technology Careers, I included a section titled Mathematics and Technology Careers to demystify the subject. This was inspired by countless conversations with individuals eager to enter the tech industry who asked, often with visible concern, “My mathematics is weak—do I still have a chance?” The anxiety behind this question reveals a deeper problem with several consequences.

The cost of a misaligned mathematics education

When mathematics is introduced poorly or taught without relevance, the consequences extend far beyond the classroom.

• Overloaded curricula that prioritize content coverage over true understanding, and relevance breeding fear instead of curiosity
• Students losing confidence early and missing the intellectual satisfaction that comes from solving real-world problems with greater accuracy.
• Individuals abandoning careers they could have excelled in because mathematics feels like an insurmountable barrier
• Teachers becoming frustrated as they repeatedly teach abstract concepts to learners who feel overwhelmed and disconnected
• Poor decision-making within organizations resulting in financial waste, operational inefficiencies, and missed revenue opportunities

Mathematics (Decision Making Science) as a Daily Life Skill

Ironically, mathematics is one of humanity’s most powerful problem-solving tools—yet many are conditioned to fear it rather than harness it.  We all rely on mathematics every day; examples can be seen in carpentry, surgery, cooking, sewing, engineering, software engineering, designing, architecture, masonry, construction, and many other disciplines.

What should we be doing differently in the Age of Data and AI?

Today, hundreds of millions of terabytes of data are generated every single day—and that volume continues to grow exponentially. Data, however, is only as useful as our ability to interpret it, reason with it, and make decisions from it. To prepare learners for a data-driven and AI-powered world, we must rethink how mathematics is taught and applied.

• Policymakers and educators must redefine mathematics as a practical decision-making and problem-solving discipline, not just a theoretical subject.
• Curricula must be age-appropriate and relevant, focusing early learning on reasoning, patterns, estimation, and everyday problem-solving rather than abstract complexity.
• Academic and career progression requirements should be relevance-based, aligning mathematical expectations with the actual needs of specific disciplines.
• Parents must nurture confidence, supporting children beyond grades and reinforcing that mathematics is for problem-solving and not an indicator of intelligence.

Redefining Mathematics for the Data and AI Age

In the age of data and artificial intelligence, mathematics should no longer intimidate—it should empower. If we get this right, mathematics (decision-making science) can become a bridge rather than a barrier—opening doors to innovation, inclusion, and opportunity in a rapidly evolving world.

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