The Joy of the Struggle: Mathematical Problem-Solving in the Age of AI

As we honor Srinivasa Ramanujan on National Mathematics Day, I find myself reflecting on a paradox of our times. Mathematics was always my favorite subject—that unique thrill of arriving at the right answer through logical reasoning, the satisfaction when complex problems yielded to persistent effort. We possess unprecedented computational power—AI can solve complex equations in milliseconds, optimization algorithms process millions of scenarios, and machine learning models predict financial outcomes with remarkable accuracy. Yet something precious may be slipping away: the profound satisfaction of wrestling with a mathematical problem until breakthrough arrives.

I remember my early days as a finance professional, armed with a calculator and spreadsheet, spending hours building financial models from first principles. Each formula was carefully constructed, every assumption rigorously tested. There was an intimate relationship between problem and solver—a dance of logic, intuition, and persistence. When the numbers finally balanced, the satisfaction was visceral.

Today, as a Senior Finance Leader guiding multiple organizations, I too leverage AI tools that generate financial projections and identify patterns in vast datasets within seconds. The efficiency gains are undeniable but questionable too. I still question assumptions, interrogate the relationship with outputs, and trust when my sense says the answer won't solve the customer problem. The mathematical logic beneath the surface doesn't always address what truly matters.

Ramanujan's genius wasn't just in finding answers—it was in his intuitive understanding of mathematical relationships, his ability to see patterns others missed. These qualities emerged from deep engagement with problems, not from consulting an oracle for solutions.

The real danger of our AI era isn't that machines solve problems for us—it's that we'll stop developing the mathematical intuition that allows us to frame the right problems, challenge assumptions, and recognize when something doesn't add up. In finance, this intuition differentiates a technician who runs models from a strategic finance leader who shapes business outcomes.

The struggle to solve problems develops mental muscles no AI can build for us. It cultivates pattern recognition, logical reasoning, and creative problem-solving that remain uniquely human. On this Mathematics Day, perhaps our greatest tribute to Ramanujan is preserving the spirit of mathematical exploration that made his discoveries possible. In an age where answers come easy, the question—and the journey to its solution—often matters more than the destination.

Deepti Bio

Deepti Beri is a Chartered Accountant and Strategic Finance Leader. She is the founder of BizWiseAdvisors.com a leading consulting firm, specialising in CFO Services, AI and Automation in Finance and end to end Startup Advisory. She serves as Board Member, Fractional CFO and Independent Advisor. She founded and scaled multiple ventures while driving governance excellence across multinationals.