“AI did not make me a mathematician. It just gave me enough Excel formulas to sound dangerous in a meeting.” – MJ Martin
As AMI systems demand more consideration of the design, it taxes the designer to be even more cautious about the placement of gateways, repeaters, and endpoints. So these complex system demand comprehensive calculations to ensure superior RF coverage. Using math has become essential to success. But not every designer is equipped to perform these calculations and derive these formulas. So AI math is a godsend to those of us in need of help.
Artificial intelligence is changing the way ordinary people approach difficult mathematics. For generations, many useful mathematical tools were locked behind years of study, specialist training, or professional software experience. Algebra, trigonometry, calculus, probability, statistics, and complex Excel formulas often seemed intimidating to anyone who did not already speak the language of mathematics. AI is changing that relationship. It does not remove the value of learning, but it does make mathematics more accessible, practical, and usable for people who need results.
One of the most powerful advantages of artificial intelligence is its ability to translate a real-world problem into a mathematical process. Instead of starting with a blank spreadsheet and wondering which formula to use, a person can describe the problem in plain language. AI can then suggest the correct Excel equation, explain what each part does, and adjust it when the first version does not work. This is especially useful because Excel is both simple and extremely powerful. A single formula can combine logic, lookup tables, geometry, date calculations, probability, and conditional rules.
This matters because many people can understand the business problem but not the mathematical structure behind it. They may know what they want to measure, compare, estimate, or predict, but they may not know how to convert that need into a working formula. AI becomes a bridge between intent and execution.
Trigonometry is a perfect example. Many people hear the word and immediately think of school exams, triangles, angles, and mysterious functions such as sine, cosine, and tangent. Yet trigonometry is not just abstract classroom theory. It is a practical tool for measuring distance, direction, slope, height, rotation, signal paths, GPS location, mapping, aviation, construction, radio propagation, and engineering.
The basic idea is that trigonometry describes the relationship between angles and the sides of triangles. Sine, cosine, and tangent are functions that help calculate unknown distances or angles when some information is already known. For example, if you know an angle and one side of a right triangle, trigonometry can help calculate another side. In Excel, formulas such as SIN, COS, TAN, ASIN, ACOS, and ATAN can perform these calculations. The challenge is knowing which one to use, when to convert degrees into radians, and how to structure the equation correctly.
AI makes this much easier. A user can say, “I have two latitude and longitude points. How do I calculate the distance between them?” AI can produce the Haversine formula in Excel. A user can say, “I know the height of an object and the angle of elevation. How far away is it?” AI can create the tangent-based formula. Suddenly, a person who never formally studied trigonometry can use it confidently in a practical spreadsheet.
Once AI helps unlock trigonometry, it becomes natural to move into other mathematical realms. Algebra can be used to rearrange formulas and solve for unknowns. Calculus can help explain rates of change, acceleration, optimization, and growth curves. Probability can help estimate risk, forecast outcomes, and model uncertainty. These fields may sound advanced, but AI can break them into usable steps.
The key advantage is not that AI magically makes someone a mathematician overnight. Rather, it gives the user working access to mathematical tools that were previously too difficult to apply. It can explain, test, correct, and improve formulas in real time.
AI is making hard math easier because it reduces the friction between curiosity and capability. It allows people to ask better questions, build better spreadsheets, and solve problems that once felt out of reach. Used wisely, AI does not replace understanding. It accelerates it. It lets a person begin with a practical need, receive a working formula, and then learn the mathematics through use. That is a powerful shift. Math is no longer just something studied in school. With AI, it becomes something people can actively use.
About the Author:
Michael Martin is the Vice President of Technology with Metercor Inc., a Smart Meter, IoT, and Smart City systems integrator based in Canada. He has more than 40 years of experience in systems design for applications that use broadband networks, optical fibre, wireless, and digital communications technologies. He is a business and technology consultant. He was a senior executive consultant for 15 years with IBM, where he worked in the GBS Global Center of Competency for Energy and Utilities and the GTS Global Center of Excellence for Energy and Utilities. He is a founding partner and President of MICAN Communications and before that was President of Comlink Systems Limited and Ensat Broadcast Services, Inc., both divisions of Cygnal Technologies Corporation (CYN: TSX).
Martin served on the Board of Directors for TeraGo Inc (TGO: TSX) and on the Board of Directors for Avante Logixx Inc. (XX: TSX.V). He has served as a Member, SCC ISO-IEC JTC 1/SC-41 – Internet of Things and related technologies, ISO – International Organization for Standardization, and as a member of the NIST SP 500-325 Fog Computing Conceptual Model, National Institute of Standards and Technology. He served on the Board of Governors of the University of Ontario Institute of Technology (UOIT) [now Ontario Tech University] and on the Board of Advisers of five different Colleges in Ontario – Centennial College, Humber College, George Brown College, Durham College, Ryerson Polytechnic University [now Toronto Metropolitan University]. For 16 years he served on the Board of the Society of Motion Picture and Television Engineers (SMPTE), Toronto Section.
He holds three master’s degrees – in business (MBA), communication (MA), and education (MEd). As well, he has three undergraduate diplomas and seven major certifications in business, computer programming, internetworking, project management, media, photography, and communication technology. He has completed over 80 next generation MOOC (Massive Open Online Courses) [aka Micro Learning] continuous education programs in a wide variety of topics, including: Economics, Python Programming, Internet of Things, Cloud, Artificial Intelligence and Cognitive systems, Blockchain, Agile, Power BI, Big Data, Design Thinking, Security, Indigenous Canada awareness, and more.
Martin in a volunteer, a photographer, a learner, a technologist, a philosophizer, and a romantic optimist.