For the past few years, AI has been the product.Companies led with it. Investors looked for it. Customers asked whether it was included.But technology categories rarely stay at the centre of the conversation forever.Few businesses today choose software because it uses cloud infrastructure. Few consumers select applications because they run on the internet. Once a technology becomes useful enough, attention shifts from the technology itself to what it enables.AI appears to be approaching the same moment.Consider how businesses actually buy technology. A hospital rarely goes looking for artificial intelligence. It looks for faster diagnosis, better patient outcomes, and more efficient clinical workflows. A bank looks for stronger fraud detection and risk assessment. A manufacturer looks for lower downtime and better production planning.The purchasing decision is rarely about AI.It is about solving a problem.This distinction matters because it changes where competitive advantage comes from. Access to AI models is becoming increasingly commoditised. Thousands of companies can build on the same foundation models. What they cannot easily replicate is industry expertise.The company that understands insurance claims has an advantage over the company that simply understands AI. The company that understands legal workflows has an advantage over the company that only understands language models. Domain knowledge is becoming just as important as technical capability.That reality is becoming increasingly visible across platforms such as the ET Most Innovative AI Product Awards 2026. The diversity of categories from healthcare and BFSI to cybersecurity, legal technology, tax ecosystems, and manufacturing, reflects a market where value is being created through industry expertise rather than generic AI capability.The next generation of successful AI products may not be the ones with the most sophisticated models. They may be the ones whose users barely notice the AI at all.