![\"Legacy](\"https:\/\/static.toiimg.com\/thumb\/msid-130881804,imgsize-33684,width-400,height-225,resizemode-4\/mahesh-kumar-goyal.jpg\" "\\"Google")
<\/div>\n<\/div>\n<\/div>\nUrging tech leaders to rethink how they approach artificial intelligence, Mahesh Kumar Goyal, Senior Data and AI Expert at Google LLC, said that legacy systems which are often dismissed as outdated are in fact the most valuable foundation for building successful AI solutions. Addressing industry experts during a recent virtual interaction, Goyal cautioned against the sector\u2019s growing obsession with \u201cgreenfield innovation\u201d while ignoring decades of accumulated business knowledge.Referring to his recent participation at Google Cloud Next 2026, Goyal said the conversation around \u201cAgentic AI\u201d is accelerating globally, but many organisations are heading in the wrong direction. \u201cWe are often tempted to build the future from scratch,\u201d he told the audience, \u201cbut the real future lies buried in systems companies already have. If you ignore them, your AI will lack context and fail in the real world.\u201dGoyal explained that most enterprises separate their AI initiatives from modernization efforts, a mistake he described as an \u201carchitectural lie.\u201d \u201cYour modernisation strategy and your AI strategy are the same strategy,\u201d he said. \u201cIf you treat them as different, you will build impressive demos, not impactful systems.\u201dSharing insights from his own experience, Goyal recounted a large-scale cloud migration project where a modern system failed during an AI pilot. The reason, he said, was simple: critical business logic embedded in older systems had been lost. \u201cLegacy systems aren\u2019t technical debt,\u201d he emphasized. \u201cThey are encoded institutional memory. You can rewrite the code, but you can\u2019t rewrite the knowledge.\u201dHe advised organisations to develop frameworks that bridge old and new technologies rather than treating them as opposites. According to him, emerging approaches such as Model Context Protocol (MCP) and GraphRAG are enabling engineers to connect AI models with historical systems, unlocking insights that would otherwise remain hidden. \u201cThink of MCP as a peace treaty,\u201d he said. \u201cIt allows modern AI agents to talk to legacy systems without destroying them.\u201dAt the same time, Goyal warned about the risks of poorly integrated AI systems. While basic chatbots may cause minor issues, he noted that AI agents operating on incomplete or poorly understood legacy data can lead to serious financial consequences. He cited an instance where graph-based analysis revealed unknown systems handling large vendor transactions, the systems that senior leadership was unaware of.For industry leaders, Goyal\u2019s message was clear: technical skill alone is not enough. \u201cThe real challenge is not technology, it is architectural courage,\u201d he said. \u201cYou must be willing to question how systems are designed and where knowledge actually resides.\u201dConcluding his address, he offered a practical test for executives steering these organisations: \u201cTake the top three AI projects and the top three modernisation projects in your company. Put them on the same slide. If you can\u2019t connect them, you don\u2019t have a strategy.\u201dAs companies worldwide race to adopt AI, Goyal stressed that those who succeed will not necessarily have the most advanced models, but those who learn to extract intelligence from the systems they already possess.<\/div>\n