Gartner for High Tech’s Post

The Gartner view aligns with what we're seeing in the market, but our experience suggests the biggest opportunity is the next layer of enterprise adoption. Knowledge management, search, conversational AI, and analysis are the clear leaders today. Over the next two years, domain-specific models, small reasoning models, agentic AI, and multimodal capabilities will move these from isolated use cases to enterprise-wide intelligence. The missing piece is a unified enterprise foundation. Enterprises don't want separate stacks for search, agents, memory, governance, and AI. They want one governed platform that combines enterprise memory, reasoning, digital twins, sovereignty, and data management. That's what enables GenAI to scale beyond pilots into production. The future isn't just better models but enterprise intelligence built on a unified Data + AI platform.

This is a classic non practitioner view of enterprise AI. Classify technologies, colour a heat map and call it a scaling roadmap.😉 Take banking. Building an AI agent for loan processing is easy. Giving it secure access to core systems, satisfying regulators, ensuring accountability and delivering measurable ROI is where most programmes stall. This heat map shows where AI could be used, not where it is creating enterprise value. The real bottlenecks are data, governance, workflow redesign and change management, not model capability. That is the difference between analysing AI adoption and actually implementing AI at enterprise scale.

The real scaling challenge may not be choosing the next model—but governing a portfolio of them. When models disagree or one becomes a critical dependency, who owns the decision? 💎 Scale without model-portfolio governability may simply industrialise fragmentation.

Gen AI use cases in the retail space is about to take off. In recent months, I’ve found so many founders doing interesting work in this space, bringing use cases to retail giants in regional markets - especially in Asia. Startups there will capture attention and earn the opportunity to work with global retail giants once they prove their concepts (and value). Interesting times ahead.

The future of GenAI belongs to those who innovate and integrate

The next phase of GenAI adoption will likely be defined less by access to foundation models and more by an organization's ability to operationalize AI across complex business processes while maintaining governance and trust.

The next stage of GenAI will be driven by models that are smaller, more specialised and easier to integrate into real workflows. Domain knowledge, strong data governance and clear business use cases will matter more than model size alone. Companies that build these capabilities early will be better placed to improve efficiency and scale innovation.