For the past few years, AI has been dominated by big model innovation and headline-grabbing consumer launches. The next phase of AI will be led by enterprise and vertical applications that reshape how industries work at a structural level. This will open the door to a new variety of startups focused on augmenting or replacing the old legacy systems in the enterprise.
This is where the true value lies. AI is moving from experimentation to becoming part of the core infrastructure that modern organisations rely on. Consequently, AI funding, which was concentrated on a small number of companies in 2025, will begin to expand to include more newcomers.
AI: not a bubble, but a market ready for long-term growth
There is no denying that parts of the AI sector are overextended. A significant number of companies are built around narrow point solutions that are merely features and functionalities rather than full businesses. Those are the areas most vulnerable to correction – but that does not mean AI itself is a bubble.
We are entering the next phase of the AI landscape, which is defined by the growth of enterprise and vertical applications, powered by a demand for technologies that replace or enhance legacy enterprise systems and unlock better use of data across organisations. That shift is not temporary. It reflects long-term demand for better workflows and better use of data in industries like healthcare, legal, finance and supply chain. The hype will settle, but the underlying transformation will continue because it is tied to fundamental modernisation, not short-term excitement.
AI-enabled vertical SaaS solutions will continue to demonstrate real ROI through efficiency gains, data improvements and measurable outcomes. That is what will sustain adoption. This period will highlight which companies are solving deep workflow problems and which ones are offering shallow functionality. The latter group is the most exposed. We could also see pressure if funding stays too concentrated among a small set of AI leaders. As capital begins to expand to more companies, it will become clearer who has a strong model and who does not. The companies most at risk are horizontal AI tools that lack depth, smaller generalist SaaS products that will be replaced by AI-first vertical solutions, and early-stage startups that struggle in a market with very low graduation rates from Seed to Series A.
Enterprise AI moves from exploration to integration
Until recently, most AI deployments inside enterprises were experimental – pilots, testbeds, proof-of-concepts. Adoption is moving quickly at the initial exploration level, but the more meaningful change is only beginning as organisations are starting to integrate AI into long-standing workflows and mission-critical systems. This is where the acceleration will occur, because the gains are cumulative. When AI becomes embedded rather than optional, it starts to meaningfully change how companies operate.
Funding patterns reflect this – in 2025, capital was heavily concentrated among a handful of AI leaders, while that capital pool is now widening to include more new companies. However, the bar remains high as early-stage founders face long fundraising cycles and low conversion rates.
Meanwhile, the broader enterprise market is preparing for real deployment as AI becomes central to how systems operate.
Vertical AI will redefine enterprise software
AI will become a foundational part of enterprise software, as vertical AI takes the lead. Some of the most important advances will come from AI systems built specifically for industry contexts: regulated finance, complex healthcare ecosystems, legal workflows, supply chain and defence.
These sectors are burdened by legacy infrastructure and complex data challenges that are overdue for modernisation, and also stand to gain the most from intelligent automation and decision support – and AI is well suited to address those needs.
As these platforms mature, AI will fade into the background and will simply become how modern enterprise software works, just as cloud and mobile did before it. The differentiation will lie not in the model, but in domain expertise and execution. AI will no longer be a standalone topic but the underlying technology that powers the next generation of enterprise applications and enables organisations to operate with far greater intelligence and efficiency.
Capital will favour substance over story
Even if liquidity improves, early-stage AI founders will continue to operate in a selective environment. Early-stage dynamics remain challenging: seed-to-Series A timelines have lengthened to roughly two years, and only around one in five AI-native startups reach Series A within that window.
This means capital will continue flowing toward companies with proven late-stage AI companies rather than broadening access for UK early-stage founders. It’s less about the hype and more about evidence-backed AI companies through traction, robust infrastructure and real deployment.
AI’s ‘quiet period’ has never been louder
The narrative around AI is evolving. The early chapter belonged to technological spectacle, but the next one belongs to the builders modernising the workflows that keep the economy running. This phase is quieter, more technical and far more meaningful. AI is not replacing enterprise software but rather becoming enterprise software – the companies that understand that distinction will define not only the next year, but the next decade of growth.
