Regardless of discuss of an ‘AI bubble’ occurring on the sidelines, enterprises are heading into 2026 with extra funding earmarked for AI. In response to Boston Consulting Group’s annual AI Radar, firms anticipate to double their AI spending this 12 months, from 0.8% to about 1.7% of revenues.
Who stands to profit? It wouldn’t be sensible to put in writing off the possibilities of startups commanding a good portion of this enterprise spending. Autonomous workflows are shifting from idea to actuality. In observe, this implies enterprises shifting away from “AI options” in direction of AI staff dealing with total processes. AI-native startups, launched and scaling at tempo in a post-LLM world, can acquire an edge over incumbents providing legacy options that may’t sustain.
Tipping autonomous workflows for take-off
There’s little question that agentic AI is the place the enterprise AI puck is shifting subsequent. We must be clear about what meaning. Removed from AI brokers as glorified LLM chatbots with extra autonomy, agentic AI can deal with total business-critical processes, from KYC (know-your-customer) to FP&A (Monetary Planning & Evaluation) and compliance remediation, by way of autonomous workflows.
Underneath the hood of those workflows are the layers of an rising agentic AI software program stack: self-correcting workflows (permitting AI to repair its personal errors and preserve autonomous processes), safe reminiscence (a complicated mechanism enabling AI brokers to enhance workflows utilizing retained context) and multi-agent collaboration (the framework for AI employee collaboration that underpins refined autonomous workflows).
Intuitively, enterprise software program incumbents needs to be main the best way within the pivot in direction of autonomous workflows. Many, nevertheless, are nonetheless caught within the mindset of transport “AI options”. Low churn breeds gradual innovation, and incumbents battle to retrofit legacy options from a pre-LLM world for the agentic future.
AI-native startups, alternatively, are constructing these programs from scratch. They’re embedding automation into their merchandise from day one. Agentic considering shapes their firm construction, tradition, and tempo of execution. They’re subsequently primed to ship autonomous workflows first.
The startups behind the momentum
In 2026, we’ll see much more AI-native startups launch merchandise centred round autonomous workflows. There are some recurring themes once we take a look at the backgrounds of the European founders behind these corporations.
Firstly, it’s more and more frequent to see industry-expert entrepreneurs behind AI-native startups, pioneering options to the issues they encountered first-hand of their careers. Be it legacy ERP software program or cumbersome information practices, these founders typically have a really particular, typically vertical-specific, course of in thoughts that agentic AI could make much more high-performing, and they’re constructing in direction of this imaginative and prescient.
Moreover, there’s a rising cohort of savvy entrepreneurs launching new AI corporations designed to disrupt a selected income stream or service they’ve recognized as ripe for disruption by way of agentic AI.
We’re additionally seeing extra founders elevate capital in sectors that enterprise capital used to keep away from. Startups in sectors reminiscent of defence, power and procurement are benefitting as extra buyers come to phrases with conventional sticking factors in these sectors, reminiscent of lengthy gross sales cycles and regulatory constraints, and look past the standard areas of startup disruption the place competitors is fierce. By automating compliance, defence procurement, power administration and development workflows, AI-native corporations in these sectors are benefitting from this shift in VC behaviour.
Regardless of the founder’s strategy, these startups are discovering frequent methods to problem essential moats that incumbent gamers have lengthy used to take care of their dominant market positions. The primary is buyer onboarding. AI-native startups are automating onboarding processes to slash timescales round information migration, coaching and configuration from months to days. Lengthy onboarding cycles and subsequent vendor lock-in have gotten much less dependable moats for incumbents.
The second moat is technological benefit. This can be a essential improvement that speaks to a broader pattern shaping enterprise AI and what it means to be a profitable enterprise expertise firm in 2026 and past.
Person expertise as the brand new key differentiator
To place it merely, AI is making software program far simpler to duplicate than ever earlier than. Founders not want deep technical information or in depth assist to create fundamental functions with a immediate. Likewise, enterprise workers can now reimagine their enterprise processes by way of LLM prompting. No familiarity with software program improvement is required.
This presents an enormous danger for incumbent enterprise platforms and a serious alternative for AI-native startups. Incumbents can not get away with providing clunky, unintuitive software program with out experiencing buyer churn, on the premise that it may possibly’t be simply replicated. This implies there’s a brand new battleground defining enterprise software program excellence: person expertise.
In response, AI-native startups can supply sturdy UX by constructing person communities round their options that act as suggestions loops for steady product enchancment. Founders have interaction customers early and contain prospects extra instantly within the design and iteration levels than ever earlier than. This encourages loyalty and retention, and attracts extra customers and buyers. Being AI-native, startups have already got a extra simple path to constructing the intuitive and adaptable workflows that enterprise customers worth.
Coming forward
For Europe’s early-stage founders, 2026 presents a chance to construct corporations which can be first movers in introducing autonomous workflows throughout a variety of {industry} verticals and customary enterprise processes. The startups that lean into their inherent strengths over incumbent competitors and prioritise person expertise can steal a march and experience the subsequent wave of software program disruption.
