Gartner AI-native trend reshapes monday.com buy-versus-build debate

The new baseline for software is faster build, not just faster buy

Gartner’s October 20, 2025 trend call in Orlando matters far beyond analyst slide decks because it changes what buyers think is possible. Its AI-native development platforms use AI models to create software faster than was previously possible, which can lift productivity, unlock new products and, in some cases, replace off-the-shelf SaaS with custom-built alternatives. Gartner places that shift inside its 2026 “Architect” theme, alongside AI supercomputing and confidential computing, a signal that the next round of digital transformation will be judged on secure, scalable foundations as much as on speed.

For monday.com, that is the strategic pressure point. The company has spent years arguing that teams can move from idea to workflow without a giant engineering organization. Gartner’s framing makes that promise more urgent, because more customers are now willing to ask whether they should build something themselves if AI can compress both time and cost.

Why monday.com is in the middle of the build-versus-buy fight

The numbers show that monday.com is not dealing with an abstract trend. In the fourth quarter of 2025, revenue reached $333.9 million, up 25% year over year, and full-year 2025 revenue grew 27%. Customers with more than $50,000 in ARR represented 41% of total ARR, a sign that the company is already selling deep into serious business use cases, not just lightweight departmental adoption.

Momentum carried into 2026. First-quarter revenue reached $351.3 million, up 24% year over year, and the company reported record net adds of customers with more than $500,000 in ARR. monday.com has also said it serves more than 250,000 customers worldwide. That scale is the opportunity and the warning: the more work customers run through the platform, the more they will compare monday.com with the idea of building a custom internal system instead of extending a subscription.

The strongest proof that the market is moving in Gartner’s direction is monday vibe. monday.com said it was the fastest product in its history to surpass $1 million in ARR, and that more than 60,000 apps were built on monday vibe in about three months. That is not just adoption, it is evidence that customers want low-friction software creation inside the platform itself.

What can no longer be bolted on

For product teams, the lesson is not that every capability must be rebuilt from scratch. It is that some capabilities have become too important to treat as add-ons. Connectors, permissions, syncing data across systems, governance, reliability and the ability for agents to run work are now part of the core buying decision, not secondary features.

That is why monday.com’s AI updates matter as product strategy, not just feature news. The company has introduced AI Blocks, AI agent connections, a monday AI Agent builder and a new AI experience centered on monday Sidekick. Those pieces point to a platform that is trying to do more than generate text or summarize tasks. It is trying to become a place where AI can trigger, route and complete operational work inside real business systems.

The March 2026 launch of Agentalent.ai pushes that logic further. As a managed marketplace for enterprises to discover, evaluate and hire AI agents for defined business roles, it suggests monday.com sees a future in which buyers do not just assemble automation steps. They procure, govern and deploy agents the same way they now buy software modules. In Gartner terms, that is the Architect theme turning into a product roadmap.

What this means for engineers and product managers

For engineers, the build-versus-buy shift raises the bar on platform architecture. If customers believe they can build internally, monday.com has to make its own system easier to extend, safer to control and more useful out of the box. Flexibility becomes a retention feature, because the platform must stay attractive even when a customer’s technical team thinks custom code is possible.

For product managers, the pressure is more specific. Each new AI feature has to answer a hard question: does it reduce the time from intent to operational workflow enough to beat a bespoke alternative? That means prioritizing workflows where setup time, data syncing, permissions and cross-tool orchestration are the real product, not the AI wrapper around them. It also means designing for enterprise buyers who want proof that agents can operate inside policy, not just generate a draft.

The practical rule is simple: if a feature helps a customer do work faster but cannot survive in a governed environment, it will not carry the product far enough. monday.com’s next phase has to make AI feel operational, not experimental.

How sales teams should talk about value now

The sales story also changes under Gartner’s lens. Buyers who are newly open to custom-built alternatives will not be impressed by vague claims of innovation. They will want a tighter ROI case: faster deployment, lower maintenance burden, stronger integration depth and fewer people required to keep workflows alive.

That is where monday.com’s positioning as an AI work platform becomes important. The company is no longer selling only work management. It is selling a way for nontechnical teams to build and run workflows, then layer AI agents into those workflows without starting from zero. That distinction matters in enterprise deals, especially when buyers already know what it looks like to wire together their own stack.

The most persuasive message is not that monday.com is bigger or trendier than competitors. It is that its platform can absorb the very reasons a customer might otherwise build in-house. If monday.com can keep accelerating app creation, protect governance and deepen integrations while AI makes internal development easier everywhere else, it can stay ahead of the buy-versus-build argument. If it cannot, customers will use the same AI-native tools Gartner highlighted to question every SaaS renewal on their calendar.