We have crossed a threshold in the AI economy where the competitive advantage is no longer about *access to data* — it’s about access to *context.* The "context economy" has arrived, defined by a fundamental shift from selling data products to selling context products as a service.

This is the shift that is ushering in [the age of AI connectivity](https://konghq.com/blog/news/the-age-of-ai-connectivity)the age of AI connectivity. And we've been building the platform to solve it.

Gartner's strategic planning assumption stops you in your tracks: by 2029, 50% of software application providers will be forced to share their context layer externally for third-party orchestrators to stay relevant, versus less than 2% today.

Let that number sink in. Nearly every enterprise software platform you rely on will need to participate in a context economy — one where AI agents from across your organization, and from external orchestrators, need to consume not raw data but *enriched, domain-specific, semantically staged context* through MCP servers.

The problem is that most enterprises aren't remotely ready to participate in this economy, let alone profit from it. They can expose raw APIs. They might even stand up an MCP server or two. But turning context into a governed, monetizable, discoverable product? That requires something most platforms simply don't have.

It requires unified AI connectivity. And that requires Kong.

What makes this Gartner report so striking is that its recommendations — which are published independently and written for a broad enterprise audience — map almost perfectly onto Kong's platform architecture. Not directionally. *Precisely*. Aghi briefly touched on these points in his blog; allow me to expand on them a little further.

Gartner says enterprises need to **"expose MCP servers by enabling publishing to registries in enterprise-managed AI gateways."** That's Kong's AI management, which includes [AI Gateway](https://konghq.com/products/kong-ai-gateway)AI Gateway and [Konnect MCP Registry](https://konghq.com/products/mcp-registry)Konnect MCP Registry. AI Gateway is purpose-built to govern, route, and manage traffic to and from LLMs, MCP servers, and AI agents. The Konnect MCP Registry enables teams to control which agents access which context, and under what conditions.

But here's what most vendors miss: the richest enterprise context doesn't originate in AI systems. It lives in the APIs and event streams that have been running your business for years: transactional records, behavioral signals, real-time operational data, and partner integrations. 

Kong's [API management stack](https://konghq.com/products/kong-gateway)API management stack already governs the API-driven context at massive scale across hundreds of enterprises. Kong's [Event Management stack](https://konghq.com/products/event-gateway)Event Management stack manages the streaming data layer — Kafka, webhooks, event-driven architectures — where real-time context is born and brokered. Together, Kong's three management layers (AI, API, and event) cover the spectrum of enterprise context: synchronous API traffic, asynchronous event streams, and AI-native traffic exposed over protocols such as MCP and agent-to-agent communication. 

Gartner also says enterprises need to **"facilitate easy discoverability and usage... drive a frictionless PLG motion focused toward developers."** That's Kong's Developer Portal, where internal teams and external partners can discover, subscribe to, and begin consuming APIs, LLMs, events, and MCP Servers in a fully self-service motion.

But it’s not just controlling and opening up access to context. Gartner says the shift to the context economy requires **orchestrating context across enterprises** rather than defending it within walled gardens. That's [Kong's Context Mesh](https://konghq.com/blog/product-releases/introducing-kong-context-mesh)Kong's Context Mesh, the new integration and runtime layer that lets enterprises unify the full AI data path across APIs, events, and AI-native protocols like MCP, so context flows where it needs to go without creating new security or governance gaps.

And then there's the piece every other vendor in this space simply cannot address.

Gartner identifies the hybrid monetization model — base fee plus usage-based overages — as the most sophisticated and commercially sustainable approach for MCP and AI gateway providers, as it enables you to align predictable revenue with consumption alignment. It's the model that will let enterprises not just participate in the context economy but *build a business within it*.

But a monetization model is just a theory without the infrastructure to execute it. You need to meter context consumption at a granular level. And you need to bill for it, whether that's internal chargebacks, partner revenue sharing, or direct customer billing. You need to track it, govern it, and report on it across the entire context lifecycle.

That's exactly what [Kong Konnect Metering & Billing](https://konghq.com/products/kong-konnect/features/usage-based-metering-and-billing)Kong Konnect Metering & Billing delivers. It closes the loop that every other platform in this space leaves open. Competitors can point to a gateway. Some can point to a portal. A handful are starting to tell a credible MCP story. Nobody else has the metering and billing layer that transforms context delivery into a revenue stream.

And nobody has it all in one, unified place.

This is what makes Kong categorically different: we don't just help enterprises operate in the context economy. We give them everything they need to [*profit from it*](https://konghq.com/solutions/ai-monetization)*profit from it*.

Gartner issues a clear warning to enterprises that try to protect their context by staying closed: providers that "lock and defend their rich context" will be "open to disintermediation at the context layer by other players that orchestrate context across enterprises outside of their walled gardens."

But the opposite risk is just as real. Enterprises that open up their context without proper governance, security, and monetization infrastructure are exposed in a completely different way — cost overruns, compliance failures, ungoverned AI agent behavior, and revenue leakage.

Kong resolves both sides of this dilemma simultaneously. The Gateway layer provides the governance and security that enterprises require before they can safely open their context externally. Context Mesh provides the orchestration architecture that prevents fragmentation and lock-in. The Developer Portal provides the discoverability that makes context assets commercially viable. And Konnect Metering & Billing ensures that every token of context delivered generates measurable, attributable, billable value.

Gartner's report is a signal, not a forecast. The enterprises that will lead in the context economy aren't the ones waiting for the market to mature. They're the ones building the infrastructure today to publish, govern, and monetize context at scale.

Kong is the only platform that addresses all four dimensions of this challenge in a single, integrated architecture: a gateway and management layer that spans API, event, and AI-native protocols; the discovery layer; the orchestration layer; and the monetization layer.

The context economy doesn't need another point solution. It needs a platform. Kong built it.

*Ready to see how Kong's AI connectivity platform maps to your context economy strategy? *[*Talk to our team*](https://konghq.com/contact-sales)*Talk to our team** or learn more about *[*Kong AI Gateway*](https://konghq.com/products/kong-ai-gateway)*Kong AI Gateway** and *[*Konnect Metering & Billing*](https://konghq.com/products/kong-konnect/features/usage-based-metering-and-billing)*Konnect Metering & Billing**.*

**(1) All Gartner quotes sourced from "Emerging Tech: AI Vendor Race: MCP Servers Will Fuel the Next AI Revenue Surge — “Context as a Service,”' Gartner Research, 19 February 2026. Gartner clients can access the report **[**here**](https://www.gartner.com/document-reader/document/7468226?ref=solrAll&refval=535762898&)**here****.**