By Tobias Ackermann, CEO of Entirely, and Van Diamandakis, Founder and Managing Partner of Evvia GTM Architects.
There’s a gold rush in marketing technology, and it’s easy to mistake the scramble for the main event.
Numerous products have hit the market in recent months, including Adobe Agent Orchestrator and CX Enterprise. Salesforce has Agentforce, now exposing campaign management as tools a marketer can drive straight from Slack. HubSpot has Breeze. ServiceNow has an AI Agent Fabric.
Every major platform in the world is racing to ship agents and other AI solutions, and the pitch is a version of the same promise: our agents will run your marketing for you, and we do it better than all the other agents.
But this isn’t what the race is really about. It’s actually about who owns the stratum upon which the agents are run, and there is still very much a market need for an operating system that can fill this role.
The agent is not the product. The operating system is.
The stakes are specific to marketing, and analysts have put numbers on them. According to Gartner’s 2028 agentic AI prediction, 60% of brands will use agentic AI for one-to-one customer interactions by 2028, marking what it calls the end of channel-based marketing as we know it.
In the same vein, Forrester’s 2026 customer experience predictions warn that, in 2026 alone, a third of companies will damage customer experience and erode brand trust by deploying AI before they’re ready. Autonomy without governance is a trainwreck waiting to happen, and it’s one we’re hoping to avoid.
Anyone who lived through the personalization wars of the last decade knows how this goes.
Every platform began frantically ramping up personalization capabilities within its own walled garden, granting email segmentation, or the web CMS its very own targeting rules.
Ad platforms were granted their audience models, and far more.
Despite this, not one of them owned the whole picture of the customer. So, we wound up with a decade of channel-deep, enterprise-shallow personalization efforts that never added up to the coherent experience everyone was sold.
The agentic era is repeating the pattern, but this time at breakneck pace. As Real Story Group’s analysis of vendor-embedded agents puts it, every major vendor now ships agents, and each one works best inside its own walls. Adobe’s orchestrator elegantly coordinates agents within the Adobe Experience Platform, as long as you’re using the Experience Platform. And Salesforce’s agents are formidable and capable products, assuming you stay inside Salesforce. Connect anything external and you’re funding an integration program, not joining a neutral system. The agents are real, but these impenetrable walls are the problem.
No large enterprise runs one single vendor. That would be impossible, and nobody does it all well enough to meet the needs of the world’s largest orgs.
The 2025 Marketing Technology Landscape from Scott Brinker of Chiefmartec.com counts more than 15,300 marketing tools.
There is a common call for consolidation, but companies keep adding tools because the work keeps outgrowing any single suite. That’s the reality an agentic strategy must survive: a heterogeneous, half-consolidated stack nobody is going to rip out, run by marketing departments that can’t afford to hand their entire operation, and their institutional memory, to one vendor’s agents.
An agent is a worker, but one with no shared context, no governance, and no memory is a liability at enterprise scale. The potential harm that such a liability could be brought about often seems to slip beneath the radar of companies chasing shiny objects like magpies.
If you turn a dozen autonomous agents loose on a stack that was never designed to accommodate them, you get message and content drift. You get entangled, duplicate records are written to the CRM, out-of-policy actions occur, and brand misfires can become costly in every sense of the word.
The failure of the frantic implementation of every agent under the sun is rapidly becoming an orchestration failure. Autonomy without an operating system is a highway to Hell for marketing teams searching for simplicity and efficiency.
And analysts are blunt about where they believe this will land. In its agentic AI project forecast, Gartner estimates that of the thousands of vendors now marketing agentic AI, only around 130 are the real thing, and calls the rest “agent washing,” the rebranding of chatbots and automation as something autonomous.
It expects more than 40% of agentic AI projects to be canceled by the end of 2027, and the reasons it gives aren’t that the models fail. They offer unclear value, runaway costs, and inadequate governance. By 2030, half of all agent failures may trace to governance gaps and broken interoperability between systems. This brings us back around to operating systems.
We can picture quite clearly three agents from three different MarTech tools, each doing its job reasonably well.
A successful chain starting with an email agent’s win-back campaign to dormant accounts leads to an ad agent that sees the same accounts go quiet, and retargets them. The CRM agent watches engagement spike from the efforts of the others, and reclassifies the accounts as in-market and alerts the sales team.
These are all three locally correct decisions and excellent use cases for agents in MarTech. But, they make for one incoherent customer experience.
Now, the sales team is chasing manufactured demand that only came about because the AI was busy talking to itself, not its customers.
The problem is that agents cannot take ownership of the whole picture. That is the failure mode of agents without a system, and the more there are, the worse it becomes.
Strip the category back to what an enterprise needs, and a real operating system for agentic marketing does four things that have become an imperative for agentic work.
It connects the whole stack, the tools you already run, and exposes them as something agents can act on, with no rip-and-replace. This is the layer that walled-garden suites simply cannot be, because their incentive is to make their own walls the destination.
Routine moves execute automatically, and consequential ones route to a named human with a window to approve. High-impact or out-of-policy actions are blocked until someone signs off, and every decision is logged with its reasoning. Autonomy within the bounds you set is the only kind an enterprise can deploy.
The agents that matter are grounded in an organization-specific substrate: how your campaigns map to budgets, how approvals map to markets, how brand rules apply per channel, and what compliance signed off last quarter. That substrate can’t be copied without running the same campaigns inside the same company, which is the point. The 2026 Gartner Hype Cycle for Agentic AI lists context graphs among the foundations needed for agentic AI to work at scale.
Every campaign decision, action, and outcome feeds the next one. The system doesn’t just execute faster, it gets measurably better at your markets, your constraints, and your customers over time. Instead of starting every job from zero, an operating system never starts from zero twice.
"One neutral layer across the whole stack, not agents trapped inside one vendor’s walls."
Underneath all four of these points, for any serious enterprise, and certainly every European one, sits the part agentic tools skip: sovereignty and compliance by design.
There has never been a greater need for data residency you control. Adherence to GDPR and the EU AI Act are handled in the architecture rather than bolted on afterward. A regulated enterprise can’t deploy autonomy it can’t audit, and it can’t audit what it can’t govern.
Gartner now calls the governing layer a “guardian agent,” and its first Market Guide on the subject makes the architectural point that governance has to move into runtime, and controls built inside a single vendor’s platform can only police that platform, never the agents running across the rest of the stack. Enterprise-wide governance needs a layer that can see and govern across vendors, not just within one. According to Gartner’s guardian agent prediction, 40% of CIOs will demand such capabilities by 2028.
The winners of the agentic era won’t be the teams with the most agents. They’ll be the ones whose agents run on a system that owns the whole picture, governs every move, and compounds.
Every suite vendor will tell you its orchestrator is open. But when you read into the architecture, it becomes clear that external agents connect to the vendor’s hub, and the data, the memory, and the governance accrue to the platform you’re already standing on.
That isn’t a knock on the engineering, which is genuinely excellent. It’s a statement about incentives. A vendor whose business is selling you more of its own stack has little reason to make it easy to govern agents that live outside it.
The open protocols make this even harder to ignore. Standards like MCP and Agent-to-Agent now let any agent, in principle, talk to any tool.
The plumbing for cross-tool orchestration exists. What the suites won’t do is build on it as equals, because the moment governance runs across the whole stack, the suite becomes just one more tool being governed, not the one doing the governing. They adopt the protocols and still position themselves as the hub.
The personalization wars proved the channel can’t own the global picture. The agentic era will prove the same about the suite. The gap is a layer built to govern agents across the whole stack, not just inside one vendor’s walls, and that’s a much harder position for an all-in-one suite to occupy credibly than for a system built for exactly that job from day one.
This is the layer we built Entirely OS to be, and we built it around those four jobs rather than around a suite that needed agents bolted on. We call it the world’s first operating system for agentic marketing, and the claim rests on a specific, defensible definition.
Entirely OS is by far not the first product to ship marketing agents; countless have done and continue to do so. But it is the first governed, sovereign layer, a guardian layer for marketing, designed to run agents across the entire stack instead of inside one vendor’s walls.
It owns the global picture. Entirely OS connects to the systems a marketing team already runs and exposes them as something agents can act on, with no integration project and no demand that the tools change. When a new system is added, the platform discovers what it does, what data it holds, and what it supports, and then registers it so agents can query and act on it. Adding to the stack is a configuration task, not an engineering project.
Entirely OS connects, scales, and orchestrates your existing MarTech applications into your own open ecosystem, securely and compliantly, without rip-and-replace.
We've learned that trust in production isn't earned through feature lists. It's earned through partnerships built around outcomes: your business outcomes, your compliance requirements, and your data staying in your boundaries.
It governs every action. Routine operations execute automatically. Consequential ones notify a named approver with a window to review. High-impact or out-of-policy actions are blocked until someone explicitly approves them, and every decision is logged with its reasoning and its outcome.
Governed execution: routine runs, consequential notifications,
high-impact actions are blocked until a human signs off. Every decision is logged.
It runs on your own intelligence. At the core is Entirely Intelligence, an organization-specific knowledge graph built from your own systems: how your campaigns map to budgets, how approval chains map to markets, how brand rules apply per channel, and what compliance signed off last quarter.
The agents work from that, not from generic training data, and everything learned in a campaign goes back into Entirely Intelligence. That advantage can’t be replicated without running the same campaigns inside the same organization, which is exactly why it compounds.
It doesn’t force one level of autonomy on every task. You choose.
It can be an assistant that surfaces answers and reasoning. Or, an executor that takes a defined action and returns finished output. It could be an orchestrator that runs a multi-step workflow end-to-end and escalates when a human decision is needed.
Entirely OS’s agents have names and clear remits: Sam, Mika, and Lenn, and they share one semantic model and one governance layer, getting measurably better at your markets over time. All of it runs sovereign on AWS, is built for GDPR and the EU AI Act, and it meets marketers inside Slack, Microsoft Teams, or their AI workspace rather than behind another dashboard.
The honest hard part of agentic marketing is getting from a promising pilot to something running reliably in a real, regulated, multi-vendor environment. The 2026 Gartner CMO Spend Survey found that 70% of marketing leaders say their processes aren’t yet mature enough to scale AI, with a shortage of in-house expertise the biggest barrier they name.
An operating system doesn’t fix that on its own. It’s why our answer is a structured program, the Agentic Marketing Lab, that connects the full stack, finds the highest-value use cases, and deploys in the live environment until the team is genuinely in control. That’s the line between a pilot that impresses and a system that runs.
A marketing function that compounds is a different kind of asset than a marketing team that merely “works hard”. Most of what a team learns from a given campaign is lost the moment that campaign reaches its end: the context or judgment, the hard-won read on what worked in which market – all of it scattered across people’s heads, and buried in tools and dashboards that don’t talk to each other.
An operating system that retains that information turns it into an appreciating asset instead. The hundredth campaign starts where the ninety-ninth finished. That’s the quiet, enormous advantage on offer, and it only accrues to the organizations that build the layer needed to capture it – a layer that was until now absent.
The agent gold rush will sort itself out the way these things always do. The demos will slow, the category language will settle, and what’s left standing will be whoever built the system running underneath their army of agents – a system governed, grounded in its own intelligence, and compounding with every campaign.
The agent is not the product. The operating system is.
The question for any marketing leader watching this race isn’t which agents to fund next. They must focus instead on whether this year’s campaigns make next year’s cheaper and faster to run, or whether the team is just filling a drawer with clever tools and starting from zero every time. One is an advantage that compounds. The other is a cost center with better demos.