The martech industry has been telling marketing leaders the same story for a decade: buy our platform for all your needs.
Adobe said it. Salesforce said it. HubSpot said it. Each acquired, built, and bolted on capabilities in a race to become the one platform to rule them all.
Not one of them has delivered end-to-end marketing effectiveness. Not one even fully comprehends the complexity of marketing's stretch from billboards to TV ads to email nurture.
And every CMO running a complex enterprise stack has scars to prove it. We're left to stitch together disparate data in spreadsheets, taking credibility hits along the way because we can't justify our spend in anything close to real-time.
As a result, our budgets are under constant pressure. But, tempting as it may be to want to solve these failed integrations through more industry consolidation both enabled and forced by AI, doing so would be a mistake.
There's a better way.
The State of Martech
It's important to understand just how bad things have become.
Gartner's Marketing Technology Survey found that martech use has fallen to just 33%, meaning two-thirds of the capability companies are paying for goes unused.
Meanwhile, martech's share of marketing budgets hit its lowest level in a decade in 2024, and the Gartner 2025 CMO Spend survey shows that marketing budgets have flatlined at 7.7% of company revenue, down from 11% in the pre-pandemic era.
Some 59% of CMOs say they lack sufficient budget to execute their strategy. CMOs are spending less on technology they were already dramatically underusing.
This is not just an AI disruption story. It's a product-market fit crisis—and the market is starting to agree.
Adobe, Salesforce, and ServiceNow shares are all down 30–40% year-to-date. HubSpot shed more than half its value in 2025. In February, a single AI product launch triggered what traders called the SaaSpocalypse, erasing roughly $285 billion in software market capitalization within 48 hours. And Adobe's long-tenured CEO stepped down in March 2026 amid what Bloomberg described as deep skepticism about the company's AI-era viability.
These aren't isolated events. They're the market's verdict on a structural vulnerability the industry has been papering over for years that AI is now making painfully apparent.
The Empire-Building Trap
The playbook was always the same: acquire your way to owning the whole marketing waterfront. Adobe bought Marketo, Workfront, and tried to buy Figma. Salesforce absorbed Tableau, Slack, and MuleSoft. Each told Wall Street the same story: we will become the platform.
But trying to own everything isn't the same as making everything work together. Sure, every one of these platforms integrates with other tools. Integration, however, is not the same as interoperability that delivers shared metrics and accountability for outcomes.
Your creative suite can tell you what content was produced. Your CRM can tell you which leads were touched. Your media platform can tell you what was spent. Your analytics tool can tell you how results correlate.
But none of these tools can tell you whether your marketing truly produced the return—because none of them owns the end-to-end view, and most have their own novel metrics.
Why Agentic AI Isn't the Fix—Yet
The current conversation treats AI as both the cause of martech's decline and its salvation. The reality is that it's neither.
Yes, agentic AI is creating legitimate pressure on per-seat SaaS pricing. If ten AI agents do the work of a hundred employees, a company needs ten software seats instead of a hundred. That's just math.
But deploying AI across a fragmented, unreconciled marketing stack is like diving into an empty pool. AI requires clean, reconciled data flowing across systems to function. It requires contextual understanding that is domain-specific, vertical-specific, and brand-specific.
Marketing is so complex that the measurement industry has sustained a decades-old "you can't get fired for buying it" positioning for providers who don't even have to reveal their methodology. If martech issues were simple enough for an autonomous agent to solve, someone would have solved it with traditional software years ago.
The stages required to implement AI are sequential and non-negotiable.
- Reconcile and normalize your data
- Build agents trained on specific marketing functions
- Develop vertical expertise
- Develop brand-level intelligence
- Develop cross-brand benchmarking
Every CMO I talk to understands the vision, and those making progress are disciplined about not skipping steps. It's all about information architecture—IA needs to come before AI.
What the Industry Needs: A Collaboration Framework
The path forward isn't more consolidation—it's structured collaboration.
What CMOs need is a model where platforms stick to what they do best, plug into a shared operational and financial backbone, and collectively deliver the full spend-to-performance measurement no individual vendor can achieve alone. This isn't idealism, it's the architecture AI actually requires to function effectively.
And martech companies may now be as willing as only the dying can be.
Three Things Business Leaders Should Do Now
1. Evaluate Platforms on What They Connect, Not What They Own
The vendor that gives you the most complete picture of marketing's financial impact isn't the one with the biggest product portfolio. It's the one that integrates openly and provides the operational layer that validates everyone else's contribution.
This shouldn't require you to change your process to fit the tool, but rather that the tools fit your execution needs.
2. Demand Transparency from Your Measurement Partners
If your MMM or analytics provider can't explain and defend their methodology, you're outsourcing the problem rather than insourcing the tools to solve it.
Bayesian approaches that let data reveal patterns—rather than confirming a preset hypothesis—are available now. Use them.
3. Stop Diving Into the Empty Pool
Sequence your AI adoption. Data reconciliation and workflow automation come first. Domain-trained agents come next. Vertical and brand-level intelligence come after.
The companies racing to deploy AI across unreconciled data aren't innovating, they're just failing faster.
The Real Opportunity
Wall Street's verdict on martech isn't wrong—it's incomplete. Investors are punishing the empire-builders because the empire-building model was never going to deliver what brands need, and now companies have new tools in their toolkits.
But the underlying problem martech exists to solve—giving marketing leaders financial governance, performance visibility, and the ability to prove ROI—hasn't gone away. Flattened budgets and AI-driven complexity have made it more urgent.
The martech companies that thrive in the next era won't be the ones who tried to own everything. They'll be the ones who made fractured systems and processes work together.
More Resources on Martech
The Unicorn Trap: How Marketing Leaders Should Redesign Roles for the AI Era
From Chaos to Control: Orchestrating AI Across Enterprise Marketing
SaaS Is Evolving and AI Is Driving It
Reframing Agency Procurement (Part 2): Procurement's View and A Joint Framework
