Marketing organizations are racing to adopt AI while simultaneously trying to contain it. About 76.6% of marketers now have AI policies in place, up from 55.3% just a year earlier, per the Association of National Advertisers’ January 2026 survey (registration required). Investment is also surging. Nearly 89% plan to increase AI spending, and two-thirds would maintain that investment even during an economic downturn.
Yet beneath this appearance of control, a different pattern emerges. More than half of marketers report feeling overwhelmed by the pace of AI change. Organizations are governing AI adoption without first planning for it — building guardrails around a road that has not been mapped.
Governance theater: Policies without planning
The ANA data reveals a critical gap between governance activity and strategic execution. While 76.6% have established AI policies and 52.7% have formed cross-functional steering committees, the actual planning infrastructure remains hollow. Nearly half of organizations (46.2%) lack formal AI planning horizons. Even more damaging: 71.6% haven’t established ROI targets for their AI investments.
This ends up being governance theater — the appearance of control without the substance of strategy. Consider what effective governance requires in any other domain of marketing technology. When organizations implement customer data platforms or marketing automation systems, they should start with planning:
- What business outcomes do we need?
- What processes must change?
- How will we measure success?
Governance follows planning, not the other way around. But with AI, the sequence seems to have been reversed. Concerned by headlines about compliance risks and data privacy (which 95.5% of respondents cite as a worry), organizations may have rushed to create policies before developing strategies. The result is a collection of restrictions without direction and boundaries without destinations.
Only 1.1% of organizations surveyed achieve both high measurement sophistication and high ROI expectations. That’s a systems failure. Organizations are deploying AI tools, establishing usage policies and forming oversight committees — all while still lacking the fundamental capability to connect investment to outcomes.
Dig deeper: Marketing gains from AI begin with governance
The investment-value disconnect
Marketing organizations are pouring resources into AI with remarkable conviction. That 88.6% planning to increase spending represents a 32-percentage-point jump from the previous year’s 56%. More striking: 66.7% would maintain AI investment even if economic conditions deteriorated. Where does this confidence come from? Apparently not from demonstrated strategic value.
When asked about the primary value AI delivers, 60.9% of marketers point to time efficiency. Their near-term expectations cluster around tactical execution: content creation (21.4%), workflow efficiency (18.5%) and personalization (13.3%). These are operational improvements, but not competitive advantages. They make existing processes faster without making organizations more strategic.
This pattern should feel familiar to anyone who’s tracked martech adoption over the past decade. Organizations accumulate tools, pursue efficiencies and wonder why utilization rates stagnate at 42% while disappointment grows to 54.9%. The cycle repeats because the underlying problem (such as strategy before tools, planning before policies) remains unaddressed.
AI adoption may be following the same trajectory, just faster. Companies are investing in capabilities they haven’t defined business cases for, prioritizing tactical speed over strategic impact. The governance policies they’ve established don’t fix this.
Dig deeper: The AI oversight gap is marketing’s next governance test
What strategic governors are getting wrong
The ANA research identifies four behavioral segments within marketing organizations, categorized by experience level. The largest group — 61.4% of the workforce — are strategic governors, marketers with 12+ years of experience who, in theory, should be guiding AI adoption with wisdom earned from previous technology cycles.
They exhibit the highest confidence in their organization’s AI journey (45.9%). They also report being the most overwhelmed (31.4%), which is a symptom. Strategic governors spent the past decade watching martech stacks balloon from dozens to hundreds of tools. They’ve seen utilization rates decline as capability increased. They’ve participated in countless platform evaluations, vendor selection processes and integration projects. Their experience tells them that more technology without better processes creates complexity, not value.
Yet here they are, seemingly confident about AI adoption while simultaneously drowning in its pace. And that’s because confidence without strategic planning is just hope dressed in professional language. The perception gap between leadership and practitioners can also amplify this problem. When the ANA compared responses from its Growth and Governance Council (senior leadership) with those of the broader workforce, the difference was stark. Leadership shows 51.7% optimism. Practitioners report 29.3% anxiety.
This scenario shows the failure of organizational translation. Executives see AI as a strategic opportunity. Practitioners experience AI as an operational burden. Without shared planning frameworks that connect leadership vision to practitioner execution, these groups are perpetually working toward different goals.
Strategic governors should be the bridge. Instead, they’re standing in the middle of that gap, confident in their understanding of both sides while overwhelmed by the impossibility of connecting them without a clear strategic plan to build on.
Dig deeper: Smarter AI means bigger risks — Why guardrails matter more than ever
Building strategy before scaling spending
The path forward isn’t mysterious. Organizations need to reverse the sequence: planning before governance, strategy before scale.
Start with planning horizons
Before expanding AI tool adoption, establish what success looks like in a given timeframe. Not at the tool level, but at the business outcome level. Which customer experiences should improve? What operational costs should decline? How should team capabilities evolve? Planning horizons force organizations to think systematically about AI integration rather than tactically about tool deployment.
Establish ROI targets next
Before the next budget cycle, before the next vendor evaluation, before forming another cross-functional steering committee. If 71.6% of organizations can’t articulate what return they expect from AI investment, they’re not investing strategically — they’re speculating. ROI targets don’t have to be perfect. They need to exist.
Build cross-functional planning, not just cross-functional governance
Those 52.7% who formed steering committees took an important step. But committees that govern without planning become review boards that slow adoption without improving outcomes. Strategic planning requires collaboration before implementation, not oversight after deployment.
Develop measurement sophistication before scaling investment
The 1.1% who achieve both high measurement capabilities and high ROI expectations didn’t get there by accident. They built frameworks to track how AI improves specific workflows, changes customer outcomes and generates business value. Measurement sophistication isn’t a luxury for the mature. It’s the foundation for anyone serious about strategic AI adoption.
This is a systems architecture problem. Governance, planning and measurement together drive value. Governance alone creates the appearance of control without delivering results.
Dig deeper: Guardrails and governance: How to protect your brand while using AI
Strategic blueprints for AI infrastructure
Marketing organizations are building AI infrastructure without strategic blueprints. They’re establishing policies to govern tools they haven’t defined use cases for, protecting data for initiatives they haven’t planned and forming committees to oversee investments they can’t measure.
Again, the appearance of control masks the absence of strategy. As agentic AI adoption accelerates (37.4% of organizations plan implementation in the next six months), this gap will widen. Agents amplify strategy when it exists and amplify chaos when it doesn’t. Organizations that skip from governance policies to agent deployment without strategic planning in between won’t just fail to realize value. They’ll encode their lack of strategy into automated systems that execute bad processes really, really efficiently.
The question isn’t whether to invest in AI. The data shows that ship has sailed. The better question is whether to invest strategically or speculatively, with planning or with hope, building systems or accumulating tools.
Treat AI planning as the prerequisite to AI governance, not the outcome. Because policies can’t save you from a strategy you never developed.
Dig deeper: Most AI agents fail without data and governance maturity
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Contributing authors are invited to create content for MarTech and are chosen for their expertise and contribution to the martech community. Our contributors work under the oversight of the editorial staff and contributions are checked for quality and relevance to our readers. MarTech is owned by Semrush. Contributor was not asked to make any direct or indirect mentions of Semrush. The opinions they express are their own.
