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Neither marketing nor IT should own every AI platform decision alone. Marketing should define the customer, brand, and growth outcomes a platform must deliver; IT and data, security, and risk leaders should assess whether it can be integrated, operated, and governed safely. The final decision should follow an explicit approval process that names who evaluates, approves, operates, and can pause the system.
A 2026 Acquia-commissioned survey found a sharp difference in how marketing and technology executives described CMS and digital experience platform (DXP) decision rights. It is evidence of differing perceptions across respondent groups—not proof that matched CMO-CIO pairs at the same companies disagreed.
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What “AI platform” means changes who should decide
The phrase can refer to several different purchases: enterprise AI infrastructure, marketing-specific AI tools, a CMS or DXP with AI features, data and governance systems, or agent orchestration. The best-supported ownership evidence here concerns CMS/DXP decisions and their AI governance implications. It should not be treated as a universal finding about every AI purchase.
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For any platform, separate the choice into distinct responsibilities: setting the business outcome, defining requirements, evaluating technical fit, approving risk, controlling budget, and operating the system. One executive may hold more than one responsibility, but assigning all of them by job title alone can leave important work unowned.
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What the 2026 survey says about CMS and DXP ownership
Acquia announced research commissioned by Acquia, conducted by Coleman Parkes Research and analyzed by VCCP. The survey covered 500 executives—250 CIO/CTO respondents and 250 CMO respondents—in the United States, United Kingdom, and France, with fieldwork in July and August 2026. The groups were surveyed separately; the announcement does not report matched CMO-CIO pairs within companies. Acquia’s September 14, 2026 announcement therefore measures reported perceptions, not a company-by-company audit.
| Respondent group | Reported view of CMS/DXP decision rights |
|---|---|
| CMOs | 25% said marketing owns the decision; 24% named IT; 18% named the head of digital. |
| CIOs and CTOs | 57% said they were the decision maker, and 66% said they were the key evaluator. In their account, CMOs represented 33% of decision makers and marketing directors 42% of key evaluators. |
These figures show why a platform project can feel jointly owned while authority remains unclear. The CMO responses distribute ownership across marketing, IT, and digital leadership; the CIO/CTO responses more often identify technology leaders as decision makers or evaluators. The percentages answer different questions and come from separate respondent groups, so they should not be read as directly matched or added together.
Platform choice, AI investment, and governance are different decisions
Owning a CMS/DXP procurement decision is not the same as deciding where a business invests in AI, and neither automatically settles who oversees AI use after deployment.
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Governance needs its own named authority. In Acquia’s survey, 66% of CMOs said demonstrating control of AI-generated marketing had become a brand-reputation issue, but 41% were confident their own team could embed governance into AI initiatives. That gap makes governance more than an IT sign-off or a marketing promise: someone must define the controls, verify they work, and be empowered to stop use when conditions change.
Why ownership matters before a platform is selected
Content and data need accountable owners
Acquia’s survey found 61% of CMOs said content was spread across so many systems that there was no single reliable source of truth; 40% said their current stack was ready for AI agents. Among CIOs and CTOs, 70% called data sovereignty essential, 56% said they would not deploy AI capabilities until content structure and data integrity were solid, and 51% identified migration complexity as a significant barrier. These reported concerns point to concrete decision gates: identify trusted content, establish permissions and residency requirements, and determine who is responsible for migration and data quality.
Adoption can outrun coordination
OneTrust and Sapio Research surveyed 1,200 senior business decision-makers at organizations with at least $100 million in annual revenue across eight markets in June and July 2026. In that sample, 74% reported departmental or scaled AI adoption and 52% said AI was used across multiple functions or embedded in processes, while 5% reported clear coordination and accountability across the AI lifecycle. The survey also found 87% said their organizations encouraged agent use, compared with 47% reporting clear governance, oversight, and controls. These are findings from the OneTrust/Sapio sample, not estimates for all organizations. OneTrust’s 2026 AI-Ready Governance Survey describes its methods and results.
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Technology leaders can be accountable without full control
IBM’s Institute for Business Value, working with Oxford Economics, surveyed 2,000 executives responsible for IT, technology, or AI decisions across 33 geographies and 19 industries from January through April 2026. IBM reported that two-thirds of surveyed CIOs and CTOs were accountable for AI systems they did not fully control; 70% said business teams were deploying technology faster than IT could track, 77% said AI adoption was outpacing governance capabilities, and 11% felt fully ready for expected agent scale. These results describe that executive survey, not every company. IBM’s June 2026 release reports the findings.
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A practical division of responsibility
There is no single job title that should automatically own every platform decision. Instead, assign decision rights by the work and risk involved. The following framework is an evidence-informed recommendation, not an outcome tested by the cited surveys.
| Responsibility | Who should lead | What the decision must cover |
|---|---|---|
| Business outcome | Named marketing or business sponsor | Customer experience, brand, growth, and measurable business goals. |
| Platform requirements and evaluation | Business sponsor with IT and relevant data/security evaluators | Use cases, integrations, architecture, reliability, vendor risk, and evaluation criteria. |
| Content and data stewardship | Named content or data owner, with technical support | Trusted sources, structure, quality, access permissions, and applicable data-location requirements. |
| Risk approval | Designated security, privacy, legal, or AI governance approver, as relevant | Required controls, approval thresholds, monitoring, auditability, and conditions for pausing use. |
| Budget and final decision | Named budget holder and explicitly identified final approver | Who funds the choice, which approvals are mandatory, and how unresolved trade-offs are escalated. |
| Operations | Named platform or service owner | Migration, maintenance, incident handling, monitoring, and ongoing accountability after launch. |
The business sponsor should not be expected to certify architecture or security alone; technical evaluators should not choose a platform without the business owner defining what success means. For high-impact uses, make risk approval a gate rather than an informal consultation.
Write a decision charter before procurement
A short written charter can prevent disagreement from surfacing only after a platform has been selected or an AI feature is already in use. For each high-impact choice, record:
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- Named roles: the business sponsor, technical evaluator, data or content owner, risk approver, budget holder, and operational owner. One person may fill multiple roles, but none should be implicit.
- Decision rights: which people advise, which approvals are required, and who makes the final choice if views differ.
- Approval and pause thresholds: which uses require additional review, who can suspend deployment, and what evidence is needed to resume it.
- Lifecycle checks: how the organization will verify content and data quality, monitor system behavior, and revisit approvals when capabilities, data, or risk change.
- Escalation path: who resolves a deadlock and how the decision and rationale are recorded.
For a CMS or DXP with generative features, for example, marketing can define the content and customer experience goals; IT can evaluate architecture, integration, and operational fit; content and data owners can confirm source quality and permissions; and the designated risk approver can set release conditions. The charter should state who can authorize launch and who can pause the feature—not leave those rights to assumption.
Questions to resolve before choosing a platform
- Are we buying infrastructure, a marketing tool, a CMS/DXP, a governance capability, or an agent platform?
- Who owns the customer or revenue outcome, and how will the team know whether the platform delivers it?
- Who can validate architecture, integration, security, migration effort, data sovereignty, and operational support?
- Which content and data sources are trusted, structured, permissioned, and maintained—and who is accountable for them?
- What AI uses require explicit approval, monitoring, or a pause, and who has authority to enforce those controls?
- Who controls the budget, makes the final decision, and resolves disagreement between business priorities and technical constraints?
Answering these questions together is more useful than asking whether “marketing” or “IT” owns AI in the abstract: authority can be shared, but accountability for each decision needs to be clear.
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