Clear Strategy Proprietary Research · Volume 01

The State of
AI in Marketing.

A field study of 100 marketing leaders on how AI is used, coordinated, governed, and funded — and where the operating discipline still has to be built.

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Q Take the 10-min AssessmentBenchmark your team against the 5-stage AI Maturity Curve · Share results with your org
MethodPollfish · n=100
FieldedAug 5, 2026
Questions420 items
Scroll
Methodology at a Glance

100 marketing leaders. 420 questions.
Zero synthetic respondents.

100
Respondents · Marketing decision-makers across industries
420
Questions · Strategy · creative · ops · governance · spend
6
Discipline areas covered across the study
1
Field date · Aug 5, 2026 — a same-day snapshot
The Central Finding

AI is everywhere.
Almost nowhere is it scaled.

67%
Adoption
of organizations are experimenting or using AI across multiple marketing teams
the gap 62-pt maturity chasm
5%
Maturity
have AI that is integrated, governed, measured, and continuously improved
40%
Faster content or campaign production
36%
Improved creative quality
46%
Expertise still held by individuals
48%
Tool choice driven by personal preference
Corroborated by — the adoption-vs-scale gap is industry-wide McKinsey State of AI 2025: 88% of organizations use AI, but only 1% report AI maturity. BCG: only 25% have captured measurable value from AI. Deloitte 2025: 88% used AI in 2025, but only 8% maintain comprehensive governance. The 62-point gap this survey found is not a Clear Strategy outlier — it's the operating pattern across every major enterprise study.
The headline gains are real — but they concentrate in acceleration, not transformation. Only 18% report better decision-making. 16% see improved knowledge sharing. Organizations are capturing surface-level efficiency before turning AI into deeper operating advantage.
Chapter One

Speed without structure.

AI is already producing visible efficiency gains — faster content, better creative, faster reporting. But the operating model needed to scale those gains hasn't caught up.
40%
Faster content or campaign production
5%
Fully integrated, governed, improved AI
46%
Rely on individuals to hold expertise
Chapter 01 · Finding 01

The gains from AI are real — and they land in production, not decisions.

Asked which business impacts they've observed from AI use, marketers point to a consistent pattern: acceleration is winning by a wide margin over transformation. Faster content, better creative, faster reporting — the top four outcomes are all about throughput. Higher-order gains (better decisions, knowledge sharing, coordination) trail by 15–20 points.

Reported AI outcomes · % of respondentsn=100
Corroborated by — acceleration gains without transformation Gartner 2026: AI saves sellers 4.8 hours per week, yet 72% of sales orgs fail to reinvest that time in high-value work. McKinsey QuantumBlack 2025: sales & marketing capture just 28% of AI value — largely from speed, not from structural change. The pattern here — 40% faster production, 18% better decisions — is the same asymmetry playing out at scale.
Faster content or campaign production
40%
Improved creative quality
36%
Faster research
34%
Faster reporting or analysis
28%
Lower production costs
27%
Higher content or campaign volume
27%
Better personalization
25%
Improved marketing performance
21%
Where the Gains Stop

Gains concentrate in acceleration.
Transformation trails by 20 points.

The organizational learning outcomes — the ones that compound — sit well below the production gains. Only 18% report better decisions, 18% see improved productivity, 16% see improved knowledge sharing. AI is a co-pilot, not yet a system.

Column A · What's Working
The acceleration wins
  • 40%Faster content or campaign production
  • 36%Improved creative quality
  • 34%Faster research
  • 28%Faster reporting or analysis
Column B · What Isn't Yet
The transformation gaps
  • 21%Improved marketing performance
  • 18%Better decision-making
  • 18%More consistent processes
  • 16%Improved knowledge sharing
Adoption by Function

AI expanded horizontally — faster than it matured vertically.

Marketing leadership (47%), creative (38%), content (36%), brand (34%), and product marketing (33%) lead adoption. Ops, analytics, and customer-facing functions trail — meaning AI has reached the drafting room faster than the operating layer.

Marketing Leadership
47%
Creative or Design
38%
Content or Copywriting
36%
Brand Strategy
34%
Product Marketing
33%
Executive Leadership
26%
Paid Media
24%
Video / Audio
22%
Marketing Operations
21%
Organic Social
20%
Website / Landing
18%
Consumer Insights
17%
Sales / Rev Ops
17%
Search / SEO / GEO
16%
CX / Success
15%
Tier 1 · Leaders 33%+
Tier 2 · Adopters 26–34%
Tier 3 · Emerging 20–25%
Tier 4 · Pockets 15–19%
Tier 5 · Trailing <15%
Chapter Two

Knowledge stays trapped.

AI-related innovation is happening. Institutionalization is not. Effective prompts, workflows, and assistants are being invented — and quietly lost when the person who built them switches focus.
46%
Expertise still held by individuals
76%
Useful AI knowledge locked with individuals
43%
Sharing happens informally in Slack / email
Where Expertise Lives

Marketing expertise is personal, not institutional.

Where marketing know-how actually sits — in people, or in documented systems? The survey asked. The answer is a fragility problem hiding in plain sight.

Where Expertise Is Held · % of respondentsn=100
Corroborated by — the knowledge-locked-with-individuals pattern MIT Sloan Management Review 2025: the emerging "agentic enterprise" study finds that 76% of AI capabilities remain personal to the individual employee rather than institutional. PwC Responsible AI 2025: only 55% of executives report enterprise-wide AI knowledge sharing — the rest is trapped in silos or with individuals.
Individual employees
46%
Documented strategies & processes
29%
Standard operating procedures
28%
Marketing playbooks
27%
Custom assistants (custom GPTs)
19%
Reusable AI skills / workflow libraries
14%
How AI Knowledge Actually Spreads

From a good idea to institutional asset — 6 in 10 don't make it.

What happens when someone at your company builds an effective prompt, assistant, or workflow? Here's the actual funnel — from Slack chat to a governed, reusable capability.

Stage 1Effective prompt / assistant / workflow developed
43% · Shared informally (Slack)
Widest stage. Discovery is happening.
Stage 2Documented in a shared location
23% · Documented
Written down — but not necessarily reviewed.
Stage 3Reused within the immediate team
20% · Reused (Team)
Local reuse. Still one team, not the org.
Stage 4Becomes a shared assistant or custom GPT
17% · Shared Assistant
Packaged so colleagues can use without asking.
Stage 5Becomes a reusable AI skill
15% · Reusable Skill
Portable across projects & teams.
Stage 6Becomes a template or playbook
11% · Template
Codified. Reproducible without the author.
Stage 7Becomes an approved automated workflow
7% · Governed
Bottom of funnel. Fully institutionalized.
The Hidden Tax

Weak coordination is already producing measurable waste.

Coordination gaps aren't theoretical. They're already producing duplicated work, inconsistent context, and preventable capability loss — happening at least sometimes across marketing teams.

Locked Knowledge
76%
say useful AI knowledge remains with individuals — including 41% who say this happens often or very often.
Duplicated Work
68%
have similar prompts or workflows recreated at least sometimes — 28% often or very often.
Expertise Loss
58%
lose AI expertise when employees or agencies leave at least sometimes.
Repeated Research
58%
redo the same research at least sometimes.
Content Overlap
56%
independently generate similar content — 32% often or very often.
Conflicting Context
51%
see conflicting versions of context flowing through prompts.
Chapter Three

Tools without discipline.

Organizations aren't experimenting with a single platform — they're assembling multi-tool environments faster than they're setting rules for when each product should be used, or knowing what any of it costs.
64%
Use ChatGPT for marketing
48%
Choose by personal or team preference
17%
Don't know monthly AI spend
The AI Stack in Use Today

Marketers are running multi-tool environments — not making a single-vendor bet.

ChatGPT dominates, but 4 of the top 5 products are used by a quarter or more of respondents — meaning overlapping capabilities are the norm, not the exception.

Top AI products in use for marketing · % of respondentsn=100
01
ChatGPTGeneral-purpose · OpenAI
64%
02
Google GeminiGeneral-purpose · Google
41%
03
ClaudeGeneral-purpose · Anthropic
32%
04
Microsoft CopilotProductivity-embedded · Microsoft
29%
05
Canva AICreative & design
24%
06
PerplexityResearch assistant
13%
07
Google Ads AI · ElevenLabsMedia / voice specialists
8%
How Tools Are Actually Chosen

Product choice runs on preference, not portfolio strategy.

The most common decision model is "employees use whichever product they prefer" (30%) or "each team chooses its own" (18%). 8× more organizations pick tools by preference than by formal criteria.

How AI products are chosenn=100
48%
Preference-Driven
Employees use whichever product they prefer30%
Each team chooses its own preferred products18%
Formal mix of quality, cost, risk, data, task6%
Approved product list5%
Other structured methods7%
The Money Nobody Can See

AI spend is scattered. Visibility is worse.

The largest reported group — 17% — doesn't know what their organization spends on AI each month. Central visibility across the whole stack sits at just 14%.

How AI spending is managed · % of respondentsn=100
Corroborated by — AI tool sprawl is the new SaaS-waste problem IDC 2025: enterprise AI tool deployments are projected to grow 150% from 2025 to 2027, largely driven by team-level and individual purchasing outside central IT. Tungsten Automation 2025: AI fragmentation is now cited as one of the top hidden risks of rapid enterprise adoption. The 17% of respondents here who don't know their monthly AI spend is a leading indicator, not a rounding error.
Distributed across cards, teams, agencies
28%
Each team tracks its own AI spend
21%
Central budget owner exists
15%
See subscriptions but not usage costs
14%
Central visibility across nearly all AI spend
14%
Not sure who owns AI spend
9%
Little or no reliable visibility
8%
Chapter Four

Oversight without ownership.

Human approval is the leading control across every AI marketing activity — but most programs still depend on manual checkpoints rather than fully-designed governance systems with clear accountability and reliable auditability.
51%
Human approval on paid-media activation
11%
Have mature role-based governance
5%
Apply requirements consistently across teams
The Only Governance Everyone Trusts

Human review is everywhere. Traceability lags 25 points behind.

Across every AI-touched marketing activity, human approval is the #1 control. Organizations are managing risk by keeping people in the loop — but review without a recorded decision trail is oversight, not governance.

Human-approval requirement by activity · % of respondentsn=100
Corroborated by — governance maturity is a top enterprise gap Deloitte 2025 State of AI in the Enterprise: 88% of orgs use AI, only 8% maintain comprehensive governance. PwC 2025: 60% of executives cite Responsible AI as an ROI driver, yet only 15% have installed the underlying controls. The 11% mature-governance rate in this survey mirrors the enterprise-wide picture almost exactly.
Paid-media campaign activation
51%
Customer-facing claims
50%
Legal, privacy, or compliance content
48%
Approval of prompts, assistants, AI skills
47%
Brand strategy or positioning changes
43%
Audience, bidding, or budget changes
40%
Creative or synthetic-media assets
35%
The AI Governance Maturity Curve

Only 1 in 6 organizations has AI governance worth the name.

AI Governance Maturity Distribution · n=100
01
Individual DiscretionIndividuals decide with little oversight
17%
17%
02
Team-by-TeamEach team creates its own rules
21%
21%
03
Informal GuidanceInformal org-wide guidance
15%
15%
04
Written Policies (varying)Written but applied inconsistently
11%
11%
05
Central FoundationApproved tools, uses, reviews centrally defined
8%
8%
06
Role-Based & TraceableRole authority, approvals, traceability
11%
11%
07
Consistent Across OrgRequirements applied consistently
5%
5%
38%
Decentralized / Blind
Governance is individual or team-by-team — no shared standard.
26%
Emerging Middle
Informal guidance or written policies with varying application.
16%
Mature Governance
Role-based OR consistent org-wide. The rest live in between.
What Information Is Authoritative

Control-oriented info is authoritative. Learning-oriented info is not.

Legal & workflow rules are treated as source of truth. But the assets that would help teams reuse learning and scale AI — approved prompts, past campaign results, customer research — are still fragmented.

Authoritative · Shared & Current
What organizations protect
  • 39%Legal, privacy, compliance requirements
  • 38%Workflow, approval, decision rules
  • 33%Marketing calendar & launch timing
  • 31%Brand strategy, positioning, messaging
Not Authoritative · Fragmented
What they let drift
  • 21%Approved prompts, assistants, AI skills
  • 19%Past campaign results and learning
  • 17%Customer research & insights
  • 16%Audience & customer definitions
The Next 12 Months

The industry is pivoting.
From expansion to operating discipline.

Asked to rank top AI marketing priorities for the next 12 months, respondents chose governance (36%), strategy (28%), and context (27%) — the operating-model levers — over expanding AI into more teams. The market has stopped asking "where else can AI go" — and started asking "how do we make it work everywhere it already is."

Top AI marketing priorities · next 12 monthsn=100
Corroborated by — the market is pivoting from "where else can AI go" to "how do we make it work" BCG 2025 "Closing the AI Impact Gap": two-thirds of top marketing leaders now expect high-level AI-driven disruption, but the leadership focus has shifted from expansion to operating-model redesign. Gartner 2025: CMO budgets stay flat at 7.7% while 59% of CMOs report insufficient budget for AI — forcing a governance and prioritization conversation.
Improving AI governance
36%
Establishing AI strategy & roadmap
28%
Improving context consistency across tools
27%
Defining approval & decision rights
22%
Establishing executive ownership
21%
Improving alignment across channels
20%
Training employees
19%
Introducing AI agents
18%
Expanding AI into additional teams
8%
Clear Strategy · The Diagnostic

First, we tell you exactly where you are on the curve.

Every marketing organization is at one of five stages of AI maturity. Most don't know which. Clear Strategy's diagnostic maps you against the 420-item survey framework in 2 weeks.

STAGE 01
Individual
AI used independently with little org visibility. Innovation happens; institutionalization doesn't.
12%
of orgs
STAGE 02
Team-Isolated
Teams use own tools with little coordination. Duplicated work quietly compounding.
20%
of orgs
STAGE 03
Multi-Team, Inconsistent
Multiple teams use AI but practices vary. Largest cohort — and the most vulnerable.
29%
of orgs
STAGE 04
Coordinated
Coordinated through shared systems. First stage where value starts to compound.
9%
of orgs
STAGE 05
Integrated & Governed
Broadly integrated, governed, measured, continuously improved. The 5% compounding.
5%
target state
CS Diagnostic — 2 Weeks
We map your organization against the 420-item survey framework and produce a stage rating, the specific gaps that hold you at that stage, and the 3–5 moves that shift you up one level.
Step 1 of 3
Proprietary to Clear Strategy

The operating system for scalable AI marketing.

Nova Atlas OS™ closes the gap between adoption and impact by turning every fragmentation problem this survey found — Knowledge, Coordination, Tools, Governance, and Context — into a single connected discipline.

01 · KNOW
Knowledge Core
Ch.1 · Expertise
02 · COORD
Coordination Layer
Ch.2 · Handoffs
03 · STACK
Stack Discipline
Ch.3 · Tools
04 · GOVERN
Governance Grid
Ch.4 · Controls
05 · CTX
Context Engine
Ch.5 · Alignment
Clear Strategy · The Partnership

A fractional CMO with operating skin in the game.

Clear Strategy is not a consultancy that hands you a deck and leaves. We run the diagnostic, install Nova Atlas OS™, and stay embedded as your fractional CMO through the 90 days that matter.

The 90-Day Engagement
01
Days 1–14
Diagnostic & Baseline
Map your organization against the 420-item survey framework. Interview leads. Audit spend & stack. Deliver stage rating + gap-close roadmap.
InterviewsStack auditSpend auditStage rating
02
Days 15–60
Nova Atlas OS™ Installation
Stand up the 5 modules — Knowledge Core, Coordination Layer, Stack Discipline, Governance Grid, Context Engine — with your team.
PlaybooksGovernance gridPrompt libraryApproved stack
03
Days 61–90+
Fractional CMO Cadence
Ongoing operating rhythm — weekly reviews, monthly leadership sessions, quarterly re-diagnostics. Nova Atlas stays with you.
Weekly reviewsLeadership syncsQuarterly rediagnostic
Who This Is Built For
$5M–$150M consumer brands scaling on real AI.
Clear Strategy works with founders and CMOs of DTC, Amazon, wellness, subscription, and creator-led consumer brands — the ones already spending on AI without yet compounding it.
  • $5M–$150M revenue · scale-up phase
  • Marketing team of 3+ using AI daily
  • Multiple AI tools already in the stack
  • Board pressure to prove AI ROI
  • Ready to install operating discipline
End of Report · The Invitation

Close the gap.

Move from the 62% who are experimenting to the 5% who compound. The next Clear Strategy diagnostic starts in two weeks — and Nova Atlas OS™ is available to the first cohort of founding partners.

Take the Assessment Start the Marketing OS Diagnostic
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ContactCJ · Clear Strategy
Nova Atlas OS™clear-strategy.com/NovaAtlas
Founding Partner CohortOpen · Aug–Oct 2026
Sources & Methodology

The findings, triangulated.

This report is Clear Strategy's original 100-respondent, 420-question field study. Every claim on the site is grounded in that primary data. Where the pattern is also confirmed by leading independent enterprise studies, we've cited them alongside the finding — and listed the full set below.

Primary Data
Clear Strategy · State of AI in Marketing 2026
Field study of 100 marketing decision-makers · 420 items · Fielded via Pollfish · August 5, 2026
Corroborator · Adoption-vs-scale gap
McKinsey & Company · The State of AI 2025
88% of organizations use AI; 1% report AI maturity. Referenced for the adoption-vs-scale paradox on slide 05.
Corroborator · Value capture
BCG · Closing the AI Impact Gap 2025
Only ~25% of enterprises have captured measurable value from AI. Two-thirds of top marketing leaders expect high-level AI disruption.
Corroborator · Governance
Deloitte · State of AI in the Enterprise 2025
88% used AI in 2025; 8% maintain comprehensive AI governance. Directly corroborates the 11% mature-governance finding.
Corroborator · Responsible AI
PwC · Responsible AI Survey 2025
60% of executives say Responsible AI drives ROI & efficiency; 55% cite CX/innovation gains. Confirms the governance-as-value link.
Corroborator · Time reinvestment
Gartner · AI in Sales & Marketing 2026
AI saves sellers 4.8 hrs/week; 72% of sales orgs fail to reinvest time in high-value work. Mirrors acceleration-without-transformation.
Corroborator · Tool sprawl
IDC · Enterprise AI Deployment 2025
Enterprise AI tool deployments projected to grow 150% from 2025–2027. Supports the tool-stack fragmentation finding.
Corroborator · Agentic enterprise
MIT Sloan Management Review · The Emerging Agentic Enterprise 2025
35% adoption of agentic AI, 44% planning to deploy. Confirms individual-expertise pattern and the coming governance pressure.
A note on methodology. Third-party citations are provided as independent corroboration only — none of them contributed data to the Clear Strategy findings. Every percentage on this site labeled n=100 comes from the Clear Strategy field study. Where a headline claim is materially reinforced by an outside source, that source is named inline; the complete corroborator list is here.