The AI Marketing Maturity (AIMM) Index – March 2026
Key Findings –
In March 2026, ProGEO.ai surveyed 112 marketing professionals.
Key findings from the ProGEO.ai AI Marketing Maturity (AIMM) Index include:
91.1% (n=102) of marketing professionals have an enterprise subscription to a GenAI platform.
57.1% (n=64) of marketing professionals have a personal paid subscription to a GenAI platform.
76.8% (n=86) of marketing professionals report their company has a corporate usage policy for GenAI.
43.8% (n=50) of marketing professionals report their company enforces a corporate usage policy for GenAI with technical controls.
75.9% (n=85) of marketing professionals use GenAI on a daily basis for work.
83% (n=93) of marketing professionals use GenAI to brainstorm content at least once a week – the most frequent use case.
23.2% (n=26) of marketing professionals use GenAI for vibe coding at least once a week – the least frequent use case.
Overview –
In March 2026, ProGEO.ai surveyed 112 marketing professionals at RSAC, the largest cybersecurity conference in the world. Within this enterprise technology population, GenAI has reached nearly universal adoption – 91.1% have a company-paid subscription to GenAI platforms.
In 2022, an MIT Technology Review Insights survey forecast the widescale adoption of AI for 64% of marketing and advertising use cases by 2025. In March 2026, ProGEO.ai found that 75.9% of marketing professionals use GenAI on a daily basis.
There is a gap between the most frequent use case – 83% of marketing professionals use GenAI to brainstorm content at least once a week – and the least frequent use case – 23% of marketing professionals use GenAI for vibe coding at least once a week. This gap is even more pronounced between high intensity and low intensity users.
The ProGEO.ai AI Marketing Maturity (AIMM) Index measures GenAI adoption rates and usage patterns. The results of this survey are intended to serve as a benchmark for marketing professionals to reflect on their own opportunities for growth.
What is the enterprise adoption rate of GenAI in 2026?
The widespread adoption of GenAI is readily apparent – according to a ProGEO.ai survey of 112 marketing professionals, 91.1% (n=102) have a corporate-paid subscription to at least one GenAI platform.
GenAI Platform Adoption – Corporate Subscriptions
ProGEO.ai survey, March 2026 (n=112)
Nearly half of survey respondents (49.1%) have multiple enterprise subscriptions to GenAI platforms – the market is currently multi-platform, not winner-take-all.
Anthropic gains market share as OpenAI declines
When OpenAI launched ChatGPT in November 2022, it reached one million users in its first week. ChatGPT maintained a dominant, but shrinking market share through 2025.
When Anthropic launched Claude Code in February 2025, it presented serious competition for OpenAI. The AIMM Index indicates Anthropic has achieved strong market penetration in the cybersecurity industry.
GenAI Market Share – Corporate Subscriptions
ProGEO.ai survey, March 2026 (n=112)
According to a ProGEO.ai survey of 112 marketing professionals, ChatGPT maintains only a slight market share advantage over Claude – 66 survey respondents indicated a corporate-paid subscription to ChatGPT, while 56 respondents indicated Claude.
This research did not benchmark user preference for GenAI platforms. According to Arena – an AI leaderboard created by researchers from UC Berkeley – Anthropic’s Opus 4.6 model was leading both text and code generation at the time of this publication (April 9, 2026).
Most marketing professionals pay for GenAI
GenAI Platform Adoption – Personal Subscriptions
ProGEO.ai survey, March 2026 (n=112)
According to a ProGEO.ai survey of 112 marketing professionals, 57.1% (n=64) have a personal paid subscription to a GenAI platform. This is a notable difference from the nearly ubiquitous and multi-platform enterprise adoption rates – 42.9% (n=48) of respondents do not have a personal paid subscription to a GenAI platform, and only 16.1% have multiple personal paid subscriptions.
GenAI Market Share – Personal Subscriptions
ProGEO.ai survey, March 2026 (n=112)
The market share among personal-paid subscriptions is fairly similar to the distribution of corporate-paid subscriptions – 40 survey respondents indicated a personal-paid subscription to ChatGPT, while 33 indicated Claude.
Marketing professionals may pay for personal subscriptions to GenAI platforms to separate their personal use for enterprise accounts. However, if they use their personal subscriptions for work, then they represent the risk of unmanaged “Shadow AI” accounts.
Most cybersecurity teams do not enforce GenAI usage policies
Corporate usage policies for GenAI reflect an organization’s intentional approach to adoption.
GenAI Corporate Usage Policy
ProGEO.ai survey, March 2026 (n=112)
According to a ProGEO.ai survey of 112 marketing professionals, 76.8% (n=86) have a corporate usage policy for GenAI.
Notably, there is not a direct overlap between the adoption of GenAI and the implementation of a corporate usage policy – 5.4% (n=6) of marketing professionals reported a corporate usage policy for GenAI, even though they did not have a corporate-paid subscription. Many lagging adopters seem intentional in their avoidance of GenAI.
GenAI Policy Enforcement
ProGEO.ai survey, March 2026 (n=112)
Even though three-quarters of organizations have a corporate usage policy, less than half are enforcing it – 43.8% (n=49) of respondents reported their organization was using technical controls to enforce its corporate usage policy.
The cybersecurity industry has a gap between policy and enforcement – this gap is likely even more pronounced outside of the cybersecurity industry.
How frequently do marketing professionals use GenAI?
The AI Marketing Maturity (AIMM) Index measures marketing adoption rates across a variety of GenAI functional domains – 75.9% (n=85) of marketing professionals use GenAI on a daily basis for work.
The frequency of GenAI marketing use cases
GenAI Use Case Frequency Distribution
(ordered by daily adoption rate)
% of Respondents
ProGEO.ai survey, March 2026 (n=112)
The top five marketing use cases for GenAI (ordered by daily use):
Content creation — Defined as “generating first-draft content or reviewing/editing human-written content.”
Recording or transcribing meetings or notes.
Repurposing or personalizing content.
Brainstorming content — Defined as “concepts, themes or outlines.”
Market research or competitive intelligence — Including summarizing documents.
These results demonstrate that marketers are comfortable using GenAI for content creation and market research – the most obvious use cases.
The bottom five marketing use cases for GenAI (order by daily use):
Reporting — Defined as “measurement, data analysis, charts, or presentations.”
Automation or integration — Defined as “workflows, APIs, or connected tools.”
Role-playing — Defined as “coaching or persona-testing messaging.”
Image creation
Vibe coding — Defined as “HTML, scripts, or tools.”
One of the most significant observations is that nearly a quarter of cybersecurity marketing professionals are vibe coding at least once a week. These marketing professionals are exhibiting their agency as citizen developers – vibe coding is lowering technical barriers to democratize development.
Correlating GenAI marketing uses cases – content marketing and marketing operations
GenAI Use Case Correlation Heatmap
Spearman rank correlation (ordered by daily adoption rate)
ProGEO.ai survey, March 2026 (n=112). Diagonal cells (self-correlation) shown as 1.00.
Brainstorming content – defined as “concepts, themes, outlines” – was most closely correlated with creating content – defined as “generating first-draft content or reviewing/editing human-written content.” Creating content was also closely correlated with repurposing content.
Automation or integration – defined as “workflows, APIs, connected tools” – was most closely correlated with reporting – defined as “measurement, data analysis, charts, presentations” – and vibe coding.
These correlations reveal two distinct marketing personas: content marketing and marketing operations.
The intensity of GenAI marketing use cases
ProGEO.ai surveyed 112 marketing professionals on their frequency of GenAI use cases. Each respondent earned a score between 0 (never) to 4 (daily) across 10 use cases. Those 10 scores were added up, representing their AI usage intensity.
ProGEO.ai divided the respondents into three roughly equal groups. The low tier (n=40) had a score range of 0 - 21. The medium tier (n=37) had a score range of 22-28. The high tier had a range of 29 - 40. The average score across all 112 respondents was 23.8 (out of 40).
AI Maturity Tier Profile Across Use Cases
Average frequency score by maturity tier (0 = Never, 4 = Daily)
ProGEO.ai survey, March 2026 (n=112)
The high intensity demographic shows high frequency across almost every use case. The medium intensity demographic shows high frequency across the top five use cases – content creation, recording meeting, repurposing content, brainstorming, and market research. The low intensity demographic shows low frequency across the bottom five use cases – vibe coding, automation, role-playing, image creation, and reporting.
Conclusion – What can marketing learn from cybersecurity?
The ProGEO.ai AI Marketing Maturity (AIMM) Index is intended to serve as an industry benchmark, so that marketing professionals can measure themselves against it. The AIMM Index frequency matrix presents a baseline of marketing functions for a marketing maturity model.
Maturity models are common in the cybersecurity industry. For example, MITRE – a cybersecurity non-profit organization – published “The MITRE AI Maturity Model and Organizational Assessment Tool Guide” in 2023. The MITRE AI Maturity Model is broadly applicable to AI adoption, but lacks marketing process specificity.
Typical maturity models define assessment levels – ranging from awareness to experimentation to optimization – across a variety of functional domains (e.g., pillars and dimensions). The AIMM Index frequency matrix presents many of the marketing pillars and dimensions that should be considered for a maturity model.
One of the most frequently used terms when discussing cybersecurity AI maturity is governance – management and compliance. Another way for marketing professionals to think of governance is brand guidelines. Most marketing professionals are using GenAI to produce content on a daily basis, but have they deployed guardrails to ensure a consistent brand voice?
Ad hoc prompting could be just as dangerous to marketing as Shadow AI is to cybersecurity.
Although the AIMM Index measures GenAI adoption rates and intensity of use, there are more mature use cases that were not measured, such as building custom GPTs and skills, centralizing teams through projects or GitHub, or deploying MCP servers and vector databases – these are some of the use cases that enable governance of brand identity across marketing teams.
The AIMM Index revealed there is a gap between corporate policy and technical enforcement for cybersecurity teams – that gap is most likely present among marketing teams as well.
Methodology
In March 2026, ProGEO.ai surveyed 112 marketing professionals at RSAC, the largest cybersecurity conference in the world. RSAC reports nearly 44,000 attendees and 600 exhibitors were present.
The overwhelming majority of these surveys (~100) were completed by marketing professionals that work for cybersecurity companies, the remainder (~6-12) were completed by third-party marketing professionals.
Limitations
Cybersecurity is an enterprise technology industry and RSAC is expensive to attend for exhibitors – these are companies that have demonstrated a willingness to make investments in marketing, so the adoption rates of GenAI and marketing maturity may skew higher. The results of this survey may not be indicative of marketing professionals in other industries, or even the cybersecurity industry at large.
The survey instrument was constrained to one-page to encourage voluntary participation and completion, which compressed multiple use cases into a single domain. Many of these domains could be broken down into sub-functions (i.e. pillars and dimensions).
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