Australian marketers are embracing AI, but maturity levels are lagging, with 83% of organizations sitting at the early stages of development and none reaching the two highest levels, according to the largest benchmark of CMOs on AI adoption and implementation from the Australian Centre for AI in Marketing (ACAM).
Built on responses from 126 CMOs and senior marketing leaders across 12 industries, the annual ‘Australian AI in Marketing Benchmark Report’ was developed from independent ACAM and Kantar research and supported by IBM. The report finds AI has moved from curiosity to daily marketing reality. However, AI roadmaps remain underdeveloped, workflow redesign is immature, and ROI proof is inconsistent, which is holding back scale.
To drive greater visibility, ACAM has launched Australia’s first structured framework to give CMOs a practical way to understand where they sit in AI maturation compared to peers. The six levels of AI marketing maturity are assessed across seven maturity drivers: Leadership and Culture; Skills and Capability; Governance, Risk and Brand; Data and Technology Readiness; Use Cases and ROI; Team Design and Workflow; and Roadmap, Planning and Investment, to provide a holistic view of how organizations are adopting, embedding and implementing AI in marketing.
ACAM’s benchmark shows most marketing teams are stuck in the “early to middle stages of the maturity journey,” with 31.7% of respondents classified as level two ‘Established Beginners’ — AI recognized but inconsistent. Teams are trying AI tools but use is patchy and not yet connected to strategy. Half of respondent organizations (50%) come in at level three ‘Early Emerging’ — growing adoption and capability.
AI use is spreading and skills are building, but maturity remains uneven. Just 16.7% of organizations are placed at level four ‘Mature Emerging’ — structured implementation emerging, where AI priorities, governance, workflows and measurement are starting to align.
“Twelve months ago, much of the conversation was about experimentation and early adoption,” said Douglas Nicol, co-founder of ACAM and head of original thinking.
“In 2026, the question has changed. It is no longer what AI tools marketing teams are using, it is whether they are building the maturity to turn AI activity into serious commercial impact. The findings show real progress: Maturity leadership confidence is growing, use cases are expanding and governance is becoming more visible, but the gap is also clear. Roadmaps remain weak, workflow redesign is immature and ROI proof is inconsistent. The momentum is real, but it’s uneven.”
Roadmaps remain weak, workflow redesign is immature and ROI proof is inconsistent. The momentum is real, but it’s uneven.
According to ACAM’s framework, no organization has reached the top two levels of AI marketing maturity: level five ‘Early Advanced’ — advanced operationally embedded, where AI is becoming part of how marketing work gets planned, created, measured and improved — and level six ‘Leading Advanced’ — scaled and strategically integrated, where AI is connected across maturity leadership, capability, data, governance and commercial outcomes.
Lack of AI roadmap
ACAM’s 2026 Australian AI in Marketing Benchmark Report found that while marketers have embraced AI, most teams still lack the blueprint to scale it. While AI activity continues to rise, a majority of organizations are operating without clear plans, investment logic or roadmap discipline, with only six percent of organizations reporting a fully documented roadmap, and almost six in ten (58%) reporting no documented roadmap at all.
AI’s confidence divide
The report also shows that while CMOs are leading optimistic teams, they are often managing a confidence divide. When asked how their team felt about AI in marketing, 69% said the majority sentiment was ‘excited but cautious,’ but 56% of CMOs reported a concerned minority that was either cautious, scared or negative. The proportion of scared team members in that minority has increased by 22 points since 2025.
Arranged AI platform marriages
Enterprise AI platforms are becoming an arranged marriage for marketing teams. Access to tools, often selected at the C-suite level, is improving, but alignment with workflows, data and use cases remains uneven. 45% of organizations say their platforms are disappointing, harder than expected or only OK, compared to 55% who say their AI platforms have delivered better-than-expected performance or have overdelivered, highlighting the gap between access and marketing value.
AI slop
AI slop is the number one operational concern in the benchmark, cited by 61% of CMOs. A further 32% listed brand damage as a concern, underlining the risk that faster content production can create sameness and weaken distinctiveness.
“Organizations don’t need more AI hype. They need clarity on where they are today, where the opportunities lie and what to do next,” said Karin Du Chenne, group executive director at Kantar.
“Through our partnership with ACAM, we’re helping organizations measure AI readiness and turn insight into action.”
IBM ANZ chief marketing officer Miki Luong added: “As the conversations around AI in marketing move beyond individual use cases to embedding AI into the workflows, processes and systems that drive meaningful gains, marketers must ask themselves broader questions around how their teams operate, how decisions get made, how data flows through the organization and how customer engagement is orchestrated.”
Natalie Lockwood, chief marketing officer at NAB, said: “The progression from 2025 to 2026 shows an industry moving forward at pace with AI.”
“The shift from ‘Established Beginner’ to ‘Early Emerging’ maturity is encouraging because AI is becoming part of how marketing teams think, plan and operate. But it is also a reality check. We are not yet at scale. The next challenge for CMOs is turning rising confidence and activity into capability, workflows, clearer roadmaps, governance and measurable commercial impact.”
The majority of CMO responses, 38% to this year’s benchmark, were from organizations with 1,001 or more employees, 29% were from organizations with 101 to 1,000 employees and a third (33%) came from those with under 100 employees.
