The 2025 Cella Intelligence Report landed last week, and its findings confirm what I observed up close at CES in January this year: the greatest barrier to marketing AI isn't technological, it's human. I commend it to you for a read. While AI capabilities advance at breakneck speed, marketing teams remain firmly anchored in outdated mindsets and adoption patterns.
This annual study, based on data from creative teams across 25 industries, reveals a fundamental disconnect that should alarm every CMO: the technology is ready, but your people aren't.
The report's most revealing statistic isn't about technology adoption but human readiness: 54% of organisations cite "lack of in-house expertise" as their primary barrier to AI implementation. Not budget constraints. Not technological limitations. Human capability.
This expertise gap is widening precisely when AI technology itself is becoming more accessible. Consider these contradictions from the report:
88% of marketers claim to use AI, but only 5% report strong expertise in specific AI areas
61% of companies are investing in AI at the corporate level, but only 48% provide AI education
63% cite "increased productivity" as their main AI goal, while only 8% leverage it for analytics
The pattern is clear: We've reached a point where the technology is no longer the limiting factor. Our people are.
The Three Adoption Mindsets (Hint: Only One Leads to Success)
The Cella data reveals three distinct adoption mindsets emerging across marketing organisations:
Mindset One: The Tool Collectors (Destined for Obsolescence)
These teams represent the majority. They approach AI as a collection of isolated point solutions to be added to existing workflows. They've adopted ChatGPT (80%) and Adobe Firefly (56%) but treat them as glorified productivity tools.
While they claim to embrace innovation, their fundamental approach remains unchanged. They've simply grafted new technologies onto old thinking—like attaching a jet engine to a horse and carriage. The result is faster movement in the wrong direction.
What's most damning is their approach to talent: only 6% are hiring AI specialists, while 48% attempt to "upskill" current teams without fundamentally changing team composition or structure. They're trying to transform outcomes without transforming capabilities.
The Tool Collectors reveal themselves through telltale behaviours:
Tool-first thinking: They start by asking "How can we use ChatGPT?" rather than "What capabilities do we need to develop?"
Isolated implementation: AI tools remain siloed, disconnected from core workflows and systems
Preservation bias: They design AI implementation to maintain existing roles, hierarchies, and workflows
Surface-level metrics: Success is measured by adoption rates and efficiency gains rather than capability development
These organisations are essentially building high-tech versions of traditional marketing teams. They'll produce more content, faster and cheaper—but will fundamentally miss the transformative potential of AI as a new form of organisational capability.
Mindset Two: The Cautious Integrators (Racing Against Time)
About 29% of organisations have begun integrating AI into workflows rather than treating it as standalone technology. They're rethinking processes and restructuring teams, but their pace remains dangerously slow.
These teams understand the need for transformation but are attempting to manage it incrementally in a market where change is exponential. They recognise the expertise gap but underestimate the learning curve. Most critically, they're attempting to preserve existing structures while gradually introducing new capabilities—an approach that virtually guarantees they'll always lag behind the leaders.
The Cautious Integrators display distinct patterns:
Process-oriented approach: They focus on integrating AI into existing workflows rather than reimagining what's possible
Incremental transformation: They set modest, achievable goals rather than embracing disruptive change
Balanced investment: They split resources between traditional capabilities and new AI skills
Hybrid metrics: They balance efficiency metrics with emerging capability measurements
These organisations aren't building entirely new capabilities so much as enhancing existing ones. They understand the direction but lack the velocity to reach safety before the market fundamentally changes.
Mindset Three: The Capability Revolutionaries (Building Insurmountable Leads)
The elite minority—less than 10% according to Cella's data—aren't just adopting new technologies; they're developing entirely new organisational capabilities. Their focus isn't on tools but on building learning systems—both technological and human.
These organisations have realised something profound: The AI revolution isn't about better software; it's about better learning. They're not just using AI; they're becoming AI organisations where human and machine intelligence amplify each other.
What separates them isn't budget or access to technology—it's their willingness to completely reinvent how marketing expertise is developed, deployed, and integrated with AI capabilities. They're creating hybrid intelligence systems where the boundaries between human and machine capabilities blur, creating something greater than either alone.
The Capability Revolutionaries exhibit these distinctive traits:
Problem-first thinking: They start by identifying unsolved problems rather than implementing specific technologies
Systems approach: They build integrated learning systems that combine human and machine intelligence
Structural reinvention: They create entirely new roles, teams, and organisational models designed for the AI era
Capability metrics: Success is measured by the rate at which new capabilities emerge and create value
These teams aren't just doing marketing differently; they're fundamentally redefining what marketing is. They understand that AI isn't just a tool but a new form of organisational intelligence.
The Real AI Crisis: Learning Velocity
The Cella report accidentally reveals the real crisis in marketing AI: learning velocity. The pace at which an organisation can develop new capabilities has become the primary determinant of competitive advantage.
Consider these startling findings:
Only 20% of creative teams are increasing AI knowledge through "focused education"
41% report only "some knowledge" of AI
32% are complete novices
Meanwhile, AI capabilities themselves are doubling every 6-12 months. This creates a widening capability gap that most organisations have no strategy to address.
The Hard Truth: Your AI Strategy Is Actually a People Strategy
Let's be brutally honest: If your AI strategy doesn't fundamentally address how your team develops, deploys, and evolves human expertise, it isn't an AI strategy at all, it's a technology procurement plan.
The Cella report makes clear that the primary barrier to AI transformation isn't technological, it's human. The teams that recognise this shift their focus from implementing technology to transforming how their people learn, collaborate, and create value alongside AI.
The question isn't whether your team is using AI—the Cella data shows 88% are. The question is whether you're building an organisation capable of learning at the pace AI is evolving. If you're not fundamentally transforming how your team develops and deploys expertise, you're already obsolete; you just don't know it yet.
Next Steps: From Strategy to Action
If you recognise your team in the Tool Collectors or even the Cautious Integrators, here are five concrete steps to begin shifting toward capability revolution:
Conduct a capability audit: Assess your team's current AI capabilities, not just tool adoption. Map both technological and human capabilities against future market requirements.
Establish learning velocity metrics: Begin measuring not just what your organisation produces but how quickly it develops new capabilities. Track the time from identifying a needed capability to its effective deployment.
Create hybrid capability teams: Form cross-functional teams that combine AI technical expertise with domain knowledge and strategic perspective. Measure their impact not just on productivity but on capability development.
Implement immersive learning environments: Create controlled spaces where teams can develop new capabilities by applying AI to real business problems, with shortened feedback loops and rapid iteration.
Redesign core workflows: Identify one critical workflow and completely reimagine it for the AI era. Use this as a case study and learning opportunity for the broader organisation.
The gap between AI leaders and laggards is widening daily. The teams that recognise the human nature of this challenge—and respond with human transformation rather than just technological implementation—will define the next era of marketing.
Are you collecting AI tools, or building AI-era capabilities?
Brandflow is written by Justin Billingsley, who has spent his career on all three sides of the industry's table: senior client, global agency leader, technology founder. First published 13 May 2025 in the Brandflow newsletter on LinkedIn.