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AI is a core part of modern marketing strategies, but most organizations have yet to master it. AI adoption rates continue to grow, with 63% already using it and 79% of companies expanding AI adoption in 2025. However, only 10% of marketers self-report highly advanced AI maturity, according to our recent 2025 State of AI in Marketing report.
This gap means that the vast majority of businesses are still figuring out how to make AI work at scale—and missing out on efficiency, innovation, and competitive opportunities as a result.
High-maturity AI marketing organizations stand out because they’ve moved beyond experimentation and made AI an integral part of their strategic vision. They’ve embedded AI into their core operations and workflows, and in turn have unlocked AI’s full potential to drive innovation and growth.
So what exactly sets these organizations apart? What are they doing that others aren’t? To answer that question, let’s look at the seven key traits that define high-maturity AI organizations, and how your team can adopt these practices to elevate its own AI strategy.
1. Documented Use Cases
One of the fundamental traits of high-maturity AI organizations is a commitment to documenting AI use cases. Rather than approaching AI as a series of disconnected processes, they systematically document how AI is used throughout the organization and what metrics—end define success metrics before testing begins. While it might seem like a simple step, it’s one that many organizations gloss over.
Our research underscores the gap: 78% of marketing teams started using AI in 2024, despite the much lower percentage of mature AI enterprises. Employees are using AI in silos to meet the demands of their jobs, but it’s not a connected part of the overarching marketing strategy.
Documenting AI use is necessary to fix this. Right now, 75% of mature AI organizations document use cases, compared to just 22% in early stages. A proactive approach is needed to move past AI experimentation and leverage it to drive performance improvements and business outcomes.
2. Continuous Experimentation
Mature AI organizations know that the technology is always evolving, and there’s never a time when experimentation and innovation should pause. They continually look for new applications and push the boundaries of what’s possible to stay ahead.
Our research found that 59% of high-maturity organizations regularly experiment with new ways to use AI, fostering a culture of curiosity and innovation—one where failure is not seen as a setback but a learning opportunity. Willingness to experiment also ensures organizations remain adaptable and agile, capable of quickly pivoting when new opportunities or challenges arise.
3. Leadership Buy-In
According to a 2023 McKinsey survey on AI adoption, one of the biggest obstacles to AI adoption is a lack of support from leadership. In companies with mature AI strategies, leadership buy-in is a priority. Senior leaders don’t just sign off on AI projects from a distance—they actively participate in setting the AI vision and strategy.
Given the gap between executive perception of AI maturity—44% believe their organizations are “very advanced” vs. 27% of those responsible for execution—it’s likely that leadership buy-in and a commitment to actually using AI are the missing pieces to accurate maturity assessment. Our research found that mature organizations have the highest percentage of leaders currently using AI in their work today (54%).
Leadership commitment is crucial because it drives momentum and resource allocation. It also ensures that AI initiatives align with broader business objectives, making it easier to secure funding and cross-functional collaboration. When leadership is genuinely invested, it signals to the entire organization that AI is not just a passing trend but a core strategic initiative.
Mature marketing organizations have the highest percentage of leaders currently using AI in their work today (54%).
4. Workflow Integration
High-maturity organizations understand that AI shouldn’t be treated as a side project or separate function, but rather needs to be embedded into everyday workflows. Currently, 51% of mature AI marketing teams have successfully integrated AI into their workflows.
This means AI-driven insights aren’t just theoretical but practical and actionable, integrated into daily operations. This is crucial because it breaks down silos and ensures AI-driven insights are accessible to all relevant teams.
Rather than being restricted to a specialized data science unit, AI tools and insights are a part of key processes like marketing optimization, customer engagement, and sales forecasting. This holistic approach powers faster decision-making and more consistent use of insights across all functions and departments.
5. Measurement of AI ROI
High-maturity AI organizations rigorously measure the ROI of their AI initiatives. Establishing clear metrics from the start ensures teams know whether their efforts are driving tangible value or falling short of expectations.
Mature organizations recognize this and make ROI measurement a fundamental part of their AI strategy. According to our data, 96% of advanced marketing teams track AI ROI, while most early adopters still struggle to link AI initiatives to business outcomes. Tracking ROI aligns AI projects with larger business objectives and demonstrates the impact of AI investments.
Without measurable outcomes, it’s impossible to justify continued funding or scale successful approaches.
96% of advanced marketing teams track the ROI of their AI investments, while most early adopters still struggle to link AI initiatives to business outcomes.
6. Strong AI Governance
Governance is a cornerstone of responsible AI use: 79% of high-maturity organizations have a dedicated AI council, 86% offer advanced AI training, and 79% provide documented policy and guidelines.
Without strong governance and oversight, AI initiatives can become risky, leading to potential issues like bias, data privacy breaches, or compliance violations. High-maturity AI organizations mitigate these risks with formal governance structures like AI councils, transparent policies, and comprehensive training programs.
A commitment to strong AI governance fosters transparency and accountability, building trust both within the organization and with external stakeholders.
7. Domain-Specific AI Adoption
Finally, high-maturity marketing organizations know that general-purpose AI isn’t built for the complexities of enterprise marketing. Horizontal tools may check the box—but they fall short when it comes to maintaining brand voice, optimizing for SEO, or ensuring compliance at scale. That’s why leading teams invest in domain-specific solutions like Jasper—purpose-built to meet the real demands of marketing.
Today, 71% of high-maturity organizations use domain-specific AI solutions, vs. 21% using general-purpose tools. Those using purpose-built tools are 37% more likely to measure the ROI of their AI investments and drive clearer outcomes that make a business case for AI expansion.
How to Move Toward Maturity
Becoming a high-maturity AI marketing organization requires committed leadership and alignment at every level. It’s not about scattered experiments—it’s about building a strategic, organization-wide approach that embeds AI into daily workflows. The most successful teams go beyond testing and move toward operationalization, backed by strong governance, executive ownership, and real-world integration.
In other words: The difference between mature and immature AI organizations isn’t just technology, but how they put it to work. Focusing on the seven traits outlined in this guide can help your organization move faster and more intentionally toward AI maturity, aligning your strategy for AI adoption with your larger goals for success.
Get ahead of the curve. Our 2025 State of AI in Marketing report reveals how high-performing teams are using AI to lead, scale, and grow.
