Generative AI has quickly moved beyond experimentation to become an integral part of production for content teams. Meanwhile, early adopters are already layering agentic AI on top to connect previously siloed processes.

Nearly half of organizations have embedded generative AI organization-wide or across multiple functions for marketing content creation and activation, at a rate higher than any other workflow. Agentic AI is still in the early stages, but some organizations are already making headway, with nearly a quarter having deployed it in the same area.

Creativity is another area undergoing meaningful investment, with 24% having deployed generative AI to an equal degree for creative thinking tasks or processes, such as ideation. Meanwhile, 15% have already achieved widespread deployment of agentic AI to augment such tasks (Figure 1).

With early returns from generative AI now visible, organizations are channeling investment toward a more ambitious goal: using agentic AI to intelligently orchestrate content processes at scale.

Delivering more personalized customer experiences tops the list of AI investment goals for organizations over the next 18 months. Automating repetitive tasks and workflows is also a major focus, with 45% rating this a top-three AI investment priority at their organization. And nearly one-third (31%) are committed to increasing and accelerating content creation and activation efforts through their AI investments, recognizing the importance of maintaining a scalable and adaptable content strategy.

To achieve these goals, organizations are betting on agentic AI to reshape internal operations in the near term. The expected use cases span the full breadth of content workflows. As many as 69% expect agentic AI to assist employees with research, insights, or knowledge retrieval, and 59% foresee it managing internal workflows, such as approvals, routing, and scheduling. Fewer (44%) anticipate that agentic AI will create content for marketing campaigns — including original and derivative assets based on marketing briefs. This suggests that some organizations recognize the clear opportunity to enhance their marketing strategies with AI-driven content creation, but the path to broad adoption remains uncertain for many (Figure 2).

The path from AI experimentation to scaled, enterprise-wide embeddedness is not without significant obstacles. Data readiness, talent shortages, and measurement gaps are converging to slow progress for brands — while the additional imperative of governing on-brand, compliant content at scale adds another layer of complexity.

Data quality remains the most pervasive barrier. Less than half of brands (44%) believe their data quality and accessibility are adequate for AI today, suggesting further complexity involved in the scalability of AI-driven solutions. Moreover, 52% feel that their ability to advance AI initiatives is limited by their current level of data unification and structure. The challenge intensifies for agentic AI specifically: data integration and quality issues are major obstacles to agentic AI implementation for three-quarters (75%) of organizations, highlighting the need for robust data management practices.

Workforce talent is nearly as big a challenge: 71% identify a lack of relevant skills and limited upskilling resources as barriers to agentic AI implementation. And while 53% of organizations say they are committed to providing the training employees need to become proficient with AI tools, fewer (45%) believe they have sufficient AI upskilling programs in place today (Figure 3). Without the people who can build, manage, and optimize agentic workflows, even the best data infrastructure will underdeliver.

Generative AI is already enabling marketing and creative teams to push the volume and speed of production to new heights. However, as AI increasingly becomes the first touchpoint for customers, brands will need to restructure their entire content supply chain to remain discoverable and competitive.

Agentic AI offers the potential to optimize operations and orchestrate content creation and management at scale to deliver the highly personalized, on-brand experiences customers expect. Brands will not be able to realize this potential with isolated AI tools or point solutions. Successful deployment requires an integrated content supply chain that connects people, workflows, assets, and data end to end.

Organizations can take key steps to prepare for an agentic future:

• Optimize content to be AI-readable and discoverable. Properly tag, structure, and catalogue content to reach a customer base increasingly partial to AI discovery tools.

• Unify data to successfully scale agentic AI. Improve data quality and accessibility to enable agentic AI tools to optimize workflows with real-time insights.

• Align leadership’s AI vision with workforce readiness. Invest in upskilling resources to build AI talent and establish measurement frameworks that clearly demonstrate AI’s real value.