Adobe's CMO on agentic AI tools and governing their use in marketing
Adobe is positioning agentic AI-software that operates with some autonomy to complete marketing tasks-as a core capability for brands managing customer experience at scale. The company's CMO discussed how marketers should think about deploying these tools and the governance structures needed to use them responsibly.
Agentic tools differ from traditional AI assistants. Rather than waiting for a user to request each action, agents can identify tasks, execute them, and report results with minimal human intervention. For marketers, this means automating workflows across customer data, campaign management, and personalization without constant manual oversight.
Adobe's CX Enterprise platform uses AI agents to power customer experience systems for brands. The platform handles tasks like segmenting audiences, adjusting messaging in real time, and optimizing channel selection based on customer behavior.
Governance matters more as autonomy increases
As agents take on more responsibility, the need for clear governance grows. Adobe's CMO emphasized that marketers must establish guardrails before deploying agentic systems-defining what decisions agents can make independently and which require human review.
This includes auditing agent decisions for bias, ensuring compliance with data regulations, and maintaining transparency about how customer data flows through automated systems. Without these controls, brands risk damaging customer trust or violating regulations.
Marketing teams should also document why agents made specific decisions, particularly when those decisions affect customer communications or personalization. This creates accountability and helps teams learn from agent behavior over time.
Adoption depends on trust and training
Marketers won't adopt agentic tools if they don't understand how they work or trust their outputs. Teams need training on what these systems can and cannot do, how to interpret their recommendations, and when human judgment should override automation.
The shift also requires changes to how marketing organizations operate. Teams accustomed to owning specific tasks may need to transition into oversight and strategy roles, monitoring agent performance rather than executing routine work.
Brands experimenting with agentic AI now are learning which use cases benefit most from automation. Customer segmentation and campaign optimization are showing early results, while more complex creative decisions still benefit from human input.
For AI for Marketing professionals, understanding agentic systems is becoming essential. CMOs and marketing leaders should explore the AI Learning Path for CMOs to develop strategies for deploying these tools effectively.
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