How Adobe is unlocking Customer Experience Orchestration in the age of agentic AI
"When you can move faster... Instead of having to go ten weeks, twelve weeks - if you could do it in a week or two, just think about how many things you can unlock, how many opportunities can unlock. I also think it gives marketers a chance to experiment more." – Rachel Thornton
Personalization has been one of marketing's most repeated promises for the better part of a decade. Everyone has understood why it matters but far fewer have had the infrastructure to deliver it effectively. What Rachel Thornton describes in this episode of The Speed of Culture podcast is a moment where the gap between the promise and the reality is finally starting to close.
Rachel is CMO of Adobe Enterprise, and she joined Matt Britton live from CES 2026 to talk about how Adobe helps enterprise brands move from customer data to genuine, individual experiences at scale. The conversation moves through AI tools, agentic workflows, sports partnerships, brand integrity, and a forward-looking take on marketing in a world where AI agents are becoming an audience of their own.
Tune into the latest episode or read on for the key takeaways.
The Data Stack Is the Starting Point
Rachel is direct about where personalization actually begins: with data, and with the ability to do something meaningful with it.
She describes how the Adobe Experience Platform functions as the foundation for enterprise marketing, helping brands build structured customer profiles from the data they already own. From those profiles, brands can start to understand journey, intent, and the moments where the right piece of content will land. Without that foundation, she argues, AI investments do not pay off the way they should. The data has to be in line first.
AI is not a shortcut around the hard work of understanding customers but rather what makes the hard work possible at scale.
Everyone Is a Creator
One of the most interesting moments in the conversation comes when Rachel pushes back on the idea that creativity belongs to a specific kind of person or team.
Her view is that everyone creates, from the designer building a campaign, to the sales development rep writing a customer outreach, and the founder shaping a product. What the Adobe suite has always been about, and what AI accelerates, is removing the barriers between someone having an idea and being able to bring it into the world. Adobe Express, Adobe Firefly, and AdobeGenStudio are all moving in this direction, making it possible for people across an organization to produce on-brand work quickly, without needing to route everything through a specialized creative team.
The downstream effect on how teams operate, how fast they can move, and how much they can experiment is significant. Rachel describes her own BDR team as an example. They now produce their own branded outreach materials independently, within Adobe's guidelines, without waiting on anyone else.
Agents Are Already Working
Rachel does not talk about agentic AI as a future possibility but as something her team already uses.
She gives an example of an Audience Agent that takes the results of a previous campaign and recommends how to build and refine the next target audience. Another example is an insights agent that surfaces campaign learnings without requiring a request to a separate analytics team. The common thread is friction reduction: getting marketers from question to answer faster, so they can get from idea to execution faster.
What shifts, she points out, is the range of what a marketer can attempt. When a campaign takes twelve weeks to build, teams can only make so many bets. When it takes one or two weeks, experimentation becomes a structural part of the strategy rather than an afterthought.
Brand Integrity as a Structural Advantage
As AI makes content generation faster and easier, Rachel raises the question that does not always come up loudly enough: what happens when it goes wrong?
For global enterprise brands, the risk of off-brand creative, legally problematic assets, or content that does not meet regional requirements is real and consequential. Adobe's answer is to build the guardrails into the workflow itself. Their work with The Coca-Cola Company is a concrete example: AI brand guidelines embedded into the creative tools so that any team member, anywhere in the world, can produce an asset with full confidence that it meets brand standards.
Rachel frames trust as a structural advantage and not just a value. In a competitive landscape where new AI tools appear constantly, the brands and platforms that can give enterprise marketers confidence in what they produce will earn the relationships that smaller, faster-moving competitors cannot.
A New Audience: Building for AI Agents
Perhaps the sharpest insight in the conversation is the one that most marketing teams have not fully caught up to.
Brands have always had to think about how they show up for human customers. Rachel argues that they now need to think with equal care about how they show up for the AI agents those customers are delegating their search and research to. When someone uses ChatGPT or Perplexity to find a product, a vendor, or a solution, the brand's presence in that space depends on the quality and structure of its content in ways that differ from traditional SEO. Adobe's LLM Optimizer was built to address exactly this, and the Semrush acquisition extends the capability further.
Humans and agents are both audiences now. Brands that recognize this early will be better positioned than those who treat it as a later problem.
What It Takes to Keep Learning
Rachel closes with something that runs through the whole conversation: a strong, consistent belief in curiosity as the core professional practice.
She traces her own career across AWS, Salesforce, Cisco, and Adobe, and describes a pattern of taking on roles that did not always feel like obvious fits, learning from them anyway, and finding later that the connections became clear in hindsight. For the early-career marketers listening, her advice is this: curiosity, a willingness to experiment, and the critical thinking to ask good questions about what you are seeing will matter more going forward than any specific technical skill.
The knowledge economy is shifting. But the value of people who stay genuinely interested in the world around them stays constant.
