Adobe Summit 2025 - a week when agentic AI took center stage. Here's why

Some people and companies may wonder if agentic AI is all hype, but there are already some interesting applications in the tech industry—Adobe is no exception.

Amit Ahuja, SVP of Experience Cloud, Platforms, and Products, Digital Experience at Adobe, walked me through the firm's new Experience Platform Agent Orchestrator and several of the new Experience Platform Agents to demonstrate how Adobe is embedding agentic AI throughout the Platform.

Adobe’s AI journey

If you follow Adobe, you know it’s been on a journey to use AI to transform its products and platform for many years now, with generative AI being the newest AI capabilities. Last year, it introduced the AI assistant, which enabled conversations over enterprise data. However, Adobe’s customers want more than a Q&A. The aim is that AI takes on and finishes complete tasks and does them smarter and faster. This is where the Experience Platform Agents and agentic reasoning come in.

First, let’s understand how Adobe defines an agent because, let’s face it, it means different things to different companies. In Adobe’s case, an agent is:

• It’s interactive. It engages in a two-way conversation with a human and understands and responds to input in real time.
• It reasons. Adobe agents go beyond pre-programmed rules. It understands context, interprets user intent, and reasons through complex problems. And it makes decisions. The agent has learned from the company’s enterprise data and the knowledge base.
• It’s autonomous. It can take action instead of only providing high-level guidance or explicit insights. It can execute tasks, automate processes, and make changes to systems or content.

Adobe’s agent orchestration works within the Adobe Experience Platform, co-ordinating the actions of one or more agents. Ahuja says the firm looked at where the bottlenecks were for marketers and focused the agents on more complex use cases. It also works across the broader ecosystem. Adobe is committed to agent interoperability and helping others extend and customize experiences and workflows based on their specific needs.

Three pillars of Adobe’s agent strategy

Ahuja pitches the three pillars of Adobe’s agent strategy as:

(1) Helping practitioners do more

Streamlining tasks, automating processes, and providing intelligent recommendations are ways the agents work for practitioners. Ahuja talks about Audience Agent, Journey Agent, and Experiment Agents, all of which create, optimize, and manage the audience, journey, or experiment. The agents work on a combination of fine-tuned LLM and Adobe’s proprietary knowledge.

The Audience Agent can be used to create a new email campaign. The agent is prompted with a goal and responds with options and a plan. It can recommend a new audience or suggest an existing audience based on inputs from the marketer. It can do propensity modeling and predict how much of that audience is likely to convert. The agent works with connected datasets, including the CDP, customer journey analytics, and more. At every point, the marketer has the ability to select the audience, request changes, move forward, or even move backward and have the agent re-evaluate.

At every decision point, the agent clearly explains its reasoning and recommendations, including the data sources used, how the model was trained, and what factors drove predictions.

Ahuja says the core constructs of agentic reasoning—planning, verification, and backtracking—are built into all agents. He said it is necessary for humans and AI to work together.

(2) Transforming customer experiences

This pillar focuses on helping marketers create engaging, personalized customer experiences using agents. The Brand Concierge (Phil Wainewight talks about this here) is an example of an agent in this pillar.

There are two parts to the Brand Concierge agent. There’s the setup of an experience and the delivery of that experience to the customer. The marketers defines a goal and based on connected data the agent recommends strategies and content. It can also create the experience, both visual and content, following brand guidelines, and it can personalize the experience of customers using known information. The marketer can adjust what the agent creates at every point. The second part is the actual delivery of that experience - a virtual assistant (agent) the customer uses to help them do something. The example provided here was a virtual assistant that helped a customer customize their vacation trip.

(3) Enabling the ecosystem and developers

Adobe provides APIs and tools for developers to create their own agents and interoperate with the Adobe agents. The Adobe Marketing Agent is a great example. It integrates with Microsoft 365 Copilot and is available in applications like Word, Teams, and PowerPoint, essentially embedding Adobe marketing capabilities directly into the 365 workflow.

For example, after a team meeting for a new campaign, inside Office 365, a marketer can request that the Marketing agent draft a creative brief, provide audience recommendations, suggest content, and create a project workflow in Adobe Workfront. And the agent can do this by analyzing the transcript, and integrating with the necessary Adobe applications. Marketers can be in Office Copilot during and after the campaign and request performance reports, analyze journey data and recommend improvements, and draft PowerPoint presentations for reporting.

Coca Cola’s journey into agentic AI

Rapha Abreu, VP of Global Design, and Shekhar Gowda, VP of Global Marketing Technology at The Coca-Cola Company, joined Ahuja to share some insights on Coca-Cola’s AI journey (Madeline Bennett's write-up of the session can be found here). Ahuja said the company has some of the most agile thinking about implementing AI.

Abreu’s design team is responsible for ensuring the brand storytelling remains iconic worldwide, balancing timelessness with timeliness across every touchpoint. So, his job is to develop brand guidelines that define how global brands should look or visually behave worldwide. When generative AI came in, they were in the process of shifting from static to more dynamic guidelines. But they needed to do more. They needed a design system that allowed for creative flexibility to support a global presence but infused local relevance but remained consistent with the brand.

Brand consistency is paramount for us, and the more we scale, the greater is the risk of misinterpretation of brand guidelines that can lead to loss in brand fit and ultimately a bad quality execution. [...] We needed an AI-enabled system that didn't just replicate designs, but deeply learned and truly understood what makes Coca-Cola look and feel like Coca-Cola, right?

That’s what Project Fizzion does. Powered by Firefly services and a custom model, Project Fizzion lets designers create intelligent, dynamic design systems from original designs. Designers create their layouts in Adobe Creative Cloud, Fizzion learns everything they are doing and codifies it into a new style ID and applies it across different applications of the design. The agent isn’t replacing designers; it’s ensuring their vision is fulfilled, executing it across potentially thousands of applications.

Gowda said scaling is important for the company, but it was essential to do it in a way that maintains the integrity of the brand across everything. He also doesn’t believe that AI replaces creativity - it enhances it. Coca-Cola believes in a human-led approach where designers lead, and AI follows.

Another interesting point Gowda made was o emphasise the truism that AI is not a silver bullet. You must start with a clear problem to solve and define AI’s role carefully.

My take

What I saw related to Coca-Cola's use of AI and design was interesting, and the way the Audience Agent reasoned out and built a new audience was pretty cool. But, the Marketing Agent embedded in the Office 365 CoPilot caught my attention the most.

As companies start to dive into using agents and tech providers build agents on top of their products and platforms, it’s the interoperability that I haven’t seen much of yet. That’s partly because the tech providers are still trying to figure out how to create agents that work within their own systems. And some are creating multiple agents that don’t talk to each other. Trying to figure out how to design them to talk with agents outside their ecosystem is a bigger, broader initiative.

Adobe is there, working with partners like Microsoft to build interoperability between systems and agents. Plus, you’re working with an agent in line with the tools you use every day. You don’t have to move between tools to get work done - that is a key productivity hack. Tech providers can build all the agents they want, but if they are still requiring multiple interfaces and multiple agents that don’t talk to each other, they’re missing the point.