Adobe's AI Agents: A New Way to Boost Your Business
Las Vegas, Nevada, USATue Mar 18 2025
Adobe is known for its Creative Cloud, but it also has a lot more to offer. One of its big tools is the Adobe Experience Platform, which helps businesses create personal experiences for customers, like custom shopping trips. Now, Adobe is making these experiences even better with the help of AI agents.
At its yearly Adobe Summit, Adobe introduced something exciting: Agent Orchestrator. This tool lets users create, manage, and use AI agents from Adobe and other companies within the Adobe Experience Platform. These agents can handle a lot of data and customer journeys to make experiences more personal.
Adobe has rolled out a set of 10 ready-to-use AI agents. These agents can do specific tasks. For example, the Content production agent helps marketers make more content while sticking to brand rules. The Site optimization agent finds and fixes problems on a brand's website to keep customers engaged.
Adobe's data shows a huge jump in traffic to US retail sites from AI sources. This trend is likely to continue as AI becomes more common in how consumers interact with brands. Adobe also introduced Adobe Brand Concierge, an app that uses AI to create better customer experiences. It goes beyond simple chatbots by using customer data and brand details to guide customers through buying.
The Brand Concierge Agent works with other agents to create personal experiences and solve team-specific problems. For instance, it can give customers more than just basic product info. It can personalize responses based on the customer's history and even take actions like setting up a follow-up meeting. This is a big step forward in how AI can help businesses connect with customers.
https://localnews.ai/article/adobes-ai-agents-a-new-way-to-boost-your-business-2c7678f9
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questions
Could the AI agents be part of a larger plan to control consumer behavior and manipulate markets?
What metrics are used to evaluate the effectiveness and efficiency of these AI agents in real-world scenarios?
What measures are in place to prevent AI agents from perpetuating biases present in the training data?
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