Adobe introduces multimodal AI agents to automate tasks beyond chat

The technology aims to reduce manual work by synthesizing scattered data—such as support requests with screenshots, call recordings, or product manuals—into actionable insights. For example, a retailer could use an agent to analyze a customer complaint paired with a photo of damaged goods, compare it to return policies, draft a response, and flag it for approval. Marketing teams might leverage agents to refine ad campaigns by cross-referencing brand guidelines, performance data, and existing assets. However, Adobe notes challenges: businesses must ensure data quality, security, and governance (e.g., limiting agent access to sensitive actions) to avoid errors or breaches. Costs, complexity, and the need for human oversight remain unaddressed in the announcement, though Adobe suggests starting with narrow, low-risk workflows to test reliability before broader adoption.