The useful question is what changes for users, developers or buyers, and whether the announcement stays industry context or becomes something people can actually use.

Salesforce’s 2026 Agentic Enterprise Index analyzes AI agent usage from February 2025 to April 2026, revealing two distinct deployment strategies: high-volume, task-specific approaches in consumer-facing sectors and versatile, multistep workflows in regulated industries like manufacturing and public services. The average number of agents per organization increased nearly threefold over the past year, with businesses provisioning and activating agents within an average of two days—a process that has accelerated by 53% since the start of the analysis period.

To measure agent productivity, Salesforce introduced the Agentic Work Unit (AWU), defined as one discrete task completed by an AI agent. As of April 2026, AWU output is growing at a 15% compound monthly rate, with consumer-facing industries leading in volume. Retail agents, for example, typically handle one to two actions per agent but manage high volumes of routine tasks, such as order tracking and FAQ responses. Pandora’s AI concierge, Gemma, demonstrates this model by resolving 60% of routine support requests during peak seasons while improving Net Promoter Score by 10%.

Agents are increasingly capable of handling more complex tasks, with the average agent now performing six skills compared to two at the start of 2025. During peak retail periods, agents may act on up to nine skills, a 350% increase, indicating their deployment for multistep customer needs. Agents are also expanding their functionality across cloud domains, such as service agents retrieving sales records or providing personalized recommendations, enabled by headless architectures that decouple logic from front-end interfaces.

Regulated industries like manufacturing, financial services, and public sector agencies are deploying more sophisticated agent networks, as measured by Salesforce’s Sophistication Index. These sectors prioritize complex tasks such as data retrieval, drafting communications, and updating records, despite lower AWU volumes. For instance, public sector and healthcare and life sciences (HLS) AWU output grew 227x and 19x, respectively. PenFed, a federally chartered credit union, exemplifies this trend by using AI agents to navigate compliance and security requirements while handling seasonal demand surges like Tax Day.