The Index leverages AI usage data from a cohort of businesses, powered by Salesforce’s own proprietary data, to provide a first look at how companies are implementing agents, the value they’re starting to unlock, and the progress they are making toward becoming true agentic enterprises.
Over the past year, leading organizations are moving beyond building AI agents to deploying full agentic workforces — ones that work alongside humans to drive real business outcomes. The Salesforce Agentic Enterprise Index (Second Edition) captures this shift in action: drawing on usage data from the world's #1 Agentic CRM, it reveals how enterprises are scaling autonomous agents across every team and workflow — moving from proof of concept to measurable ROI at production scale.
Powered by Agentforce and other Salesforce products, Salesforce analyzed and aggregated usage data of a cohort of businesses to uncover the true story of agents in the workforce. Looking at trends from February 2025 to April 2026, The Salesforce Agentic Enterprise Index analyzes the activity and engagement of real businesses leveraging the power of AI agents to drive ROI. To qualify for inclusion in the dataset, businesses needed to have activated agents in production every month across the analysis period. These results are not indicative of Salesforce performance.
Additional data was sourced from Salesforce’s global proprietary research studies totaling 4,689 responses in May 2026. Survey audiences include the USA, UK, France, Canada, Australia, Spain, and Italy
A major transformation is underway as businesses create and scale their agentic workforce. Businesses scaled their agentic workforces from an average of 5 activated agents in February 2025 to 13 by April 2026—growing agent production nearly 3X at a 7% compound monthly growth rate.
The data also showed that it takes businesses on average 1.9 days to create an agent, decreasing 53% since February 2025.
Once activated and in use, agents progressively take on more work. The average actions per account has increased by a Compound Monthly Growth Rate (CMGR) of 31% in the last 15 months.
Agents are moving from simple tasks to handling autonomous, multi-step workflows. The average number of unique skills that each agent is able to act on rose from an average of 2 at the beginning of 2025 to 6 by the end of the year as seasonal demand grew in industries like Retail and Financial Services. When demand for agents is highest, each agent takes on triple the capability to support businesses.
Serving military families requires navigating strict compliance, security, and verification across every touchpoint.
Not only is the volume of unique skills rising, but agents are increasingly taking on secondary functions. For example, service agents are taking commerce and marketing actions, expanding the versatility of what they can do for customers and businesses. The data shows that employees are growing more confident about which actions they can entrust to agents, and agents are also acting on those tasks when conversations call for it.
The "Action-to-Output" ratio is growing at a 15% Compound Monthly Growth Rate (CMGR). This means agents are triggering external business logic rather than just generating text. This ratio increases during times of seasonal demand.
As employees increasingly hand off complex tasks to AI agents, Salesforce developed a new way to measure that activity: the Agentic Work Unit (AWU). An AWU represents one discrete unit of work completed by an AI agent — a task reasoned through, a decision made, an action taken. As of April 2026, Agentforce agents produced 734M AWUs - increasing by 15% month-over-month. As of April 2026, Agentforce agents’ AWU output is increasing by a 15% CMGR (compound monthly growth rate).
Employee engagement is deepening, with workers continuing to go back to agents each month. The average employee user tripled their AI agent interactions over the analysis period.
Slackbot, Slack’s built-in agent, became generally available in February 2026. Users are averaging 68 sessions per week with Slack agents alone since general availability.
Leveraging agents creates tangible results with customers. Retailers that deployed AI agents during the holiday shopping season saw a 4X higher sales growth rate.
Even as the share of customer service sessions handled by agents increased by more than 170-fold over five quarters, the rate of autonomous resolutions stayed steady. Proving that agents can scale without degrading the customer experience.
After they deploy AI agents, customer service organizations report that the #1 improved KPI is customer satisfaction — ranking ahead of service rep productivity, average handle time, customer retention, and first-response time.
After deploying AI agents, customer service organizations report that the #1 improved KPI is customer satisfaction — ranking ahead of service rep productivity, average handle time, customer retention, and first-response time.
Agents have built trust among shoppers - increasing their confidence in purchase decisions through trusted recommendations.
77% of shoppers that engaged with on site branded shopper agents feel more confident with their purchase
74% of shoppers trust the recommendations they receive from AI agents/agentic search
Consumer industries like retail and travel tend to deploy agents faster and at a higher volume. Non-traditional ‘AI’ or tech industries like healthcare and manufacturing are more deliberate about their deployments, leveraging fewer, but more sophisticated agents.
Consumer industries dominate AWU output, with agents in those industries representing nearly a third of total monthly AWU output across all agents.
The Retail & Consumer Goods and Travel sectors are using agentic technology to help scale to the end of year demand swings in particular, showing 100k+ average actions per account by the end of the analysis period with a nearly 60% surge between Nov 2025 and Jan 2026.
Global jewelry brand Pandora faces dramatic surges in customer inquiries during peak shopping seasons like holidays and Valentine's Day. To maintain its high-touch, personalized experience during these high-volume moments, Pandora deploys Gemma — an AI concierge powered by Agentforce. By connecting directly to back-end order systems and product catalogs, Gemma delivers fast, personalized support at scale. During peak traffic, Gemma handles 60% of routine support requests while driving a 10% increase in Net Promoter Score (NPS), enabling human reps to focus on high-touch, complex interactions.
Regulated industries like Healthcare & Life Sciences put out a more modest monthly AWU number, but grew significantly over the analysis period.
To gauge the complexity of agent usage across industries, we established a "Sophistication Index" by mapping all agent actions into 5 progressive tiers of cognitive complexity:
By evaluating how many of these complexity levels agents in each industry actively use, the Sophistication Index highlights who is leveraging agents to take on a variety of complex tasks rather than just automating high volume tasks.
The analysis reveals that operationally complex, highly regulated fields build more advanced agent networks than traditional tech sectors.
Driven by these intricate multi-step workflows, Healthcare & Life Sciences, Financial Services and Manufacturing outpaced Technology and Retail on the index, scoring 66% higher (40-50 vs. 30).
Businesses can build a more versatile, interconnected digital workforce by trusting agents to take on adjacent responsibilities outside their original scope.
Particularly in consumer industries, agents support growth during particularly busy times (holiday, tax season, etc)
The data shows employees are engaging in more sessions with agents than ever before, particularly in channels they use throughout the day.
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