Salesforce published the AI Fluency Playbook, a technical guide designed to assist organizations in preparing their workforce for autonomous agent collaboration. The document establishes a framework to equip employees with the necessary competencies for scalable and efficient human-agent workflows.
The transition toward agentic operational models requires a profound structural reconfiguration of corporate and technical culture. “When we achieve AI fluency, AI moves from a technology innovation to a workforce advantage: it is the difference between deploying tools and actually changing the way work gets done,” says Nathalie Scardino, President and Chief People Officer, Salesforce.
The emergence of the “Agentic Company” responds to the requirement for productivity optimization through autonomous systems that execute complex tasks proactively. According to Salesforce, daily use of AI correlates with a 64% increase in productivity, a 58% improvement in focus, and an 81% rise in job satisfaction. In this environment, AI fluency is a growth driver that facilitates the recruitment of specialized talent and improves business performance.
Adoption of these technologies requires an evolution in soft skills and cognitive abilities. Ali Bebo, Chief Human Resources Officer, Pearson, emphasizes this necessity for reskilling, noting that “today is all about learning agility: human skills like learning, adaptability, communication, and critical thinking are fundamental for the age of agentic AI.”
The AI Fluency Playbook is based on the internal implementation at Salesforce as “Customer Zero” for its Agentforce platform. During the previous year, the integration of AI agents within Slack resulted in a savings of 500,000 hours for staff, says the company. Furthermore, the Engagement Agent processed 190,000 leads in coordination with the sales department, while the Service Agent managed over 2 million support requests for the customer service department. These metrics have increased employee confidence in using AI tools to 85%, representing a 16% year-over-year increase.
To institutionalize this competency, the guide proposes a development model based on three organizational pillars. The first pillar, AI engagement, focuses on improving employee perception and technical trust to mitigate resistance. By fostering a positive environment, organizations ensure that staff view automated systems as collaborators rather than replacements.
The second pillar, AI activation, establishes protocols to drive the consistent adoption of these tools within daily work streams. This stage transitions AI from a conceptual resource to a functional component of the operational routine. Finally, AI expertise involves developing specific competencies that integrate human skills with agentic capabilities and business goals. This integration is essential to optimize the human-agent dyad and maximize the strategic value of the workforce.
Organizations that adopt these frameworks are expected to achieve superior operational autonomy. This would allow the workforce to move away from transactional tasks to focus on strategic functions and complex decision-making. Scardino says that when AI is utilized with mastery, it increases employee autonomy by providing individuals more control over how they work, decide, and create value.