{"id":67369,"date":"2025-06-02T07:50:00","date_gmt":"2025-06-02T14:50:00","guid":{"rendered":"https:\/\/www.salesforce.com\/?p=67369"},"modified":"2025-06-30T09:50:20","modified_gmt":"2025-06-29T23:50:20","slug":"ai-workforce-management","status":"publish","type":"post","link":"https:\/\/www.salesforce.com\/au\/blog\/ai-workforce-management\/","title":{"rendered":"How To Lead in the Age of AI Agents"},"content":{"rendered":"\n

AI agent adoption is expected<\/a> to jump 327% over the next two years.<\/p>\n\n\n\n

While we let that statistic sink in, let\u2019s put it another way: AI agents<\/a> will soon be everywhere, embedded across every business function, in every industry.<\/p>\n\n\n\n

If you\u2019re a manager, this means you\u2019ll no longer just be leading people \u2014 you\u2019ll be overseeing a blended workforce of humans and<\/em> artificial intelligence<\/a> (AI) agents. You\u2019ll need to build on your existing skills and develop new ones, to make sure that your digital and human employees are working collaboratively to their full potential.<\/p>\n\n\n\n

What does AI workforce management look like? What skills will you need and what measures should you take to manage a workforce that\u2019s part human, part machine, and all high performance? Let\u2019s take a look.<\/p>\n\n\n\n

Address employee concerns early <\/h2>\n\n\n\n

If you\u2019re adding an AI agent to your team, you\u2019ve already thought about its role and the tasks where it could be most efficient: highly repetitive or high-volume tasks like scheduling appointments, answering basic customer inquiries, processing transactions, or analyzing data. You might have also identified workflows where an agent could help make humans more successful \u2014 for example, adding an agent that provides real-time information to a rep during a customer call.<\/p>\n\n\n\n

But during this planning stage, you should also be paying attention to your employees. It\u2019s crucial that you openly address their anxiety about job displacement \u2014 and do so early in the process. As new research<\/a> from Slack puts it: \u201cIn a world where [AI] agents could outnumber employees, \u2026 managers will need to become facilitators and coaches, helping their teams navigate the new landscape of work and maximize the potential of AI tools.\u201d<\/p>\n\n\n\n

Look for opportunities to upskill team members for roles that will become critical in an AI-driven workplace, and that take advantage of uniquely human qualities like creativity, judgment, and critical thinking. By investing in and supporting upskilling, you can build trust with employees by showing you\u2019re committed to their growth. <\/p>\n\n\n\n

Salesforce offers a great example of this type of support. In addition to ongoing departmental AI training, the company hosts a quarterly Agentforce Learning Day<\/a>, where employees learn how to use AI tools and integrate them into their daily tasks, and skill up on Agentforce<\/a>, the platform for building AI agents. <\/p>\n\n\n\n

\u201cWe know from years of studies that the more engaged someone is with their work, the more engaged they are with the company,\u201d said Jenny Simmons, VP of onboarding and employee learning at Salesforce. \u201cAnd the better their work is, the better customer experience we create.<\/p>\n\n\n\n

\u201cThis is about building capacity for humans. It\u2019s about the evolution of the job to a new place.\u201d <\/p>\n\n\n\n

Adjust your onboarding strategy for AI agents <\/h2>\n\n\n\n

Forget the welcome packets and water cooler chats: Integrating an AI agent into your workforce demands a different approach. Here are some key distinctions:
<\/p>\n\n\n\n

Configuration vs. training <\/h3>\n\n\n\n

Unlike onboarding humans, which involves an extended period of training and development, bringing an AI agent onto your team is a more technical process. You\u2019ll need to configure it with the necessary data, workflows, permissions, and contextual knowledge so it can perform its tasks effectively. <\/p>\n\n\n\n

Precision vs. interpretation <\/h3>\n\n\n\n

Humans can understand nuance and ask clarifying questions, while an AI agent relies on clearly defined parameters. If those aren\u2019t in place, it can produce nonsensical answers, or hallucinate. Be very specific about how the agent should handle unexpected situations,  or edge cases, and define when it should hand off a task to a human. 
<\/p>\n\n\n\n

\"\"\n\t\t\t\n\t\t\t\t\n\t\t\t<\/svg>\n\t\t<\/button><\/figure>\n\n\n\n

Monitoring vs. managing <\/h3>\n\n\n\n

AI agents don\u2019t need motivation or feedback in the traditional sense, but they do need monitoring. Put systems in place to track performance, spot problems, and identify when human intervention is needed. Key performance indicators (KPIs) will likely be different for AI agents and humans. For example, an AI agent can handle a much greater volume of customer service cases, faster, so expectations are higher. <\/p>\n\n\n\n

Must-have skills for AI workforce management<\/h2>\n\n\n\n

Getting the most out of your blended workforce entails using the managerial skills you already have, and building some new ones.<\/p>\n\n\n\n

Communication and delegation <\/h3>\n\n\n\n

While AI agents don\u2019t have emotions, working with them requires clear communication, thoughtful delegation, and alignment with strategic goals. In fact, you may find that some of the skills you already use to manage people can be extended to agents. <\/p>\n\n\n\n

For example, setting expectations and boundaries. With humans, you define the job description, performance targets, deadlines, and project scope. With agents, you also define those things, as well as data sources, output formats (such as spreadsheets, videos, pie charts, or social media posts), and guardrails for escalating thorny or sensitive situations. <\/p>\n\n\n\n

And just as humans benefit from regular check-ins and performance reviews, agents need oversight to make sure they’re working correctly, achieving goals, and adhering to guidelines.  <\/sup>This lets you make adjustments, correct errors, and optimize their performance.<\/p>\n\n\n\n

AI and data proficiency <\/h3>\n\n\n\n

As you add agents to your team, you\u2019ll likely need to step up your tech skills, particularly around data: how it powers agents, how to interpret and act on performance dashboards, and more. <\/p>\n\n\n\n

\u201cTechnical skills will be more important, including a deep understanding of agentic AI<\/a> and data literacy,\u201d said Simmons. You\u2019ll need to understand and shape the data environment that drives your digital workforce to make sure your agents are effective and reliable. This may include: <\/p>\n\n\n\n