The AI Workforce: What It Is and How It Can Help Your Team

Executive summary:

• AI agents are becoming digital teammates by handling routine tasks, surfacing insights, and boosting productivity. This frees human workers to focus on strategic and creative work.

• Organizations should start by mapping workflows if they want to build an effective AI workforce, and by continuously testing, training, and refining collaboration between humans and AI.

The future where humans work alongside digital teammates powered by artificial intelligence (AI) is here. In these early days of the digital workforce era, AI has already shown how it can make the work humans do much easier and more effective.

For example, intelligent AI agents can process data, make decisions, and take action autonomously. These digital workers can take on challenging tasks without human supervision.

These powerful tools aren’t just removing tedious work from workers’ plates; they’re helping their human counterparts be more productive. For example, workers can ask AI agents for complex information using plain language and get instant, accurate answers rather than having to conduct time-consuming searches.

Let’s take a closer look at how the AI workforce is developing, how it meshes with human talent, and how its adoption can optimize your team’s work productivity.

What is the AI workforce?

The AI workforce represents a new digital labor force of autonomous AI agents that can analyze information, make decisions, and take actions to achieve specific goals. These AI agents function as digital teammates that augment human workers rather than replace them, operating independently within defined digital workspaces to handle routine but necessary tasks like updating CRMs, compiling reports, and managing approvals. 

For example, if a person reaches out to customer service through a chat window on your website, an AI agent could respond with natural language and quickly find the links, files, and tools they’re searching for.

The AI workforce uses machine learning to recognize patterns in user behavior and data. It then takes that knowledge, applies automation, and becomes more efficient. It takes over rote tasks from human teammates and serves up information that helps people make better-informed decisions more quickly. 

The results are already being felt across industries. According to our State of AI Agents report, people who work with AI agents are 72% more likely to say they feel very productive at their jobs. Another 62% say their roles are becoming more strategic and creative since they’re not bogged down by the repetitive and low-skill tasks that AI agents can manage.

Steps for building an effective AI workforce

The abilities of AI agents are growing at a significant rate, fundamentally changing how we work. In order to reap those benefits, however, you will need a framework to build your AI workforce. 

1. Document all important tasks and workflows

Start by evaluating all your workflows within and across teams. For example, in a client-services business, workflow steps might include:

• Once a sales rep wins a deal, a contract is generated to be signed.
• A project coordinator opens a new project, creates and assigns tasks, and updates the schedule.
• As work is completed, contributors upload to a platform for feedback.
• The work is delivered to clients, and an invoice is generated and sent.

Tasks like scheduling meetings, reporting, or analyzing data can easily be handled by AI. Have each team look at its processes, deconstruct them, and map out each task. 

2. Prioritize automations based on real needs

Weigh this process documentation against your team’s needs and frustrations—especially those with a tangible cost. For example, you might find your customer service team can’t quickly find technical product information needed to resolve cases. AI agents can find the relevant  documentation in a fraction of the time, helping their human counterparts close tickets much faster. Meanwhile, those same AI agents can deflect tickets altogether by surfacing information from the company’s knowledge base, thus giving customers an opportunity to self-serve. 

3. Find the AI tools that fit your identified needs

Now that you’ve identified tasks that are feasible and important to pass off to digital workers, you can start shopping for AI-powered tools that can handle them. Returning to the customer service example, reps could use an AI-powered enterprise search that’s trained on proprietary company information to get accurate summaries of technical details and ask follow-up questions. They can then quickly pass along the information to the customer.

Keep in mind that whichever tools you have should also be able to integrate with your existing tech stack you already use. Look for a solution that makes AI a true digital teammate, such as Agentforce in Slack. Agentforce accesses your team’s history of chats, files, and workflows so it can immediately handle tasks correctly.

4. Test and assess the AI tools

Once you have one or more AI tools that meet your requirements, it’s time to test their ability to automate your workflows. During your assessment period, note the following:

• How well did the AI perform the task you gave it in general?
• Were human workers easily able to understand when AI could handle a task for them?
• When and how often did the digital worker require human intervention?
• How did workers feel about AI and its performance in the roles it was assigned?
• If the AI interacted with customers, was it able to resolve their issue without escalation to a human worker?

5. Review and re-evaluate

Be sure to continuously monitor the performance of digital workers, and request regular feedback from human workers to find gaps, inefficiencies, and new opportunities for automating. Part of reskilling the workforce is making individual contributors into effective managers of the AI they use. 

Whatever the final mix is, your AI workforce will need to balance human and AI collaboration. People should still handle tasks that require higher-order decision-making (such as ethical issues) or the personal touch of a human, like when a customer is highly frustrated. Take advantage of AI assistants to automate low-value tasks, deliver real-time insights, or handle routine communication inside platforms like Slack.

Types of AI agents in the workplace

Not all AI agents are the same. Their quality varies, and their capabilities are grouped into several categories. Here are some of the most common:

Reactive agents

Reactive AI agents respond to current situations based on pre-defined rules. They don’t have “memory” or learn from their past interactions, but they are efficient at their one task. 

An HR team might use a reactive AI agent that generates personalized onboarding paperwork in response to a new hire’s start date approaching. The HR team saves time on paperwork so they can give individualized attention to the new hire’s needs, and the hiring manager gets assurance that no forms are missed that prevent the new hire from starting on time. 

Predictive agents

Predictive AI agents can analyze data and surface insights to help humans with decision-making. In a healthcare setting, for example, predictive AI agents can calculate the likelihood of patients being re-admitted using health records, which can be used by staff to schedule preventative follow-up appointments. By performing analysis at a massive scale, these predictive agents can help their human counterparts reduce unnecessary follow-ups while putting the focus on patients that need care the most.

Autonomous agents

Autonomous agents use agentic AI and have the ability to process, make predictions, and act on the input they encounter. They still require human oversight to monitor the accuracy of their learning and behaviors, but they can perform tasks independently. 

In a customer service setting, an autonomous agent could resolve issues by sharing documentation from a knowledge base or quickly surfacing a solution based on similar resolved tickets. This represents the ability to fully augment many human workloads, allowing low-level tasks to be offloaded as they provide the high-touch service customers demand. 

How to create AI agents that work for you

Whether you’re looking for an AI assistant for your team or building your own agent in Slack, AI can be tailored to fit your organization’s needs. Look for these key AI workforce features:

• Conversational fluency: At a baseline, whatever AI agent you choose should include conversational AI. This tool uses natural language processing so that humans can instruct and collaborate with it without specialized commands or coding. That is, they can talk to it like they would another human and reasonably expect it to interpret that input and provide the expected output.
• Contextual awareness: Your AI tool should be trained on your company’s proprietary data and complete tasks based on your organization’s context. For example, Agentforce internal agents have built-in contextual awareness of the Salesforce record a user is currently viewing, and it can deliver personalized answers and take action on behalf of users without requiring them to provide additional context. And by using machine learning for advanced pattern recognition, AI should seem to get “smarter” as it more ably surfaces content, performs actions, and even suggests more automations and workflow efficiencies.

Use case: Train AI for specific tasks

Building on the concept of roles, context, and memory, let’s look at how you could train an AI for specific tasks using the example of Agentforce in Slack:

1. Select an agent from a template, such as the Slack Employee Help template. This sets up an AI agent that can help with HR, IT, marketing, and more.
2. Use natural language inputs to define its general behavior and tone as it interacts with employees.
3. Choose data sources for the agent to operate from, such as specific channels, external knowledge bases, and cloud drives. This will ground its answers and keep it on topic.
4. Configure your agent with specific actions that help it perform its function. For example, you might allow it to share files from employee document libraries or fill PTO requests in a form that connects with Slack.

 

Best practices for digital workers

While just about every major piece of workplace software has some type of AI functionality grafted on, generating separate, decontextualized reports in 10 apps is not a meaningful digital labor workforce. Follow these best practices to unlock your AI workforce:

• Add AI in your main workspace. Choose a tool that lets you enable AI agents in your work operating system, like Slack, so it can be integrated with the other tools your team works with.
• Set clear expectations. Set up instructions for the AI and expectations for humans—which tasks AI handles and which ones humans take care of.
• Build trust in automation. Start with simple workflows, then add functionality as you go, training leaders to train their teams. 
• Involve teams in ideation and iteration. AI isn’t a switch you can flip. It has to be built upon, trained, and experimented with. Give teams the freedom to suggest places where AI can help, and solicit their feedback. AI exists to help them, which helps the business.

 

Start building your AI workforce

Just as computers, the internet, cloud services, mobile devices, and social networks all became important factors in running a modern business, AI agents are no different. They can help your business scale, improve efficiency, and give your human employees room to focus on more creative, impactful work. 

Follow the process: identify easy-to-automate tasks, get feedback from your team, select the right tool, and then test and revise as needed. Remember, an effective AI workforce includes AI agents that have conversational fluency and contextual awareness—and don’t forget to build on a solid foundation that supports native agentic AI.