What Is a Digital Workforce?

Digital workers are processing 740,000 pieces of customer content, handling 500,000 conversations, and resolving 84% of service cases without human intervention. This isn't a beta test — it's how business gets done today.

Across industries, companies are adopting artificial intelligence (AI) and using AI agents and AI automation in a broader shift towards digital labour that helps teams work faster and smarter. These technologies take on repetitive tasks, surface insights, and coordinate processes behind the scenes so that human teams can focus on what matters most.

From customer service to marketing and sales, digital workers are transforming how work gets done and helping companies stay competitive in a rapidly changing landscape.

A digital workforce consists of software-based systems known as digital workers that use intelligent automation to perform tasks typically handled by people. These systems combine technologies like AI, machine learning (ML), natural language processing (NLP), and robotic process automation (RPA) to streamline work, improve accuracy, and operate around the clock. (Note that the definition of digital workers as remote employees and freelancers who connect via tech is outdated; today's digital workforce doesn't refer to people at all.)

The usefulness of digital workers goes beyond simple automation. While they are designed to take on routine tasks, they can also use AI automation to understand context, analyse data to make a logical decision, and change behaviour based on feedback. That is — digital labour can learn and adapt, whether it's handling structured, rules-based work like data entry or abstract, dynamic work like drawing insights from customer requests.

Digital workers take on work that can slow down human teams, such as analysing high volumes of data or performing repetitive processes. These intelligent systems mimic how people would complete tasks across multiple tools, systems, and steps. By offloading formulaic work to autonomous agents, employees can give their attention to developing customer relationships, creative thinking, and high-impact problem-solving.

It's all possible because of agentic AI, which AI agents use to perform digital labour. They can also learn from outcomes and optimise how they operate, becoming more efficient and effective over time through feedback or algorithms.

Here are some of the areas where digital workforces excel:

Digital workers don't just automate individual clicks or actions — they can follow multiple processes from start to finish, handling tasks in the right order and across the right systems like a human would. That includes logging into applications, copying data between systems, generating reports, and triggering follow-up actions. A global product design and technology company, for example, uses digital workers to power 24/7 self-service, offering instant answers, order updates, and personalised support. It reduces manual workloads while keeping service quality high.

Processes like invoice generation, lead enrichment, case triage, and data population require accuracy, consistency, and speed — especially when done at scale. Digital workers excel at this type of work, completing thousands of iterations in parallel without fatigue or errors. A leading food technology platform uses digital workers to automatically handle complex catering orders, managing dietary requirements and last-minute changes that would otherwise require extensive manual coordination.

Businesses often rely on systems that weren't designed to communicate with each other. Digital workers can operate across cloud and on-premises applications, read screen content, input data, and move between tools without requiring deep integrations or API access.

By combining automation with ML, digital workers can adjust based on outcomes and improve with minimal oversight. For example, they can learn which support cases are more urgent based on customer tier and issue type, how to best route approvals through organisational hierarchies, or which campaign segments drive the most engagement and revenue.

From seasonal spikes in order volume to month-end reporting crunches, fluctuating workloads are no problem for digital workers — they can quickly scale up and down. This flexibility helps teams stay efficient year-round without overstaffing. A premium technology manufacturer deployed and managed a digital workforce during their busiest sales periods to handle thousands of customer conversations 24/7, allowing the human workforce support team members to focus on complex technical enquiries while maintaining response quality.

Digital workers can extract information from spreadsheets, PDFs, email threads, scanned forms, and more. They can tag, classify, and summarise this data or feed it into downstream processes to support decision-making. At Salesforce, for example, Agentforce uses Data Cloud to unify this kind of structured and unstructured data, helping AI agents access what they need to deliver fast, accurate, and relevant responses.

When paired with intelligent automation, digital workers can analyse input data, apply business rules, and make decisions within a workflow. For example, they can flag anomalies in financial transactions, calculate pricing thresholds based on market conditions, or update customer relationship management (CRM) records with new customer insights as they become available. A global talent solutions provider uses digital workers to serve as both recruiter assistants and candidate concierges, analysing candidate data and job requirements to make intelligent matching decisions in real time.

AI agent workforces deliver measurable business results by automating tasks that create bottlenecks and eat up resources. By handling high-volume, repetitive, or rules-based processes, they help teams do more with less, without compromising quality or control. Other benefits of adopting and managing a digital workforce include:

• Time and cost savings: Digital workers perform routine tasks with speed, accuracy, and consistency. They eliminate the slowdowns that come with manual processes, reducing labour costs, minimising rework, and freeing teams from unnecessary delays. Over time, this leads to major savings in both budget and bandwidth.
• More strategic focus for your human workforce: When digital employees take on transactional work, employees can shift their attention to higher-impact efforts. This might include resolving complex customer issues, exploring new market opportunities, or driving innovation from within. The result: more empowered teams and work that aligns more closely with each person's skills.
• Improved employee satisfaction and retention: Repetitive work can lead to burnout and disengagement. Digital workers relieve that pressure by taking on tasks that drain time and energy, helping employees feel more satisfied, challenged, and valued in their roles. Many companies also use these digital colleagues as a springboard for reskilling programmes, giving employees the opportunity to learn and lead in new areas of work.
• Faster, more consistent customer service: AI agent workforces operate 24/7 and respond in real time. They can generate conversation summaries, retrieve relevant information, and assist with common requests, improving both speed and consistency across service channels. And because they follow defined workflows, customers get reliable support every time.
• Scalable operations during growth or surges: Hiring and onboarding new employees takes time. Digital workers can be deployed almost instantly, allowing businesses to scale up during busy periods, expand into new markets, or respond to unexpected shifts in demand. When things slow down, they can scale back without incurring additional costs.
• Better risk management and compliance: Human error is a common source of risk. Digital workers follow precise rules, track every action, and provide built-in visibility for audit or compliance needs. With consistent execution and detailed logs, it becomes easier to spot issues early and stay ahead of regulatory requirements.
• Cleaner, more reliable data: Data fuels every part of a modern business, but only when it's accurate. Digital employees improve data quality by automating validation, removing duplicates, and ensuring information flows correctly across systems. This leads to better forecasting, stronger insights, and more confident decision-making.
• Rapid ROI: Because digital workers reduce costs and boost productivity from day one, many organisations see results in weeks rather than months. They also require less overhead than traditional system changes, making them a cost-effective first step towards broader digital transformation.
• Shorter time to market: With faster internal workflows and fewer manual handoffs, businesses can move from idea to execution more efficiently. Whether businesses are launching a new campaign, releasing a product update, or implementing internal changes, a digital workforce can help them remove friction and accelerate outcomes.
• Stronger automation capabilities: Over time, digital workers help teams build automation muscle. As they learn from data and user behaviour, they can handle more complex work, support more departments, and serve as a foundation for future automation efforts, raising the organisation's overall automation IQ.

What makes digital labour work is a system of automating technologies. Some of these tools handle the basics, like moving data between systems. Others help software to “think” by identifying patterns, making a choice based on historical information, and even understanding language.

Here's a closer look at the core technologies that make it happen:

Robotic process automation (RPA) automates repetitive, rule-based tasks and workflows by mimicking the actions a human would take across systems. It can log into applications, extract and input data, and follow step-by-step instructions without human intervention. RPA provides the essential execution engine for a digital workforce, handling high-volume workloads at scale with precision. This technology serves as the foundation that enables digital workers to interact seamlessly with existing systems and applications.

Artificial intelligence (AI) enables digital workers to perform tasks that require reasoning, decision-making, or pattern recognition. By simulating human cognition, AI helps systems understand which actions to take based on context, whether it's personalising a customer email, analysing sentiment, or selecting the next best action in a workflow. AI powers smarter decisions and context-aware automation, making digital employees capable of handling complex scenarios that go beyond simple rule-following.

Machine learning (ML) allows digital colleagues to improve over time by learning from historical data. Instead of relying on static rules, ML models use collected data to forecast outcomes, such as which leads are likely to convert or which cases may escalate, and help prioritise work accordingly. This creates a self-optimising feedback loop for smarter automation, enabling systems to improve accuracy in predicting outcomes without explicit programming.

Natural language processing (NLP) enables systems to interpret and respond to human language via conversational AI. It powers capabilities like chat summarisation, sentiment detection, and knowledge article generation. With NLP, AI agent workforces can understand requests, extract meaning from unstructured content, and generate responses that feel natural and helpful. This technology allows systems to understand and process human language, making interactions more intuitive and accessible.

BPM platforms coordinate workflows among people, systems, and digital workers. They provide a framework for analysing, managing, and optimising the intelligent automation programme, ensuring tasks are completed in the right order, with the right logic, and that exceptions are handled consistently. BPM serves as the strategic layer that coordinates how all these technologies work together across an organisation.

RPA is an essential component of most digital workforce strategies and is often the first step organisations take towards building one. But RPA alone cannot fully emulate human workflows. A digital worker integrates RPA with other cognitive technologies like AI, ML, and NLP to handle the complex work that simple automation cannot address.

Think of it this way: RPA bots excel at following clearly defined steps for simple, repetitive tasks. But when work gets more complex — involving judgement calls, variability, or natural language — businesses need the intelligent workforce automation that a digital workforce provides.

Here's how the two approaches compare:

Scope and complexity of work:

• RPA bots are built to automate narrow, task-specific actions, like copying data from one field to another, generating reports, or submitting forms. They're fast, consistent, and reliable, but they're limited to simple processes with defined steps.
• Digital workers take on broader workflows that involve multiple decisions, data types, and systems. They can adjust to context, manage branching logic, and support complex, end-to-end processes — not just isolated tasks.

Tech capabilities:

• RPA bots rely on scripts and predefined rules. They mimic what a person would do in a system but lack understanding of the meaning or intent behind the actions.
• Digital workers combine RPA with cognitive technologies such as AI, ML, and NLP to analyse data, make decisions, and understand language. This layered approach allows them to work more independently and intelligently, handling scenarios that require reasoning.

Adaptability and learning:

• RPA bots do not adapt or learn. If something changes, like a field label or system update, they stop working until they are manually reprogrammed.
• Digital workers are built to learn and improve over time with minimal oversight. They use ML to recognise patterns, adapt to changes in real time, and get smarter with each interaction.

Data handling:

• RPA bots are limited to structured data, such as spreadsheets, databases, or form fields with consistent formats.
• Digital workers can also process unstructured content, including emails, PDFs, or chat logs. Using NLP, they extract meaning from language and act on it — unlocking use cases RPA can't reach.

Role in the business:

• RPA bots are most often used in back-office roles, such as finance, HR, or IT, where workflows are repetitive and rules-driven.
• Digital workers support both back-office and customer-facing teams. They help with onboarding, case management, content creation, and more — wherever complex, high-volume work needs to move faster.

Strategic value:

• RPA bots improve efficiency in specific, simple processes. They're a cost-effective and time-saving solution, ideal for eliminating repetitive manual work.
• Digital workers help organisations rethink how work gets done. They make automation more scalable, adaptable, and strategic — helping teams move faster, serve customers better, and build for sustained growth.

Digital workers are already transforming how teams across businesses operate, from sales and service to IT and operations. Agentforce, for example, offers specialised digital employees for service, sales, marketing, and commerce, each designed to integrate seamlessly with existing business processes. Wherever there is manual, repetitive work or time-consuming processes, there's an opportunity for digital workers to help.

Digital workers support sales teams by handling the behind-the-scenes tasks that slow reps down. With sales AI, they can draft personalised outreach emails, surface real-time deal insights, automate activity logging and forecasting, and coach reps based on conversation patterns.

Using AI for customer service, digital workers can deliver fast, consistent support by powering always-on AI agents, summarising customer conversations, creating and updating knowledge base articles, and classifying and routing incoming cases.

Marketers use AI agent workforces to scale campaigns and adapt to changing conditions. With marketing AI, they can build and launch campaign workflows, optimise performance based on key performance indicators, and automatically create customer segments. These systems help marketing teams move from idea to execution more efficiently, whether launching new campaigns or adjusting strategies based on real-time performance data.

In retail, digital workers and AI for commerce improve efficiency across supply and fulfilment by managing inventory and price updates, monitoring supply chain data, and checking stock availability and pricing in real time.

Digital workers are especially effective in IT environments where speed and accuracy are crucial. They can create and manage user accounts, reset passwords, generate utilisation reports, run sophisticated diagnostics, and flag security anomalies.

Digital workers are already providing AI solutions for a variety of industries while delivering consistent benefits. Here are some examples:

• Financial services: Digital workers automate onboarding, compliance, and customer service processes while maintaining regulatory requirements and improving customer experience.
• Healthcare and life sciences: Digital workers streamline patient intake, insurance verification, and medical data entry to reduce administrative burden and improve care delivery.
• Retail: Digital workers support inventory management, dynamic pricing, and customer service to enhance both operational efficiency and customer satisfaction.
• Manufacturing: Digital workers manage procurement, quality checks, and maintenance scheduling to optimise production workflows and reduce downtime.
• Insurance: Digital workers speed up claims processing, policy servicing, and underwriting to improve customer response times and operational accuracy.
• Energy and utilities: Digital workers automate outage management, billing, and field service coordination to enhance service reliability and customer communication.
• Transportation and logistics: Digital workers manage shipments, track assets, and optimise routes to improve delivery efficiency and customer visibility.

Digital workers offer a practical starting point to transform the way business is done. Instead of waiting for major system overhauls, teams can automate routine tasks and connect disconnected tools immediately. A digital workforce jibes with existing systems — even legacy applications — without requiring expensive integrations or months-long implementations.

The employee impact matters, too. Repetitive tasks often lead to burnout within your human workforce. When people see automation making their jobs easier rather than threatening them, transformation feels less disruptive and more valuable. It also provides teams with more engaging work and clearer paths for skill development.

Business needs change fast, and digital workers adapt with them. They can scale up during busy periods, take on new types of work as processes evolve, and provide the flexibility companies need to compete.

The future of work isn't human vs. machine. It's human-AI collaboration, with people and machines working side-by-side to get more done.

Digital workers are not meant to replace people. They're designed to take on work that drains time and energy: the repetitive tasks, data wrangling, and routine handoffs. That gives employees space to focus on what people do best — solving problems, connecting with customers, and driving innovation.

In practice, digital workers act as support systems. They run in the background, coordinating across tools, pulling insights from data, and keeping processes moving. Meanwhile, human teams stay focused on high-impact work that requires empathy, creativity, and judgement. This approach delivers faster service for customers, more engaging work for employees, and stronger business outcomes overall.

This partnership creates better outcomes for everyone. Employees get more interesting work and opportunities to develop new skills. Customers receive faster, more consistent service. And businesses can respond more quickly to market changes without the need for constant hiring or reorganising teams.

More teams are turning to digital workers to take on the parts of work that slow things down. Agentforce makes it possible to build and deploy AI-powered service agents, sales development representatives, and specialised digital workers to help their human workforce focus on the things automation can never replace.