In the past, “digital worker” was a term that referred to a human employee with digital skills. However, in recent years, the market has redefined it as a group of software robots who are trained to complete specific tasks or processes with their human counterparts. Forrester provides the following definition of digital worker automation: “A combination of [intelligent automation] IA building blocks such as conversational Intelligence and [robotic processing automation] RPA that work alongside employees.” They can understand human intent and respond to questions. Then they take action on behalf of the person, giving them control and authority.

Automation sees digital workers in a similar way. They are software-based labor who can independently execute meaningful parts and complex, end-to-end processes using a variety of skills. They use artificial intelligence capabilities such as machine learning, computer vision and natural language processing to complete a series of tasks within a workflow. A digital accounts payable worker might be able to perform part of three traditional jobs — customer service representative and billing agent — to complete an Order to Cash process. Digital workers have been widely adopted as part of digital transformation efforts. This allows companies to shift their workforce to more strategic roles since they increase the bandwidth of their employees.

How to launch a digital workforce

You must consider the human aspect when you are launching your digital workforce. Enterprise design can be used to help you decide how humans should interact with digital workers in order to create an intelligent workflow. The next steps will be helpful:

1. Assess the need. The group should establish a process to allow a digital worker. This stage is where you might want to begin more easily, such as by incorporating intelligent data capture and basic business rules to facilitate better decision-making. You can add complexity slowly.
2. Document the process To properly train digital workers, it is necessary to provide detailed documentation.
3. Training digital workers: Once the process is documented and approved to transfer to a digital worker they will be trained to perform the tasks in the chosen workflow. The bots are trained to flag exceptions and route more complicated use cases to their human counterparts. This allows them to be free from routine monitoring tasks.
4. Evaluate performance: During this step, teams can evaluate the performance of any given digital worker and ensure that it has produced a suitable return on investment (ROI). Teams can use process mining or process maps to validate their training efforts. They can also use this opportunity for identifying bottlenecks and further optimizing the process.

Applications for the Digital Worker

Although digital workers are capable of performing other tasks than digital, they are primarily used for support work in a range of business functions. Some examples include:

• Supply Chain –Retailers such as Amazon are using robots to check stock quantities and prices.
• Human Resources: Bots are able to answer benefits questions in real-time, collect data, and route difficult tasks to subject-matter experts, improving the employee experience at companies.
• Sales and Product Support –Bots are able to answer basic product questions and help customers succeed and sales teams manage existing and prospective clients. They can route customer requests based on urgency. This ensures that high-priority issues are dealt with promptly, which improves the customer experience.

Digital workers face challenges

Although digital workers can improve process efficiency, it is not easy to implement a digital workforce. These are some of the barriers that can hinder your success:

• There are not enough tasks that can be automated, so it is difficult to justify hiring a digital worker.
• Some unstructured data sources may be too complex for technology
• It can be expensive and time-consuming to gather information for documentation purposes.
• If digital workers aren’t designed to be flexible and adaptable, scaling can be difficult