5 Digital Workers You’ll be Meeting Soon

5 Digital Workers You’ll be Meeting Soon

Together these digital workers are increasingly taking care of all repetitive, rule-based tasks and freeing humans to tackle the parts of the job that require thinking out of the box, engaging with complex social interactions and performing physical tasks that robots struggle to get right.

by Ryan Falkenberg AI and machine learning are here and working away in a company near you, and on your phone, in your car and in all sorts of plac

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by Ryan Falkenberg

AI and machine learning are here and working away in a company near you, and on your phone, in your car and in all sorts of places online. These technologies are most visible in the workplace in the form of digital workers, who are not a thing of the future but are already here, dealing with clients and handling all sorts of tasks.

If you’ve not encountered one yet, you will soon.

Below we outline five types of digital worker you’ll likely have on your team in the immediate future if you don’t already.

  1. The natural language boff – this colleague is a language specialist, who is able to understand natural language and have a conversation with a person in the language of their choice. Some do this using voice, like Siri, and others do it using free text – like chatbots.
  2. The process navigator – this digital worker makes rule-based decisions and actions in line with all product, policy and procedures and, like the maps apps on your phone, navigates you through the decisions and actions you need to perform in a consistent, compliant and context-relevant way.
  3. The data reader – this digital worker is a specialist at reading information off documents and images and converting it into a format that can be used by the other digital workers to execute their tasks. This is very useful for automating the capture of scanned order forms or pdfs.
  4. The predictor – this cognitive system or algorithm is a specialist in making predictions from data patterns and is very helpful, for example, in determining what your customers will want to buy next based on their purchase history or assessing if they are a fraud risk based on a huge range of possible predictors gleaned off multiple data sources.
  5. The system processor – These workers are specialists in performing system actions; an activity that is often categorised as robotic process automation. They do this using existing system screens, just like a person would do it, only a lot quicker. For example, if you were asked to create a new client account in your CRM, the process you may need to follow is to first look up the account details off a specific spreadsheet and then copy across the details into the relevant fields across different screens in your CRM. Well, your system worker can now do this for you in a fraction of the time while you continue working on more important things – all you need to do is trigger your system worker and off they go.

Together these digital workers are increasingly taking care of all repetitive, rule-based tasks and freeing humans to tackle the parts of the job that require thinking out of the box, engaging with complex social interactions and performing physical tasks that robots struggle to get right.

As a result, this future human-digital worker team are able to do far more, far quicker, and at a lower cost than ever before. Take a rule-bound industry like banking or insurance as an example.

Instead of trying to train staff to perform complex financial need analyses, then be able to identify relevant solutions based on the identified needs, then complete all the processing to onboard the customer and execute the order in line with all the system and process rules, this can now be handled by an integrated human-digital team.

Firstly the language boff can facilitate a free-flowing digital engagement via the client’s mobile or the company’s web page. The questions asked and answers given can be provided to the language boff by the process navigator so they get it exactly right in line with all business rules.

Then when needed, the client can be asked to upload scanned information that the data reader instantly converts to text – information that the predictor then uses to search off multiple sources to complete a credit risk and fraud check.

Once this is done and the client is not found to be a risk, the system processor can then process the order via the relevant internal systems. Once the order is approved, a call can then be triggered in the contact centre where an agent chats to the client to confirm the order has been processed and to provide a warm human closure to the customer experience.

If the customer has any issues or concerns, the process navigator can also help navigate the agent through this so they get it right, every time.

The same applies to work done by technicians or customer service specialists. In fact, any task that is defined by decision-making rules.

In a country like South Africa blessed with high emotional and physical intelligence, augmenting people with a team of digital co-workers who can handle the rule-based logic means we can turn automation to our advantage. If we leverage the machines to do the administrative heavy lifting – like making sure the right questions are asked, the right solutions identified and the right actions are performed – we can allow people to focus more on the customer engagement and the physical implementation of solutions that have been identified.

This can then create jobs for people who are currently unemployable because they lack the technical knowledge and therefore pose a risk to companies who are heavily rule based and regulated. By offering young people access to a team of digital experts who make sure they don’t make a mistake, it unlocks them to start working with less training, less support and less anxiety. And the best part is that this is not a future speak.

It can all be done today using technologies readily available to everyone.

  • Ryan Falkenberg is a co-CEO at CLEVVA

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