An evolving dictionary of Intelligent Automation

When I was actively involved as a researcher, it was a running joke (and also a truism) that scholarly distinction wasn’t earned through originality, but through the invention of new terms to describe old things. The same is most certainly true when it comes to industry jargon. And it’s especially difficult to keep up with terms used to describe the use of artificial intelligence to automate business processes.

The following is a list of common — and frequently confused — terms. This is an evolving field, and in some cases there is still no general consensus around terminology. If you feel a term is missing, or a definition is lacking, please leave a comment below.

Autonomous Enterprise

Sarah Burnett (2022) simply describes an autonomous enterprise as one in which most, if not all, high-volume, repetitive, and transactional business processes that make up core business functions are automated. According to Burnett, key characteristics of the Autonomous Enterprise include:

  • Conducts core, daily business functions using AI, with minimum human touchpoints
  • Employs people who are required to perform few repetitive tasks
  • Empowers staff to automate repetitive tasks for themselves
  • Uses operational data to create digital twins in order to identify inefficiencies and improve processes
  • Analyses operational data to support strategic decisions, including risk management and innovation

Autonomous Operations

Most commonly, the term is used to refer to the operations of vehicles, heavy equipment and physical robots in ways that make use of webs to sensors and AI in order to automate things like transportation, manufacturing, mining, agriculture, and the like.

For the sake of clarity, I would recommend the term ‘Autonomous Business Operations’ to describe the use of AI to automate decisions, actions, and self-learning in the business process domain.

Decentralized Autonomous Organization (DAO)

Decentralized autonomous organizations (DAOs) are blockchain-based organizations fed by a peer-to-peer (P2P) network of contributors. Their management is decentralized without top executive teams and built on automated rules encoded in smart contracts, and their governance works autonomously based on a combination of on-chain and off-chain mechanisms that support community decision-making.

Santana & Albareda (2022) Blockchain and the emergence of Decentralized Autonomous Organizations (DAOs): An integrative model and research agenda


Hyperautomation is not a thing or a specific set of technologies. Instead, it is an organizational mindset according to which everyone is automating everything that can be, all the time.

Intelligent Automation

While many definitions would tie the term Intelligent Automation explicitly to particular kinds of technology (i.e. as the combination of Business Process Management (BPM), Artificial intelligence (AI), and Robotic Process Automation (RPA), I prefer the more common sense and technology-agnostic definition proposed Coombs, et al (2020): “the application of AI in ways that can learn, adapt, and improve over time to automate tasks that were formally undertaken by a human.”

Virtual Enterprise (VE)

A virtual enterprise (VE) is a temporary alliance of businesses that come together to share skills or core competencies and resources in order to better respond to business opportunities, and whose cooperation is supported by computer networks. (Wikipedia)

Bots don’t care if you live or die

The best approaches to automation don’t automate everything. Where processes are automated, exceptions are bound to happen. And when those exceptions happen it’s important that humans are able to address them…especially when the life and death of humans are concerned.

When too much is automated, humans lose skill and vigilance. They become less responsive and less capable when things go badly. It’s for this reason that responsibly-built airplanes automate less than they can, and in fact intentionally build friction into their processes.

A bot doesn’t care if we live or die, succeed or fail. That’s why a robust approach to hyperautomation must consider, not just whether a process CAN be automated, but also whether and the extent to which it SHOULD be.

Hyperautomation is necessary to human survival

As a result of digitization (converting analogue to digital information) and digitalization (deploying processes that make use of digital information) congnitive load has INCREASED, not decreased.

The speed that information travels today means that just being able to keep up is a competitive advantage. But the result for humans is more communication channels, more meetings, and more demands. Burnout is a real thing. I’ve seen people change jobs as a way of declaring ‘email bankruptcy’ — they have become so under water and so overwhelmed that the only way to escape is to leave their job entirely and start fresh somewhere else.

Hyperautomation is not a technology. It is a change in culture where everyone is empowered to automate anything that can be. The democratization of software development made possible by no-code and low-code platforms is vital to realizing that vision.

Hyperautomation is most frequently cited as a solution to business problems. And it is. But it is more importantly the solution to a very real HUMAN problem: how to survive and thrive in the face of digital transformation.