AI, Intelligent Automation and Their Impact on the Enterprise

3 minute read

Let automations do the mundane work and find more effective ways to get it done. This will free your human workers to do more creative and important tasks.

A word to the wise: You should not use the terms chatbot, Artificial Intelligence (AI) and intelligent automation interchangeably. These are vastly different technologies that serve various purposes, but market hype leads many enterprises to think there is little disparity between them.

Unfortunately, many vendors claim to provide clients with AI and intelligent automation, when they’re merely providing chatbots. We’ve written at length about the differences between chatbots and AI
— and put simply, chatbots do not apply human thought processes to solving problems, as they only follow pre-programmed scripts. Conversely, AI and intelligent automation use cognitive intelligence, machine learning and collaboration with humans to make on-the-fly decisions.

This brings us to the focus of this piece, which is the difference between AI and intelligent automation, and how they can deliver real business benefits, both separately and collectively.

AI allows software to learn and use acquired knowledge to make decisions and complete tasks. For example, a digital colleague assigned to a customer service role can access inventory data to help customers make informed decisions about products. The cognitive software processes a request, uses its intelligence to find information, and makes a judgment about which information best applies to a resolution. AI can learn from interactions to provide customers with faster service, handle multiple questions in one conversation, and use dialogue to help customers find exactly what they need. In other scenarios, AI can learn when customers are most likely to answer emails and recommend specific times for sales teams to contact them. Or AI can process upcoming traffic and use real-time information to recommend the best route for delivery drivers.

The combination of automation and Artificial Intelligence (AI) is what’s known as intelligent automation. Whereas AI is able to watch, interpret and learn business processes, intelligent automation is able to repeat these processes over and over so that humans don’t. By adding AI’s ability to learn processes and apply knowledge in an appropriate context with the ability to repeat processes at scale, businesses are able to reduce the amount of manual labor delegated to repetition. In other words, to build upon an example of physical automation: Companies have taught machines how to build cars. Intelligent automation would allow these machines, while building new cars, to look for and apply more efficient methods of car manufacturing to future tasks.

Intelligent Automation and New Business Processes

Businesses today use out-of-the-box automations to solve basic IT issues. These automations are great at accomplishing simple tasks and repeating them. Need to reset company passwords every 30 days? Need to recover a deleted email? Basic automation can perform these tasks without a problem. But if there’s a change to any aspect of your IT environment, basic automations will have to be reengineered via manual labor.

Intelligent automation performs and studies the processes as a human employee would. The automation learns and masters the process and everything around it so that it can use that knowledge to adapt to changes. Intelligent automation doesn’t automatically apply changes
— it alerts human labor and requests modifications for future processes.

Think of intelligent automation as a self-improving technology. It doesn’t need to be replaced as it ages, and it doesn’t rely on a vendor to make constant upgrades in order to improve. It allows companies to save money by lowering the Mean-Time-to-Resolution (MTTR) for basic tasks, and it reduces human error.

These characteristics are what separate intelligent automation from standard applications of AI, and indeed a strategy that encompasses uses of both can deliver powerful results
— something to consider as your business examines where to dedicate future investments.


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