The Contrast Between Intelligent Automation (IA) and Artificial Intelligence (AI
Pat Graham speaks about the realities of moving from IA to AI and what you can really expect to get, without all of the hype.
As the pace of technological change continues to move at breakneck speed, it is becoming increasingly difficult to understand the business value behind the buzzwords. Stories about automation, robotics (RPA) and artificial intelligence (AI) have dominated our newsfeeds this year. But they seldom provide any understanding of how these technologies can help transform a business.
This is the first article in a series that will take you on a journey and dispel a few myths about these trends, hopefully in easy to consume language. Along the way I want to enable you to step back from the hype and understand how you can implement these technologies to increase your revenue and save your business money too. I want to help you move beyond the sales pitch of AI is the future to how will this help your business.
Our journey takes us from intelligent automation (IA) to artificial intelligence (AI). Although, you have probably read many articles that suggest a combination of AI and automation will pave the way to a tech-fueled dystopia and a dehumanized workforce, the reality is we have been here before, and it's nothing new.
The term automation was first used in the 1940’s to describe automatic controls in mechanized production lines. In simple terms, automation is the technology by which a process or procedure is performed without human assistance or intervention. Intelligent Automation is when you inject a set of logic or rules by which a more complex decision tree is followed and results stored accordingly.
In some circles within the industry, there is a belief that intelligent automation (IA) needs artificial intelligence (AI). I would argue against this school of thought because IA is rules-based where AI is not. Essentially, AI should be a boundary less environment where a machine (computer) learns, applies logic, knowledge, reasoning, and problem-solving to implement a solution to a problem. Equally, AI can make a recommendation then reapply that logic, learning and expanding its rule base as it grows.
In simple terms, you can quickly achieve intelligent automation without moving into the world of AI, where a natural outcome of AI is IA. Although the journey from intelligent automation to artificial intelligence can be daunting, understanding precisely what problem you are looking to solve should always be your priority.
Too many businesses head straight into solution mode and become overwhelmed by the allure of the latest shiny technology. Don't be tempted to stray from your path and lose sight of your objective; this should always be paramount. A salesperson will happily drop buzzwords to get you to sign on the dotted line, but will it really streamline your business processes?
When implemented in the right scenario and for the right reasons, the results AI can offer are incredibly impressive. For example, I have worked with a company that ran their 5000 call centre calls through an AI engine and over 4900 were rerouted and resolved correctly.
However, this was just the beginning, when pushing them though 2x further, 4997 of them were resolved first time without the need of any human intervention. When a new batch of 10000 calls was added, there was a success rate of 98% first-time resolution. The most impressive aspect of this test was it highlighted how the AI engine was learning.
In a digital age where the customer experience is becoming as important as the transaction itself, AI could offer obvious appeal. Decreasing resolution and waiting times are just a few examples of how technology can deliver greater business value and a vastly improved customer experience.
By contrast, intelligent automation (IA) is more of a mechanical activity. For example, in a similar scenario to my example above, when a leading mobile phone provider launched a new upgrade offer to the market. Every time a customer called and selected a specific item in the interactive voice response (IVR) menu, it was tracked.
Throughout the promotion, the company was able to see they had over forty thousand requests for this specific offer. To keep this from becoming a manual process, they combined data collected with the call log, tied this to the subscriber information, and automatically completed a credit check. Applicants who successfully passed the credit check were sent an SMS to confirm they wanted the upgrade.
Those that were unsuccessful were also informed and given the opportunity to request a reason for being turned down. Once the subscriber replied with confirmation to accept the offer, the offer was placed, warehouse informed, all order details attached to the customer record and customer notified of the pending delivery.
The entire process was completed without any human intervention. This is intelligent automation. It did not require any special learning but followed a predefined set of rules. Unlike AI, IA assists rather than replaces people and enables them to amplify their capabilities by leveraging its technology.
For many enterprises, understanding the contrast between IA and AI will be the first steps on their digital transformation journey. As businesses of all sizes begin to rethink all of their processes, intelligent automation could be the star of the show rather than AI.
Achieving business goals, improving productivity, and making workers happier by freeing them from the shackles of repetitive, mundane tasks while also reducing expenses is a language that every leader can understand. By unlocking the power of IA, we are only just beginning to see the art of the possible on the horizon.