There are a growing number of use cases for intelligent automation out there. Lawtech, Insurtech and Healthtech are just some of the vertical-specific names for a growing number of services that deliver varying levels of intelligence and automation to those markets.
In the case of insurance, one of the earliest adopters, intelligent automation is used to help with underwriting processes. AI using natural language processing (NLP) can help tally the benchmark scores by which underwriter summaries are based on. It can then create an initial draft for the underwriter to check and approve. If there’s an issue, the underwriter can check the AI’s thinking and correct it, making the AI smarter.
That example came from AXA in 2019, and it’s not hard to imagine the tool being able to halve processing times for the underwriters. It doesn’t replace them but allows them to focus on the key parts of their role.
How IA can change the world
One potential scenario sees an intelligent robot process automation (iRPA) tool scanning fault record documents. Traditionally, it would feed the data into other documents for later analysis, but the intelligent RPA spots a change from previous batches of reports, a rise in a particular issue.
Normally, that might generate an alert or error, requiring human intervention. But the company’s iRPA can identify a common element responsible for the fault from the data. Not only can it alert a manager to a specific problem, the iRPA can talk directly to the production chatbot of a factory that might be next door or on the other side of the world.
It can provide pertinent data including when the issues started being reported, part numbers or batch codes. They can correlate those with any changes in the production factory and, between the two tools, identify exactly what went wrong. The bot can alert its factory of the dodgy batch, perhaps telling a robot to remove it from the floor if it is still in use, and summon fresh stock on an automated transport, and order more supplies with a third party. And the original iRPA can tell another intelligent agent to send recall codes to any stores or warehouses with contaminated stock.
The factory fixes the problem instantly, the company doesn’t sell any more a low-quality product, and the quality assurance manager is still enjoying their break when a validated report about what the bots achieved comes in.
With a collection of intelligent agents working in the business, any process from sales to accounts, production to invention becomes faster and smarter.
Catalyzing change in your business
Every business and market has similar tasks that need doing, and tools like RPA and AI analytics have been helping speed up the process to make the digital effort work smarter. Examples might include:
- Improving business workflows
- Business document processing, analysis and creation
- Developing process intelligence for production lines
- Automated building of apps or tools for the business, clients or customers
There are two ways any business can adopt intelligent automation:
- The seed and grow approach
- Through a planned rebuild of the company’s IT infrastructure
Seed and grow sees the company analyzing all aspects of the business. Then, picking areas that are ripe for automation and intelligent automation, building and delivering solutions that can transform a function, process, role or department.
With a few easy wins and some more challenging efforts, the business starts to develop its IA skills, while workers and leaders start to notice the benefits and want to take further steps along the road to AI and IA.
Rip and replace is rightly falling out of favor with most IT departments as there is little need to cause great disruption, except in the most legacy hardware- and software-heavy environments. However, for larger companies, a great migration to a new system that features the latest AI and intelligent automation tools is more akin to a grand adventure than a trip to the breaker’s yard.
Many businesses in vertical markets might prefer to upgrade from their generic tools to ones specific to their industry. Even so, in many cases, the experience can be more gentle. Vendors are rapidly adding wide-ranging intelligence tools to their products, from smart analytics, intelligent RPA, AI chatbots and other features.
Services or applets using these features can be investigated and developed by non-technical staff using drag-and-drop, what you see is what you get, or no-code building tools. Whatever approach is taken, a company can start from the same building blocks of analyzing what can be automated and then developing the tools in one swift drive for automation.
Or, they can be rolled out by division, region or other boundaries, as the improvements become apparent, and any early-stage glitches are fixed, allowing the rest of the business to see the benefit.
Where will intelligent automation take us?
If you were wondering how big the IA market is, investment in intelligent automation should hit $232 billion by 2025, compared to around $12.4 billion today. The same research suggests that smart investment in IA could see a business yielding 5 to 10 times the dividends of those not taking the IA route.
By creating new business and operating models and using IA to inspire and generate further automation efforts, the use of IA could become a self-generating success story, as AIs start to teach each other, communicate with each other, and speed up how business is done, the possibilities become huge and will impact any type of market.