A recent survey from Figure Eight – an Appen company – shows that AI (Artificial Intelligence) is rapidly becoming a strategic imperative. But unfortunately, there are major bottlenecks, such as the divides between line-of-business owners and technical practitioners as well as the complexities of managing data.
But there is something that should help solve the problems: low-code. As the name implies, this involves creating applications with drag-and-drop and integrations. The result is that development is much quicker and effective (here’s a post I wrote for Forbes.com about low-code).
One of the leaders in this category is Appian, which is the first low-code operator to go public. The company has a bold guarantee for its customers: “Idea to app in eight weeks.”
Founded 20 years ago, Appian started as an IT consulting shop with a focus on AI-powered personalization and ecommerce. But at the time, the technology was far from being prime time. For example, the founders realized that a well-known collaborative filtering system would always recommend the same products – even when the parameters were different! This was certainly an eye-opener.
Despite all this, the founders were convinced that AI would be a big market. However, it would need a strong platform for building applications with rules for data and models for processes. So the Appian system was born.
But in the early days, the software was used primarily for typical IT solutions, such as for building applications for BPM and case management. But during the past few years, AI has become a more common use case.
OK then, how has low-code been able to help? Well, let’s take a look:
- Clean data: A low-code system makes it easy to describe the business process, which allows for creating a solid foundation for the data. But a platform like Appian can also make educated guesses about how the data should be organzied. True, a data scientist could improve upon this but such a person is really not necessary for maintaining data integrity.
- Ease of implementing a model/testing models: Consider that Appian allows for integrations of various third-party AI systems, such as from Amazon, Microsoft and Google. “An Appian customer recently was able to do a bake-off between leading AI providers because of the ease of being able to integrate them into the Appian platform,” said Michael Beckley, who is the CTO of Appian.
- Guardrails: When developing an AI project, even a few adjustments can wreak havoc on a model. But a strong low-code system can provide warnings and suggestions to avoid the mistakes.
- Deployment: A low-code system can deliver an app across multiple platforms, whether on the web or mobile. There is also the benefit of having a modern UI. No doubt, all this can go a long way in terms of adoption.
An illustration of the power of low-code comes from KPMG. The company has been investing heavily in AI, creating its own platform called Ignite. And yes, it is integrated with Appian.
One project that KPMG took on was to help companies deal with the sun setting of LIBOR, which means that huge numbers of contracts need to be amended.
The Ignite system processes and interprets the unstructured data using machine learning and natural language processing. After this, Appian then provides for sophisticated business process management and workflow capabilities – allowing for document sharing, customizing business rules and real-time reporting.
Based on KPMG’s own experience, the error rate for having people review the contracts ranges from 10% to 15% (this even includes trained attorneys). But with AI and low-code, the company has been able to achieve an accuracy rate better than 96%.
“Greater efficiency and higher accuracy translates to reduced operational risk, reduced economic exposure, lower cost, and better client experience through the LIBOR transition,” said Todd Lohr, who is a Principal at KPMG. “What takes a few hours for a subject matter expert to do can be accomplished by Ignite in a matter of seconds.”