Low-Code Is Cracking The Code On AI (Artificial Intelligence) 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 the 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 organized. True, a data scientist could improve upon this but such a person is really not necessary for maintaining data integrity.