Go Beyond Automation with AI
You would be hard-pressed to find anyone who would prefer to do things manually when an automatic option exists. There is a reason we no longer “roll down” our car windows with a crank or wash our clothes in a bucket.
But while most customers would like to reduce rote tasks and manual errors, deciding what (and how) to automate is not without challenges.
On October 26th, I’ll be joined by Ritu Jyoti, Group Vice President, Worldwide Artificial Intelligence and Automation Research Practice Global AI Research Lead from IDC and Andreas Welsch, VP Marketing & Solutions for AI at SAP to discuss some recent findings from an IDC survey on Scaling Low Code Success. You’ll hear how the merging of different technologies not only addresses some barriers to adoption, but helps you go further, faster.
Tools like process analytics and process mining can help you understand bottlenecks and inefficiencies so you can optimize processes in a way that is impactful to your business. These solutions, along with employee and customer sentiment, are critical to knowing where to start.
But how do you automate? Some organizations consider workflows or RPA bots in isolation. But in reality, these tools used in tandem deliver better outcomes. Workflows can optimize the process and include considerations like business rules to remove unnecessary steps. For example, if you don’t require manager approval for customer-facing travel, you can skip that step in the process. Integrating APIs into your workflows helps transfer information to the next step in an application. But APIs are not approachable for most citizen developers, so you need to abstract the complexity. For this you need a solution that supports collaboration between IT/pro-dev and business people. And for situations where APIs aren’t possible (because of complexity, the lack of a public SDK, or a legacy system) RPA bots can step in to be your digital assistant, copying and pasting, parsing copy, screen scraping and more.
Another consideration is that truly modern automation systems also need to have intelligence (AI) included; ideally in a manner that is seamless to the end user. One example of applied AI is document processing where AI can extract, classify, and route information automatically from scanned or digital documents and create records from them for use by your employees or applications.
Process analytics and mining, sentiment data, automation solutions (like workflows and RPA) and AI are the technologies needed for hyperautomation. But who builds automations? IT and Pro-Dev are often removed from the actual process and it’s challenges. This is where citizen/business developers can step in as the experts. In the IDC survey referenced, over half of respondents who were business developers were developing workflows and RPAs using low code tooling and of those, most planned to increase their investment. But this makes the need for low-code interfaces critical, which allow business developers to use tools they are familiar with (like drag and drop interfaces) and to remove complexity.
While low-code solutions make automation more successful they raise other challenges like the need for better process insights as well as opening security concerns. So in our discussion we’ll explore not just the tools to build automation, but also how to successfully organize multi-disciplinary teams and proper training to ensure success of your automation projects.