Information Technology - Blog V-Soft Consulting

How to Bridge the Gap Between Automation and AI

Written by Charan Sai Dasagrandhi | Jul 24, 2020 1:45:00 PM

As businesses are looking to automate processes now more than ever, it's important to understand that each solution requires a thorough definition of the processes you want to automate. Artificial intelligence (AI) is often viewed as a top solution for automation. During the AIIC's Back to Business with AI event, Manoj Iragavarapu, Managing Director of V-Soft Digital, discussed how to bridge the gap between automation and AI. 

Role of AI in Process Automation

To successfully bridge the gap between automation and AI, there are three aspects that must be considered: process mining, collaboration and use cases.

Process Mining

When considering automation, the first question you should ask yourself is, "What are our current processes and what steps within those processes can be automated?" To address this, you must take the time to define and document your existing processes, otherwise known as process mining.

Some tools use AI to perform process mining. These tools connect with your systems and monitor the correct process and generate a process map to determine which process needs to be automated. Utilizing these tools can save time in the process mining step. 

Collaboration to Drive Automation with AI

It's not often that a single process can be automated in a silo. Steps can be taken to automate business processes using many tools, expertise and existing platforms across departments. It takes collaboration with dedicated teams to be successful. Whether SMBs or large-scale enterprises, the cost to establish these automation processes is affordable.

Use Cases and Subsequent Steps

During his presentation, Manoj touched on many different use cases of automating processes, including a process mining tool built by the AI Innovation Consortium. Another example was from Penn State and the University of Houston, where process data was collected from enterprises to create more efficient workflows. This information was used to create a proof of concepts and staged into production-grade products.