The Journey Of Intelligent Automation

Cere Labs
4 min readSep 20, 2018

Artificial intelligence as a concept has been evolving exponentially since the last two decades now. Today, more than ever AI-driven technology has become accessible than what it was a few years back. With new and improved machine learning algorithms, the possibilities of enterprise ready cognitive systems have become a reality.

It’s been widely talked about how AI can unlock new business potentials, at both speed and scale as compared to humans. But something that we most importantly need to discuss is how is it going to happen? How can AI actually solve real world problems when it comes to implementation? Where are we when it comes to the journey of Intelligent Automation?

To get the answers we are looking for, we need to firstly treat AI as a component of a comprehensive strategy for Intelligent Automation that does more than insight mining but also assists with an actionable plan to utilize those insights. This actionable plan of which humans will also be a part of & thus making processes more efficient. This is where Artificial Intelligence as we know evolves into what I call — Actionable Intelligence.

We believe that the combination of IA (Intelligent Automation) and RPA will allow organizations to achieve the maximum extent of their desired digital transformation. So, while RPA (Robotic Process Automation) enabled the industrial revolution of the 21st century, IA will be leading the digital revolution.

Activating IA can lead to better utilization of people’s skill to areas where it is most required. When the repetitive tasks are taken care of by intelligent automation, it allows the workforce to focus on their people skills to drive delightful customer experience. In a nutshell, the company can plan a growth journey with reduced overall operational costs.

However, the current challenges that is affecting most businesses to experience the above scenario is that they are still bedazzled by AI. While most businesses want to be associated with it & they are still unsure about its application around their business. People are fascinated by a self-driving car or media stories about a fully autonomous robot. The recommended course of action for most companies would be to take the foundation steps. It is important to understand the business requirements, processes involved as you plan to integrate AI into your business operations. It is a learning cycle where the results need to be measured to truly realize the impact of AI, then a report of the corresponding performance can be shared with the decision makers to raise awareness.

Now various types of intelligent automation services are available namely optical character recognition, analytics, data extraction solutions etc. However, it is important to understand to what extent the service is going to solve your operational concerns associated with the particular process. For example if it is about document processing, what are the various challenges addressed by the said solution. Does the solution work in case of noisy inputs or intractable handwriting etc.

Thus, organizations need to treat the integration of IA as an extension to process improvement. At the moment, Artificial Intelligence can create infinite opportunities theoretically implying but to realize its full extent we would need to take realistic steps in the present to drive an organizations growth goals. This journey begins with asking important questions about the processes in your organization and understanding the significance of dark/unstructured data generated. In an ideal scenario it would take up to 90 days to reap long term benefits. If you are a business and wondering how you can make the most of this technology, the following stages would be helpful:

Eventually, in the process of adapting a strategy for Intelligent Automation, it is important to embrace a new perspective of looking at technology. What we might require now is an ecosystem where intelligent automation can co-exist with business services. There is also a realization that we might need to evolve our mindset when it comes to adopting AI solutions. It has been observed that we predominantly are used to the working of the Software paradigm” where we are aware of the steps and know what to do in every exception. It is however different in case of AI. One of the ways of understanding this phenomenon is through partnering with companies that have developed an AI expertise.

~ Written by Amyth Banerjee (AI Prospector, Cere Labs)



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