Insights & Use Cases

What We Offer

Strategy

We help you develop a Strategy and a Roadmap, including Tool Selection, Productivity metrics and ROI Models.

Implementation

We deploy your RPA solution, establish governance and address IT and security concerns. We also train your staff to maintain the solution.

Managed Services

We manage, monitor, tune and continually optimize your robotic process execution. We also implement enhancements and manage your RPA infrastructure.

TALK TO US

AI is Not Scary!

Not a day goes by that you hear about the dire predictions on Artificial Intelligence taking most of the human jobs away. When you look around yourself and hear about self-driving cars, Alexa, Siri, etc. it feels like humans may not have much to do after a few years. The reality however is not that bleak…

AI can be taught to drive cars, but the same AI can’t be used to clean tables. AI can beat humans on the “Go” board game (www.alphago.com) but the same AI program does not know how to play chess. So, today’s AI and Machine Learning can perform incredibly well at tasks that we train computers on but without proper “labeling” or training of the algorithms, it’s still a garbage-in and garbage-out scenario. Today’s AI technology is fundamentally great at processing huge amounts of data and use supervised and unsupervised AI techniques to solve a narrow set of problems that its trained on. The term “Narrow AI” describes the state of AI technology today as compared to human-like “General AI” which still may be a few decades away.

So why use AI? Businesses can use AI to solve a lot of prediction problems using their own internal data as well as combining it with publicly available external data sets. For e.g. if a financial institution is trying to predict its sales for the next few quarters, the accuracy of the prediction may be much better if they use not only their own existing data sets but also utilize macroeconomic data such as interest rates, etc., to better align their sales forecast with broader market factors. So, business intelligence is probably one of the first places where AI and machine learning technologies can have a huge impact as it allows BI groups to go beyond their traditional retrospective and predictive analytics and add a prescriptive element to their analytics.

Business process automation is another area where there are tremendous applications for AI. For e.g. many businesses have large document management and OCR system deployments, but, they still have a lot of manual business processes around such implementations. AI and ML can potentially lead businesses toward the autonomous execution of such processes using AI technologies such as natural language processing, robotic process automation, etc.

Marketing can use AI to create better customer engagement through company’s existing customer facing channels such as their websites, mobile apps, etc. For e.g. AI technologies such as sentiment analysis can help in real time social brand management. Chatbots and customer service rep assistive Bots can help in creating better overall customer engagement for the customers.

The list of business use cases goes on and on…

In summary, AI is NOT magic (at least for now). But the ability of machines to learn and program themselves even within the bound of “Narrow AI” is an incredibly powerful evolution of computing which has been termed as the 4th industrial revolution, and rightfully so.