Understanding Artificial Intelligence from Intelligent Automation – Analytics Insight

Understanding Artificial Intelligence from Intelligent Automation – Analytics Insight

What channelizes Digital Transformation into Industry 4.0? – Its AI and IA!

Businesses the world over are on the cusp of an interesting technological advancement: Digital Transformation (DX). Built on revolutionary technologies, could computing, IoT, big data and AI, DX has innovated products, work processes and legacy systems redefining the foundational change in how an organization delivers value to its customers.

Among the disruptive technologies, Artificial Intelligence (AI) and Intelligent Automation (IA) are two terms to most recon with. Together they have mobilised customer support with conversational AI, and changed the very nature how business transactions are handled.

The use cases don’t end here. As databases and customer relationship management (CRM), /ERP systems go dynamic, businesses capture huge amounts of data with much of it being unstructured. Going forward, scalability remains one of the biggest problems faced by businesses. The one obvious solution being automation which takes care of both structured and unstructured data crunching.

Disrupting Industry 4.0

In the age of digital disruption, intelligent automation is omnipresent. A heady mix of AI and RPA, intelligent automation is adapted for its sheer ease to automate rule-based tasks and unstructured data handling.  In this digital age, organizations walking on the path of change management adopt intelligent automation in a bid to outsmart their competitors.

You may wonder can these two terms be interchanged? The short answer is NO. IA and AI are two different concepts, the main point of difference being while artificial intelligence is about algorithms programmed to mimic human cognitive functions, intelligent automation takes the rule-based, highly voluminous work processes to AI-enabled RPA bots to ensure improved safety, operational efficiency, and business continuity.

Artificial Intelligence into Data Management

Needless to say, there are some genuinely transformative things that Artificial Intelligence can crack, solving complex problems in many fields, including manufacturing, health, weather prediction, and finance and logistics.

However, an enterprise must not see AI advancement in isolation. The emergence of intelligent automation (IA) in tandem with its sustained maturity has to be acknowledged to get a clearer picture in which direction technological progress is headed to. Intelligent automation brings together speed and power of BPM, machine learning, and RPA to strategize business goals, optimize customer experience, and set your business apart from the rest of the pack.

Simplifying processes with Intelligent Automation

Intelligent automation software is more than capable to efficiently handle routine manual tasks like running thousands of data-driven scenarios to ensure the accuracy or validating a series of processes across the cloud environment. Process, technology and people are the key to scale Intelligent Automation to reduce strain on their workforce and reap the benefits of higher productivity, reduced costs and improved compliance.

  • Scaling intelligent automation comes without an exception, the core being a blueprint plan.
  • Technology drives work processes and data. This is where a traditional RPA solution falls short. To parse intelligent insights enterprises, need intelligent Automation.
  • To march ahead in the competition, digital workforce and human mins need to work in tandem to oversee the overall automation program being implemented.

The complexity of today’s digital landscape invites intelligent solutions for consistent, efficient and accurate analysis. Where it gets interesting is the classic marriage between AI and Automation — also referred to as intelligent automation (IA).

This powerful combination, driven by advanced cognitive engines, machine learning (ML) algorithms, forms the starting point to be applied to solve a wide range of business problems. Other disruptive technologies like natural language processing, Cloud computing, IoT and 3D Printing come later.

In the long run, for organisations to harness the most from intelligent automation, a clearly defined processing environment need to be defined where humans review and approve machine decisions to drive strategic outcomes.

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Kamalika Some

Kamalika Some is an NCFM level 1 certified professional with previous professional stints at Axis Bank and ICICI Bank. An MBA (Finance) and PGP Analytics by Education, Kamalika is passionate to write about Analytics driving technological change.

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