Contact Us

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Thank you for your interest in Cognizant.

We’ll be in touch soon.

We are sorry. Unable to submit your request.

Please try again or post your inquiry to

How AI extends the case for enterprise IT automation

October 18, 2019 - 566 views

How AI extends the case for enterprise IT automation

By adding AI-powered IT automation across the enterprise, organizations can realize not only operational efficiency but also unprecedented business change.

Artificial intelligence (AI) offers an unprecedented opportunity to reconstruct business models and re-engineer business processes. By adding AI-powered automation to their strategic mix – across the front, middle and back office – IT organizations can simultaneously deliver superior user experiences, increased efficiency, optimized cost and improved agility.

The full potential of AI and automation can only be achieved by integrating these technologies into the workstream, with the goal of enabling enterprise-wide business improvement. To quantify progress, tangible and measurable business outcomes need to be defined. For example, an insurance company embarking on an intelligent automation initiative could measure  the percent reduction in cost per claim; a retailer could measure percent improvement in on-time shipping, etc.  

Focus on Business Change

In addition to operational efficiency, enterprises should prioritize how AI and automation can facilitate business change. We worked with a large U.S.-based agricultural company that had incurred penalties due to failed transactions caused by software application issues. We supported this critical application with  Cognizant HiveCenterTM, our AI-enabled intelligent automation platform.  By focusing on the outcome (eliminating the penality rather than application uptime), we helped the business realize dramatic cost savings.

Intelligent automation is applicable across IT operational processes in enterprise application support, cloud, infrastructure and security. For a retailer with stores across North America, whenever store application performance is slow, AI-based automation kicks in as the first line of diagnosis across server, network, database and application stacks. Automation is also prevalent in digital engineering when applications are developed with cloud-native technologies across the design, test and release cycle.

Moving From Thought to Action

A recent report we commissioned from Everest Group provides insight into how to establish business value and build a roadmap to intelligent automation. 

  • Develop a business-led view of IT automation. This is a critical step. For retailers facing stock-out issues due to supply chain issues, intelligent automation can enable systematic management of inventory. To meet this goal, the business-led view should also include efforts to streamline required business processes and make behavior and procedural changes, as well. Only then can automation deliver true benefits to mitigate stock-out issues.
  • Understand the business value continuum. Business objectives and system characteristics vary significantly across the front, middle and back offices. With the right approach to designing and implementing the automation framework, intelligent automation not only delivers outcomes within a function, but it can also connect and orchestrate value across functions. For example, when we automated a client onboarding process for a mortgage company, we focused on customer interaction (front office), application processing (middle office ) and automation reconciliation (back office).
  • Measure the efficacy of your automation implementations. Enterprises need to articulate desired business outcomes through tangible business KPIs. However, certain KPIs are difficult to achieve without significant business refinements beyond IT modernization and automation. Choosing the right set of KPIs and establishing clear expectations (as noted above) is key to measuring efficacy.

To accelerate automation-led initiatives, enterprises should look to partners that invest in advanced capabilities, including integrated AI/ML-powered platforms. Such platforms accelerate  automation programs with minimal impact on existing processes.

Digital Business & Technology, Intelligent Process Automation automation, artificial intelligence, intelligent automation, AI, IT automation

KS Ganesan

K.S. Ganesan (KSG) is Vice President and Global Technology Leader within Cognizant’s Enterprise IT Automation Practice. With...


Related Posts

Don't Miss Our Next Cognizant Chronicle

Get actionable strategy and tech insights monthly to help your business thrive.

Subscribe now