Release Notes

6 Cognitive Automation
1 Problem Statement
Businesses are undoubtedly at the cusp of “AI everything”. Industries as diverse as Motorsports and Medicine,
have started collecting data for the purpose of analyzing, predicting, and maximizing organizational
performance. AI has been silently churning behind the scenes keeping our credit cards and identity protected.
AI has moved seamlessly into our homes with the advent of Amazon’s Alexa and Nest. And today, AI is on the
verge of overtaking an everyday task in the form of autonomous vehicles.
Some in the Engineering community have concluded that the time is now to understand how we can apply this
exciting capability to remove even more mundane and manual tasks from our engineering job.
Many Engineering organizations that have already instilled a culture of continuous improvement through
automation with their prior adoption of Agile, Test Automation, and DevOps practices, are the best suited to
begin the exploration of the AI-inspired solutions to the Engineering SDLC processes.
Figure 1- Evolution of Automation in the SDLC
The next generation of Automation within the Engineering SDLC comes to us in the form of AI-inspired
approaches: Analytics, AI and Machine Learning. We call this Cognitive Automation. It offers the promise of
the automation of tasks that up until now could only be performed by humans.
Practitioners going down the path of Cognitive Automation should proceed with caution due to the combination
of excessive hype and unprecedented complexities as compared to prior stages of automation. There’s certainly
a wealth of similarities to prior stages of the automation evolution:
• During Agile adoption, organizations experienced massive process and cultural changes across
Marketing, Development and Test organizations.
• During the adoption of Scripted Automation, organizations had to re-skill their Test workforce with
programming skills.
• During DevOps transformations, the culture and program skillsets were in place, but new tools for
provisioning and cloud-hosting powered the enablement of this stage.