To implement intelligent automation, our global IT organization's Automation COE team
is carrying out a three-stage journey:
Foundational framework
The first stage was to lay a foundational framework by enhancing processes according
to industry-leading practices, improving data quality to enable automations and
developing an intelligent automation platform. The guiding principle in this stage
was to take an intelligent “shift left” focus, meaning a focus on prevention. We
concentrated on eliminating waste, simplifying processes, implementing preventative
remediation and building a foundational informational infrastructure. We assessed,
targeted and prioritized processes across the delivery life cycle to be optimized
and automated using techniques available. And we continue to do so.
An automation discovery team analyzes use cases to determine how to resolve
operational issues through automation. We use scripts, macros, batch programs, mini
bots, and other standard and custom solutions to automate standard and repetitive
tasks. We have implemented several robotics processes extensively to automate
repetitive and predictable tasks to eliminate several days of manual effort for
operational activities.
Intelligent automation
In this stage, we are accelerating the adoption of intelligent automation and
artificial intelligence. We are looking to expand our application of cognitive
chatbots and intelligent bots for all possible processes and to focus on optimizing
processes and preparing for a digital operations model. The vision is to create an
AI/ML-powered robotic workforce to augment humans in operations to enhance user
experience, improve quality and reduce operating expenditures.
Intelligent automation represents an evolved version of automation in which machines
mimic human actions and possess cognitive capabilities, including natural language
processing, speech recognition, computer vision technology and machine learning.
Machines with automated intelligence comprehend vast amounts of data, analyze,
understand and learn it on the go, and intelligently automate processes to bring in
more operational and business efficiency.
Leading the innovation drive, Accenture developed and deployed multiple AI machine
learning assets. Each asset involves AI analysis of tickets, provides
recommendations and automatically resolves the tickets. These solutions are helping
accelerate Accenture's touchless operations journey while improving speed and
accuracy of ticket resolution.
Touchless operations
Our vision of touchless
operations is to disrupt and redefine internal operations. We are exploring
ways to deploy highly intuitive solutions; use machine learning to predict events
and recommend next-best actions; mature self-learning, self-healing capabilities and
auto-resolution processes; and minimize human-engaged transactions. Our strategy
will be to focus on guided solutioning through platform adoption, operating in the
cloud, reflective intelligence, self-service offerings, interactive bots and
gamification triggers.
People and culture
Automation helps improve our internal operations productivity, quality, performance
and user experience. It also helps to reduce manual work of global IT operations
teams and enables employee careers to evolve to different roles that drive creative
thinking and working with machines for problem solving. This evolution reflects a
technology trend Accenture calls Human+
Worker, where workforces are becoming human+: each individual is empowered
by their skillsets and knowledge plus a new, constantly growing set of capabilities
made possible through technology. Companies must adapt the technologies that
successfully created this next-generation workforce to support a new way of working
in the post-digital age.