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Ready, Set, Fail?

Ready, Set, Fail?


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Avoiding setbacks in the intelligent automation race

Findings from KPMG research study

Most intelligent automation (IA) projects underway or currently in the pipeline will fail.   


While enterprises have high expectations of the impact of IA, they are not yet ready to implement it from the top down and at scale. Until companies recognize two critical issues, they will struggle to get an adequate return on investment. First, IA investment decisions need to be C-level strategy imperatives, and second, IA is about business and operating model transformation, not simply technology deployment.

It is not clear whether most companies understand that IA is about changing business processes, and then restructuring the organization around those new processes that are now driven by technologies that did not exist before. This means shifting the business and operating model from one of people supported by technology to one of
technology supported by people. It's a digital-first operating model.

KPMG recently undertook a study to understand the reasons for and implications of deploying IA and what it takes to scale. KPMG professionals interviewed executives from numerous industries and geographies worldwide about their experiences with deployment and their perspectives on the future. Most emphasized that IA is poised to digitally transform their companies and industries and profoundly impact their employees' roles.

At the same time, executives highlighted several challenges. In addition to grappling with the extraordinary pace of change, they are faced with understanding and choosing among hundreds of technology options, the need for effective data and analytics, prioritizing automation focus, and defining their future workforce. KPMG research considered three main areas of IA—basic or robotic process automation (RPA), enhanced automation, and cognitive automation.

These results underscore the need to not only act quickly but to also plan deployments strategically with scale in mind. Most companies' executives acknowledged they are still experimenting only with RPA, applied to legacy applications and processes. With such a narrow focus and a bottom-up approach, they have not positioned themselves to transform their business and operating models so they can become and remain competitive with digital-first companies.


"Many traditional businesses with legacy approaches risk falling behind digital-first companies if they stay with the status quo. It takes a comprehensive transformation of business and operating models to compete in their own market at the level at which a Tesla or Amazon do in theirs."

- Cliff Justice, KPMG Partner,
Innovation & Enterprise Solutions,
and leader of Cognitive Automation initiatives

As IA use accelerates across industries and organizations worldwide, digital-first companies already have a distinct competitive advantage. Not all companies can emulate Amazon’s one-click experience with its complexity and checks-and-balances built into a digital supply chain.
Companies can, however, close these gaps if they act quickly, understand the urgency, and define and execute a comprehensive IA strategy—one that not only looks at technology, but also at business and operating model opportunities and constraints.

This report summarizes KPMG’s research into how IA is currently impacting business and operating models. It provides recommendations for how companies can plan for and implement an IA strategy that will help enable them to compete with digital-first competitors and thrive in a digitally driven world.

Defining the IA marketplace

Enterprise investment in the IA market—which includes artificial intelligence, machine learning, and RPA—is growing rapidly.
Overall spending is expected to reach $232 billion by 2025 compared to an estimated $12.4 billion today.


For more information, download the full report below.

The information contained herein is of a general nature and is not intended to address the circumstances of any particular individual or entity. Although we endeavor to provide accurate and timely information, there can be no guarantee that such information is accurate as of the date it is received or that it will continue to be accurate in the future. No one should act on such information without appropriate professional advice after a thorough examination of the particular situation.

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