What Companies Are Getting Wrong About Automation and Artificial Intelligence

Companies are increasingly experimenting with robotic process automation (RPA), artificial intelligence, and machine learning around the edges of their operations, but few are ready to deploy it systematically or at scale.

Even more troublingly, due to this misguided approach, the bulk of the related projects currently underway or soon to launch will end up failing, according to a new report from KPMG.

While the implications of taking the wrong approach are being felt by some companies now, this will only accelerate in the years to come if efforts aren’t made to use a more holistic strategy.

This market, which KPMG collectively categorizes as “intelligent automation” (IA), currently represents about $12.4 billion in overall spending. By 2025, this figure will be nearly 20 times bigger at an estimated $232 billion, says the company.

Ultimately, the newness of these innovations and cultural inertia at most companies mean that too many executives still fail to grasp that true transformation requires moving toward a “digital-first operating model,” says the big four auditing and professional services firm.

Though things are starting to change, KPMG firm notes that further adoption will likely require “shifting the business and operating model from one of people supported by technology to one of technology supported by people.”

In its study, “Ready, Set, Fail: Avoiding Setbacks in the Intelligent Automation Race,” the company highlights the limitations of any move that comes from a “bottom-up” desire to simply automate legacy processes.

“Until companies recognize two critical issues, they will struggle to get an adequate return on investment,” states KPMG. “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.”

To be sure, there are some low-hanging fruit areas to realize efficiency gains, particularly in the form of automating repetitive tasks in areas like payroll, invoicing, and customer service. But the potential benefits will remain narrow unless automation advances are thought about strategically and with scalability in mind.

Beyond losing out on savings and efficiency gains, companies that fail to evolve to this new mindset are setting themselves to be passed up by competitors, says Cliff Justice, partner and leader of cognitive automation initiatives at KPMG.

“Many traditional businesses with legacy approaches risk falling behind digital-first companies if they stay with the status quo,” said Justice. “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.”

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