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Scalability Of Intelligent Automation Technologies Directly Linked To Financial Performance, Finds KPMG Survey


According to KPMG International’s new “Easing the pressure points: The State of Intelligent Automation” global survey, enterprises are not scaling Intelligent Automation (IA) technologies [artificial intelligence (AI), advanced analytics, and robotic process automation (RPA)] fast enough to meet desired objectives and returns. However, those organizations that are scaling IA technologies are seeing strong financial performance.
Read the full report here.
When will your adoption of Intelligent Automation (IA) be scaled-up and industrialized?
What is your organization’s topline and bottom-line performance?
What are the top three inhibitors that are holding you back from achieving strategic AND operational goals?
“Investment in and adoption of IA technologies are occurring at a rapid pace, but many organizations are struggling to demonstrate significant impact,” said Cliff Justice, KPMG principal and U.S. leader of intelligent automation. “Without a holistic digital transformation strategy that underpins IA investments across an entire organization, these projects are stunted in pilot mode and fail to deliver the intended results. Yet, when implemented with a clear vision and integrated approach, IA is propelling businesses, not only with a competitive business edge but financial success.”
Key findings of the State of Intelligent Automation survey include:
- Investment in IA tech is strong with 52 percent of companies confirming investments of more than $10 million; yet investments are imbalanced across functions – finance and accounting are seeing the biggest investments.
- There is a distinct correlation between scale and top financial performance. While 64 percent of the top performing companies surveyed will be scaled by 2019, 59 percent of poorly performing companies need another 2 – 5 years to achieve IA scale.
- Overall, only 17 percent of companies surveyed have scaled up or industrialized IA technologies. Smart analytics was cited as the top most scaled technology, while RPA was the least scaled. And, the technology that organizations are experimenting with or piloting the most is AI (36 percent).
- Scale remains a leading challenge to achieving key goals with IA technologies. Other notable challenges pinpointed include uncertainty about the financial investment needed; lack of clarity on accountability for driving the agenda; and concerns about changes in governance and risk management.
- Business executives are optimistic about the impact IA will have on jobs — approximately one-half of respondents surveyed say automation will impact fewer than 20 percent of their staff. KPMG feels these executives are overly optimistic.
“To realize the full potential of IA beyond cost savings, organizations must think beyond technological investments and incorporate change management at every step of the way,” Justice continues. “Even the most basic of robotic process automation technologies will impact the future of work. Broad-ranging transformation strategies are critical to future-proofing companies’ most valuable resource: their workforce.”
Thomas Erwin, head of KPMG Global Lighthouse and a partner with KPMG in Germany, concluded, “To ensure an effective, comprehensive IA strategy that integrates complex technologies such as AI, three key components are essential: clear business objectives, an adequate budget and an orchestrated approach. These are fundamental to successfully scaling up IA across the enterprise.”
SOURCE KPMG LLP
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