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KPMG: Scalability of Intelligent Automation Technologies is Directly Linked to Financial Performance

KPMG: Scalability of Intelligent Automation Technologies is Directly Linked to Financial Performance

According to KPMG’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 organisations that are scaling IA technologies are seeing strong financial performance.

KPMG collaborated with HFS Research to explore how fast IA technologies are being adopted and what successes and challenges have surfaced. Nearly 600 business leaders including 100 top-level executives across six industries and 13 countries were surveyed about their experience with handling intelligent automation issues.

“Investment in and adoption of IA technologies are occurring at a rapid pace, but many organisations are struggling to demonstrate significant impact,” said Cliff Justice, KPMG Principal and Head of Intelligent Automation. “Without a holistic digital transformation strategy that underpins IA investments across an entire organisation, 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 Intelligent Automation survey include:

Investment in IA technology is strong with 52% of companies confirming investments of more than $10 million; yet investments are imbalanced across functions (mostly on finance and accounting)
There is a distinct correlation between scale and top financial performance. While 64% of the top performing companies surveyed will be scaled by 2019, 59% of poorly performing companies need another 2 - 5 years to achieve IA scale
Overall, only 17% of companies surveyed have scaled up or industrialised IA technologies. Smart analytics was cited as the top most scaled technology, while RPA was the least scaled.
The technology that organisations are experimenting with or piloting the most is AI (36%)
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 half of respondents surveyed say automation will impact fewer than 20% of their staff.

Thomas Erwin, Head of KPMG Global Lighthouse and a partner with KPMG in Germany, said: “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.”

Konstantinos Botsaris, Digital Innovation Senior Manager at KPMG in Cyprus said: “The introduction of Intelligent Automation technologies including Artificial Intelligence in the organisational landscape alone, is not enough. Rather, complementing technology with a long term human-centric strategy and a clear action plan can be a real game changer in terms of getting the most value. This plan should prioritise change management and also ensure that humans have a primary role in both defining and executing it, in this way deriving real benefits for organisations.”



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