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The case for scaling intelligent automation technologies


April 2, 2019   by Jason Contant


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There is a direct correlation between scalability of intelligent automation (IA) technologies and financial performance, a new KPMG International study has found.

Based on a survey of nearly 600 business leaders (including 100 top-level executives) across 13 countries, including Canada, the study found that many enterprises are not scaling IA technologies fast enough to meet desired objectives and returns. However, those that are scaling IA technologies – which include artificial intelligence (AI), advanced analytics and robotic process automation (RPA) – are seeing strong financial performance.

While 64% of the top-performing companies surveyed will be scaled by 2019, 59% of poorly-performing companies need another two to five years to achieve IA scale, KPMG said in the study Easing the pressure points: The State of Intelligent Automation, released Thursday.

Investment in IA tech is strong with 52% of companies confirming investments of more than US$10 million and 1/3 allocating US$50 million or more, yet investments are imbalanced across functions. Finance and accounting are seeing the biggest investments among the industries polled, which included insurance, banking and financial services, automotive and energy, among others.

“By far the highest expenditure levels were for the finance and accounting category, marked by 23 per cent of respondents as receiving investment of slightly more than US$50 million, a spending level that likely reflects ancillary technologies such as cloud services,” the report noted. At the midpoint of investment were core business functions (such as underwriting or mortgage processing). Here, 12% indicated spending above the US$50 million mark.

Overall, only 17% 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. Perhaps not surprising is that AI is the technology that organizations are experimenting with or piloting the most (36%).

Scale remains a leading challenge to achieving goals with AI technologies. Other notable challenged 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.

“Most organizations are actively pursuing IA initiatives but are hindered by a lack of coordination, integration and prioritization,” KPMG said in a release. “Even with RPA – arguably the most mature of the IA technologies – organizations are struggling to achieve scale.”

While investment in and adoption of IA technologies are occurring at a rapid pace, many organizations are struggling to demonstrate significant impact, agreed 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.”