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Intelligent automation spending to hit $232bn by 2025

Technologies such as artificial intelligence, robotic process automation and machine learning could help traditional enterprises gain ground on digital-first giants

Business spending on artificial intelligence (AI), machine learning (ML) and robotic process automation (RPA) technologies will see explosive growth over the next few years, with about half of enterprises using the technologies at scale by 2025.

According to research by KPMG, enterprises will spend $232bn on the technologies in 2025, compared with $12.4bn in this year.

In its Ready, set, fail? Avoiding setbacks in intelligent automation race report, KPMG also revealed that enterprises have high hopes for these technologies, but are not ready to drive these intelligent automation (IA) technologies at any scale.

According to the study, which underpins the report, 37% of enterprises are currently examining the potential of IA technology, 24% are running proof-of-concept projects, 12% are using IA selectively, while 13% are not using it at all.

But IA uptake is expected to accelerate over the next three years, with all enterprises using the technology to some extent – 49% using it at scale, 29% using it selectively and 11% running proofs of concept.

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The KPMG report said digital-first companies already had a distinct competitive advantage through IA technologies, but other companies, with the right strategies, could use it to regain lost ground.

“Not all companies can emulate Amazon’s one-click experience with its complexity and checks-and-balance built into a digital supply chain,” said KPMG. “Companies can, however, close these gaps if they act quickly, understand the urgency, and define and execute a comprehensive IA strategy – one that looks not just at technology, but at business and operating model opportunities and constraints.”

But according to KPMG director Don Ryan, this is currently a challenge for traditional businesses. “The surprising part of the survey is not that managers’ expectations are high for IA, but rather that their organisations’ readiness to implement it is low,” he said.

A number of reasons for reduced readiness were highlighted in the report. Two-thirds of enterprises said a lack of in-house talent was part of the reason, and half cited the struggle to define goals and objectives. The biggest obstacle, according to 33% of respondents, was management concerns over IA’s impact on employees.

Despite the lack of preparedness, money is being made available for the technologies, with investment in intelligent automation expected to increase in the next three years.

According to the report, 32% of organisations had approved more funding for robotic process automation and 40% said they would increase spending on artificial intelligence by at least 20% over the next three years.

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