Investment in intelligent automation (IA) technology has failed to deliver fast enough returns, with many projects still stuck in “pilot mode”.
That is according to a global study of nearly 600 businesses with more than $1bn (£0.86bn) in annual revenue, which found a “distinct correlation” between scale and top financial performance.
The findings show that 59% of poorly performing companies still need another two to five years to achieve IA scale, while 64% of top performers will be scaled in 2019.
Just 17% of the companies surveyed had scaled up or industrialised their technologies, despite 52% confirming they had invested more than $10m in projects.
KPMG, which carried out the research, said IA initiatives like advanced analytics and robot process automation are hindered by a lack of coordination, integration and prioritisation.
“Investment in and adoption of IA technologies are occurring at a rapid pace, but many organisations are struggling to demonstrate significant impact,” KPMG US head of IA, Cliff Justice, said.
“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.”
Smart analytics was cited as the top most scaled technology by the companies studied, with robot process automation the least scaled, and artificial intelligence (AI) the most piloted or experimented with.
But it was found that investments in these technologies are imbalanced across functions, with finance and accounting receiving the lion’s share.
Along with scalability, other challenges mentioned by the respondents included uncertainty about the financial investment needed, lack of clarity on accountability, and concerns around governance and risk management.
KPMG Germany partner, Thomas Erwin, 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 are fundamental to successfully scaling up IA across the enterprise.”
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