Half of finance artificial intelligence projects to be cancelled by 2024

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Jarvis secures funding from Bestvantage Investments, Hem Securities
Jarvis secures funding from Bestvantage Investments, Hem Securities

CFOs, to meet their digital transformation objectives, face major barriers to scaling up the use of artificial intelligence in-house and will increasingly turn to business process outsourcing (BPO) solutions

Half of current finance artificial intelligence (AI) deployments will be either delayed or cancelled by 2024 as the banking and financial institutions adopt AI-driven technologies globally, a new report has forecast.

The use of business process outsourcing (BPO) for artificial intelligence will rise at the same time to 40 per cent from six per cent within two years, according to Gartner.

CFOs, to meet their digital transformation objectives, face major barriers to scaling up the use of artificial intelligence in-house and will increasingly turn to business process outsourcing (BPO) solutions, the report noted.

“While finance departments have made reasonable progress in laying the groundwork for AI, the challenges come when attempting to scale up solutions that can manage the complexities of function-wide use,” said Sanjay Champaneri, senior director analyst in the Gartner Finance practice.

“The upfront costs of building scalable infrastructure in house, and the over-reliance on stretched citizen developers, will lead many CFOs to rethink their current strategies,” he mentioned.

For deploying such technologies, digital automation in finance often fails to meet the expected benefits outlined in business cases.

Much of this is down to a lack of truly functional automated processes and a significant proportion of automation work fails and is rerouted to a human for manual input.

Finance departments, without correcting for this state of “fake automation”, will struggle to scale automated solutions, such as artificial intelligence, effectively across the function, the report said.

Champaneri said, when attempting to scale up their artificial intelligence processes across the functions, finance departments will face three key barriers.

These are costly upfront infrastructure, lack of bandwidth among citizen developers and skill-gaps among citizen developers.

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