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AI solutions working for more than half of A/NZ enterprises

AI solutions working for more than half of A/NZ enterprises

Conversational AI, predictive analytics causing noteworthy changes

Credit: ID 94297557 © Jakub Jirsák | Dreamstime.com

Over half of Australian and New Zealand enterprises that have implemented artificial intelligence (AI) solutions have seen changes to their business models, new research has found.

Conversational AI and predictive analytics in particular are causing changes across the customer care and traditional maintenance business models, respectively. 

This is according to IDC’s AI in Australia and NZ: Viable Use Cases Driving Adoption report, which found the main drivers behind the investment of AI technology to be automation for productivity, customer satisfaction, business agility and accuracy.

Associate market analyst Liam Landon claimed organisations that shift workloads to AI-powered solutions end up with systems that can make decisions and act faster than their employees.

“Artificial intelligence is augmenting the employee workforce, driving changes to business models to capture real returns on improved productivity, satisfaction, agility and accuracy,” he said.

Furthermore, 40 per cent of A/NZ organisations plan to deploy an AI initiative by the end of 2020, and while COVID-19 has stemmed budgets somewhat, nearly one-third of organisations expect their AI-related budgets to increase in 2020.

IDC research pointed towards AI's adaptive nature towards market changes and customer enhancement capabilities as reasons behind why organisations are investing in AI solutions.

"The additional benefit of business agility gives organisations the ability to be more flexible to changes in the market, unlocking greater potential to stay ahead of competitors. This is especially key, given the recent stress many workplaces have been placed under due to COVID-19," IDC claimed.

A common use of AI in the region, according to the report, is conversational AI for providing consistent and accurate responses to simple queries, freeing up frontline staff to help with more complicated questions.

Meanwhile, more complex uses that utilise larger data sources to assist diagnoses is expected to grow over time with future advancements in the technology. This is particularly expected to occur in the healthcare industry.

AI recommendation systems are also being used for Australian and New Zealand organisations for transport route optimisation, detecting driving offences and determining effective environmental protocol actions.


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