Australian companies’ investment in artificial intelligence (AI) is increasing rapidly but the biggest growth is coming from those that are already using the technology, according to a new analysis warning that a widening AI capabilities gap could leave many firms behind.
Although 39 per cent of the 950 companies analysed in a recent Dataiku-sponsored IDC InfoBrief said they were using AI during 2021, that percentage was the same as during 2020 – suggesting that the technology’s growth has stalled.
Existing users said they would increase their AI investments by an average of 34 per cent annually through 2025 – suggesting, IDC found, that “having captured low-hanging opportunities, they are now implementing use cases of larger scope and complexity.”
Around 80 per cent of AI users said they had applied the technology to more than five use cases, with around 30 per cent improvement in areas such as employee productivity, customer experience, innovation speed, risk management, product and service differentiation, and better intelligence about their ecosystem.
Retail businesses, for example, are using AI to optimise their operations, improve customer service, and improve decision-making around merchandise stock.
Banks are leaning on AI to help with financial risk management, cyber security threat detection, and automated compliance management.
“By 2024, 50 per cent of our use cases and analytics will include AI to some degree,” said Craig Turrell, head of P2P within the Digital Centre of Excellence at Standard Chartered Bank.
AI is seen “both as a peer that is helping us to explain and ask questions of what’s next and why things happened, and also as a manager that helps us organise our work and tells us where to focus our questions and explanations…. [Now] we need to put AI in the hands of the masses of the organisation.”
Despite its value, however, IDC found that fewer than 40 per cent of companies had an enterprise-wide strategy to coordinate their investments across the company.
ANZ businesses lag regional leaders in key metrics such as IDC’s AI capability score – 3.0 out of 5 overall, compared to 3.2 in Japan and 3.3 in China – and data readiness score, an aggregate measure of data maturity that actually fell between 2020 and 2021.
Fully 59 per cent of ANZ companies said they didn’t have enough quality training data to make their AI function as effectively as they would like.
To make the most of AI, IDC recommends, companies need to address maturity in four key domains – data, people, technology, and process – and to speed the iterative process that is often training up to 50 task-specific AI models at once.
“AI projects cannot be managed in an ad hoc manner,” the analysis warns, encouraging data scientists to collaborate with subject matter experts to ensure AI projects are energised by cross-functional teams.
“A systematic approach to model development and management over their life cycle is essential and becoming more important with upcoming AI regulations.”
Laggards are risking their competitiveness
Even as early adopters double down on AI, fully 61 per cent of businesses – usually smaller ones – still have not invested anything in AI.
Continued lack of investment often comes down to what a recent CEDA analysis of executive workshops highlighted as a “default ‘yes’ or ‘no’ to AI”.
Amongst those “less advanced in the use of AI,” the analysis noted, “was a tendency towards polarised approaches to considering potential risks, the management of these risks, and broader expectations.”
Lourens Swanepoel, Australia data and AI lead with technology consultancy Avanade, believes executives need to actively improve what he calls the company’s AI-Q (AI knowledge and literacy) if they ever hope to tap AI’s benefits.
AI projects “often start off with big, grand intentions but there is too much of a short-term, tactical view taken because it’s driven by just one use-case in the organisation,” he told Information Age, “and the challenge is how to scale it from there.”
“We’ve seen that in companies that understand the specific value cases of AI and data as it applies to their functional departments, the organisation has focused on that and is really successful in terms of adoption of AI,” Swanepoel said.
“Without that, you’re forever going to be stuck in this conundrum where IT is trying to educate the business and fly the flag for AI, because it’s seen as a technical tool and not a strategic capability within the business.”