A three-step approach, and why more isn’t necessarily better…
The businesses getting the greatest returns from AI aren’t deploying the most tools or building the most agents. Instead, they’re following a disciplined three-step approach focused on data quality, process improvement and return on investment, according to CPA Australia.
New research from the accounting body found 88 percent of Australian and New Zealand organisations now use AI, but only 11 percent have deeply integrated it into their operations, highlighting a widening gap between adoption and business impact.
“They have a process of moving to AI rather than jumping to an AI solution.”
Gavan Ord, CPA Australia business and investment lead, told iStart the most striking result from the survey is how few organisations are extracting meaningful value from their AI.
“AI adoption is widespread, but the level of usage is shallow,” he says. Many organisations remain in experimentation mode, using AI for relatively minor tasks such as drafting emails rather than embedding it into workflows, decision-making and operational processes.
For many businesses, the stumbling block is working out how to apply it in their business.
CPA Australia’s annual small business survey shows small businesses often lack the time, skills or access to advice needed to realise the full potential of digital technologies.
“There are some deeper issues around the capacity and capability of small business owners in particular to take advantage of artificial intelligence and other digital technologies,” he notes.
The result is a widening gap between businesses experimenting with AI and those using it to drive measurable business outcomes.
The wider Business Technology Report, covering 1,679 accounting and finance professionals across Australia, New Zealand, Hong Kong, Malaysia, Chinese Mainland and Singapore, found a strong correlation between profitability and deeper AI integration.
Across all markets surveyed, 63 percent of businesses reporting increased profitability said AI was widely used across several business functions or deeply embedded throughout the organisation, compared with 50 percent of businesses whose profitability remained unchanged or declined.
“The real benefits come when AI becomes embedded in day-to-day operations, helping businesses improve productivity, efficiency and decision-making.”
Three steps and the case for less
So what can be learned from those companies that are reaping the full benefits of AI?
Ord says rather than rushing to deploy new tools and agents, successful organisations focus first on business processes, data quality and workflow design.
“They have a process of moving to AI rather than jumping to an AI solution.”
The first step is improving the data and data quality. Second is reviewing processes.
“Often they’ll hear from staff ‘oh, we need an AI solution for this problem’ but if they look at their process, sometimes they can improve the process without an AI solution,” he says, noting AI will not make a bad process better.
The third step is assessing whether existing software already contains AI capabilities that have not been activated or fully utilised. Only then do they evaluate whether a new AI solution is actually required.
The approach contrasts sharply with organisations caught up in the current AI gold rush.
Ord cited the example of one business owner who accumulated nine separate AI subscriptions before stepping back and reviewing what they actually delivered. After analysing usage and costs, the owner realised two subscriptions could achieve the same outcome, significantly reducing complexity and expense.
The same lesson applies to AI agents.
While many organisations experimenting with AI are building hundreds, or even thousands, of agents, some of the most effective organisations are doing the opposite.
Ord points to a large business-to-business payments technology company which runs its finance function using just four AI agents. Rather than pursuing scale for its own sake, the company invested heavily in a small number of carefully designed agents that deliver specific business outcomes.
The difference is strategic focus.
Show me the ROI
Businesses generating real value are not measuring success by how many agents they have deployed. They are measuring the return those agents produce.
That return on investment discipline appears largely absent from many AI conversations today, where discussions often revolve around experimentation, proofs of concept and productivity wins.
“Businesses that are successful at using AI are much more focused on the return on investment,” Ord says. “When they go through the process of choosing an AI tool, they have normal return on investment metrics in there.”
Leadership itself is also emerging as a strong success factor, Ord says.
The organisations making the most progress have moved beyond asking whether employees are using AI. Instead, leaders are asking why AI wasn’t used.
“The leader, the business owner, the management is really important to encouraging technology uptake and overcoming sometimes staff barriers to using technology.”
Ord says leaders need to actively use AI, demonstrating its benefits, sharing successes and failures openly and encouraging employees to look for new applications.
Governance as a competitive differentiator
The survey also highlights another challenge confronting A/NZ organisations: Governance.
A quarter of A/NZ employees use AI tools with little or no oversight or guidance.
Ord argues governance should not be viewed simply as compliance or risk management. Well-governed organisations tend to perform better during periods of disruption and change. In an AI-driven environment, governance increasingly becomes a competitive advantage because it enables organisations to scale AI safely while maintaining trust and accountability.
There is also a broader competitive issue emerging.
He says the conversations he has with organisations in China – where there has been a ‘very strong government push to use AI for a number of years – are fundamentally different from those occurring in Australia and New Zealand.
“When we speak to businesses in China, they speak in the past tense of how they’ve applied AI. When we speak to businesses in Australia and New Zealand, they’re speaking in the future tense of what they might do with AI,” he says.
“AI has the potential to make a meaningful contribution to the productivity challenge facing Australia and New Zealand, but only if businesses invest in the capability, governance and processes needed to use it effectively,” Ord says.
Three priorities
His advice for local businesses is straightforward: Deepen AI integration beyond individual productivity gains, establish clear governance with human oversight, and train both employees and managers to use AI effectively.
On the wider question of government support, Ord says there needs to be a substantial increase in incentives for businesses to use AI effectively, along with greater investment in AI literacy training.
He points to Singapore’s S$750 million investment over the past four years to encourage AI adoption among around 150,000 businesses as an example of the scale required.
By comparison, digital support programs in Australia and New Zealand target only a few thousand businesses.
“You’ve got one country that is investing heavily in supporting their businesses and investing in AI and another [New Zealand] that believes if it’s beneficial for business then there’s no role for government in helping,” he says, adding of Australia: “The level of ambition of Australian business policy support is significantly less than in Singapore and that’s one reason Australian small businesses are well behind Asia in terms of using technology, not just AI.”
