Australian SME AI report estimates $93B opportunity

An Australian report released on 22 October 2026 estimates that wider use of AI by small and medium businesses could add up to $93 billion in annual economic value. The Tech Council of Australia’s research listing frames that as a potential outcome of greater adoption over the next five years, not value businesses have already captured.

That distinction is the story for owners deciding whether to spend money on AI tools. The report’s other headline figure, $136,000 in potential annual productivity value for an average SME, describes a move from no AI use to broad adoption, according to the Tech Council. It is not a forecast of the cash savings an individual company will see after buying a subscription.

What the new estimate says

The Tech Council calls its report Accelerating AI Impact for Small and Medium Enterprises. Its research page says Delwood Advisory undertook the analysis in partnership with Employment Hero, Deputy and Google. Google’s launch announcement says 25% of Australian SMEs currently use AI, while 5% use it broadly. These are figures attributed to the research and announcement, not measurements made by Dailytech.

Google reports 25% using AI and 5% using it broadly. Its announcement does not define the survey criteria for those categories. The $136,000 scenario concerns the second, broader state compared with no use at all. It should therefore not be applied to every business within the 25% group, or to every company that signs up for a tool tomorrow.

Google points to construction, hospitality and retail as examples of sectors where tasks such as quoting, roster scheduling, ordering and payroll compliance might change. That list is useful for choosing a workflow to examine. It does not show which task produces the largest return at any particular firm. The linked announcement does not provide a company-specific payback calculation, and we have not independently verified the report’s underlying model.

Why the number is different from an earlier AI forecast

Readers may remember a much larger Australian AI figure. In July, Google described a Public First report that put a potential national economic dividend at $240 billion and discussed sectors including healthcare, education and financial services. The new Tech Council study is specifically about SMEs and a five-year adoption scenario.

Those numbers answer different questions. The $93 billion estimate is not a revision to the $240 billion figure, and subtracting one from the other would not reveal an “unclaimed” share. The studies have different scopes and stated assumptions. What is new here is a narrower question: how much value greater AI use among smaller firms might create, and how far current use is from broad adoption.

What a business owner can actually do with it

The national estimate can justify a closer look at AI, but a local decision needs local evidence. One practical way to start is to choose a repeated task with an observable output: for example, producing a first draft of a quote, summarising customer questions or checking a routine document. This is an editorial measurement suggestion, not a method endorsed by the researchers or a test Dailytech has run.

First record how long the task and its corrections take without the tool. Then run a limited trial and record the same measures, including time spent checking the AI output. Count the subscription cost, setup and training time, and any extra review required to reach the same quality. Compare completed, usable work rather than the speed of a first draft. If the process handles customer or employee information, check who can access the account and its records before entering real data; our guide to AI chat history and privacy explains questions to ask about consumer chat tools.

The result may be a time saving, a quality improvement, both, or neither. Even saved time is not automatically cash returned to the business: it depends on what staff can do with that time and whether other costs rise. That is why the report’s modeled “productivity value” and a firm’s realised financial return should be kept in separate columns.

For a broader rollout, identify an owner for each process and a way to catch mistakes. Our article on why AI projects stall covers adoption and management problems beyond the tool itself. If a workflow asks AI to supply sources, use the checks in our AI citation guide before those references reach customers. When a paid tool becomes necessary, compare subscription plans against the task you measured rather than the national headline figure.

What remains unknown

The public announcements establish the report’s headline scenarios and adoption figures. They do not establish that any one SME will obtain $136,000, that the modeled $93 billion has already been realised, or that buying a specific AI product causes either outcome. This article has not assessed the full report’s methodology or reproduced its calculations, so it does not make claims about sample design, uncertainty ranges, or results by sector.

The useful takeaway is narrower than the headline number. Australian SMEs have a new estimate of what widespread AI adoption could be worth. Owners can decide whether that possibility applies to them by measuring one workflow, its correction costs and its output quality before committing to wider use.