Welcome back to Neural Notes, a weekly column where I look at how AI is affecting Australia. In this edition: what can we expect from AI within the business world in 2026? If the past few years were about experimentation, 2026 is where we will (hopefully) see the proverbial AI chickens come home to roost. Because we’re really past the point of novelty, or at least we should be. It’s high time it actually starts being judged on its outcomes. Related Article Block Placeholder Article ID: 330566 Aussie LLM Maincode powers Mastercard’s agent-led payments trial Tegan Jones For small businesses in particular, the conversation is shifting away from whether to use AI at all, and toward how deeply it is embedded, how much risk it introduces, and whether it genuinely improves productivity, margins, or the customer experience. To be fair, AI tools are cheaper, easier to deploy, and increasingly bundled into software that many businesses already rely on. But that accessibility is also exposing new gaps. These include the difference between surface-level use and meaningful change, speed and strategy, and automation that helps and automation that actually creates risk. Here are the AI trends we’re likely to see in 2026 that will matter for Australian small businesses and startups. Smarter business news. Straight to your inbox. For startup founders, small businesses and leaders. Build sharper instincts and better strategy by learning from Australia’s smartest business minds. Sign up for free. * indicates required Email Address * By continuing, you agree to our Terms & Conditions and Privacy Policy. Most Australian SMEs will be using AI (but often in shallow ways) According to the Australian government, 2025 saw a big uptick in AI adoption across SMEs. However, adoption remains heavily skewed toward medium-sized businesses and basic use cases such as reporting, customer or data analysis, and templated email or chat replies. According to government data, AI adoption sat at 82% for businesses with 200-500 employees, 68% for 20-199 and 40% for 5-19. Micro-businesses continue to lag, with fewer than 33% using the technology. Survey data consistently shows that the bigger the business, the more likely it is to experiment with AI and delegate repetitive work to tools, while smaller firms delay adoption or confine it to low-risk admin tasks. Deloitte’s analysis of Australian SME AI maturity highlights this gap clearly: while a majority of businesses may be experimenting with AI, only a small minority (around 5%) are considered “AI-enabled”, meaning they have integrated the technology into central operations and strategy. Related Article Block Placeholder Article ID: 330524 ASIC warns Australians risk AI scams without better financial literacy Jacob Shteyman That makes the term “AI adoption” a misleading headline metric. The more important divide is not between businesses that use AI and those that do not, but between businesses that embed it deeply into workflows and those that don’t. Founders and leaders will face more pressure to prove AI is actually helping the business Across SME-focused commentary, 2026 is framed less as “the year to try AI” and more as the point where owners, CFOs and boards want evidence that tools are saving time, reducing errors or lifting revenue. Many businesses globally (and of varying sizes) say they are adopting AI to manage labour shortages, rising wages, and administrative overload, yet very few have formal metrics, review processes or governance around how tools are used. As AI spreads, scrutiny is likely to come first from lenders, enterprise customers and procurement teams, before it comes from regulators. Founders will increasingly be asked not whether they use AI, but whether they can demonstrate it’s secure, compliant and materially improving margins or growth, rather than just adding another subscription cost. Unchecked automation and AI agents will create new risks Agents were the hot new thing of 2025, but as agentic AI systems are increasingly allowed to act across multiple tools, the scale of potential errors grows. This isn’t to say that agents will automatically be bad. There are already incredibly useful-looking use cases rolling out. But businesses should be cautious of simply setting and forgetting. A single hallucinated output, bad prompt, or misconfigured workflow can trigger knock-on effects across connected systems, a risk that is amplified in small teams without dedicated security or risk expertise. Some of the particular vulnerabilities include prompt injection, data leakage and over-reliance on automation, alongside short-term job displacement risks when re-skilling doesn’t keep pace. We already saw this last year when CommBank backflipped on replacing 45 customer service roles with AI.  Related Article Block Placeholder Article ID: 330479 Shopify merchants face double fees for using ChatGPT checkout Tegan Jones For founders and leaders alike, “moving fast with AI” increasingly means budgeting time for governance, training and contingency planning, not assuming tools are bulletproof simply because they come from large vendors. AI ads will be easier than ever to buy (and waste money on) Large platforms are rolling out AI-first advertising products that auto-generate creative and assets, suggest audiences and optimise spend, lowering the technical barrier for SMEs and startups. OpenAI’s move into impression-based ads and e-commerce features inside ChatGPT adds to a landscape where complex campaigns can now be launched from a prompt rather than a specialist team. But cheap production and automation can just as easily scale mediocrity.  AI-driven ad tools might make it easier to generate large volumes of “good enough” creative, test multiple audiences at once, and keep campaigns running continuously. But they don’t solve underlying issues like weak positioning, unclear value propositions or pricing that doesn’t match customer expectations. In practice, many small businesses may find that using AI to increase the speed and volume of campaigns could return lacklustre click-through rates, conversion rates and return on ad spend. Human work will become a differentiator Creative industry forecasts point to a counter-trend to the AI “ad-pocalypse”, with some brands leaning into visibly human, imperfect or local work as a point of difference. Early examples of brands publicly pledging not to use AI in ads, or explicitly celebrating film, handwriting and rough creative, have driven strong engagement from audiences fatigued by synthetic-feeling content. That same dynamic is starting to appear inside organisations. As generative tools take over drafting, summarising and routine analysis, judgement, taste and domain knowledge become more visible and valuable. Related Article Block Placeholder Article ID: 322896 AI spokesperson helps Vodafone ads hit two million views Tegan Jones 1 Some employers are even experimenting with supervised or AI-free tasks to assess how candidates think without a model in the loop. OpenAI will face more pressure than ever OpenAI is under growing pressure to convert massive usage into sustainable revenue. We’ve seen this in the last few months with its cheaper ‘Go’ tier, ads rollout and early e-commerce features (and upcharges) such as instant checkout and shopping research tools. This is unfolding alongside a broader market dynamic where Nvidia has become the most heavily weighted stock in the S&P 500 at 7.27% at the time of writing. It’s followed closely by other big tech companies that are pushing hard on AI — Apple, Microsoft, Amazon and Alphabet (Google) – and are customers of Nvidia.  This points to a firm expectation that AI demand and compute spending will remain elevated. It’s worth remembering that OpenAI is still very much in the red. The company’s own recent forecast predicted a US$14 billion loss in 2026, and CEO Sam Altman recently met with Middle Eastern investors in the hope to raise US$50 billion. If flagship AI providers struggle to make their economics work, it could have a negative effect on the broader market. For Australian SMEs, the downstream effect is more immediate. What would happen to those businesses overly reliant either directly on ChatGPT or the broader OpenAI ecosystem if something dire were to happen? 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