Australia and New Zealand’s mid-market brands are ahead on AI adoption. But enthusiasm isn’t translating to ROI. Intuit Mailchimp explains why intent matters more than installation.
Mid-market brands across Australia and New Zealand are at a crossroads. They’ve outgrown start-up scrappiness, but don’t yet have the deep pockets or teams of enterprise players.
According to Intuit Mailchimp’s The Marketing Equaliser report, many are still operating with lean teams; about half (51%) of mid-market businesses globally have marketing teams of fewer than 10 people. A third of B2B marketers are juggling more than seven platforms in their stack, and artificial intelligence (AI) is now central to that mix.
The good news is that, against this backdrop, Australia and New Zealand are tracking ahead in many ways. Enthusiasm for AI may be aglobal trend, but here confidence is high, headcount is rising, and local brands are using technology to deliver real customer value. About 86% of ANZ marketers expect to grow their teams over the next year, higher than peers in the UK and the US. Meanwhile, 44% say they are widely deploying AI, compared to around a third globally.
Still, most teams are stuck in partial AI mode; running fragmented pilots, testing isolated tools and layering yet another platform into an already busy stack. What’s missing is a clear roadmap that ties AI to measurable business outcomes. The next competitive advantage belongs to those who learn from experimentation to operationalise AI with intent, aligning it to strategy and embedding it into workflows to unlock efficiency and effectiveness.
Start with the real marketing impact
While 44% say they’ve widely adopted AI, more than half (56%) still have work to do. For ANZ’s mid-market marketers, the path forward doesn’t require a wholesale reinvention, but a staged, strategic roadmap.
Before implementing AI at scale, look across your organisation and campaigns to identify where AI can make the biggest difference. Use data across the funnel, from brand awareness and lead generation to acquisition costs and retention, to find gaps. Bring in perspectives beyond marketing, including commercial leaders, customer service teams and product managers, to surface issues and opportunities you may not see on your own.
Once you have a long list of needs, narrow it down to two or three high-impact business problems where improvement would meaningfully influence growth. That becomes your starting point.
Build intentional foundations for easier experimentation
Having identified the key challenges, the next step is to understand your baseline. For example, how many platforms you use and where they overlap, how clean and accessible your data is, and how strong AI literacy is across your team.
Many ANZ mid-market brands are working with a lean team handling a growing list of tools, in a labour market where 43% of marketers struggle to find people with the right skills. In that environment, finding extra time to upskill is a real challenge.
Functional AI practices recognise those realities. It is less about implementing flashy pilots and more about quietly and consistently improving how your team works and how your customers experience your brand.
This is also where leadership matters. Appointing AI champions inside your marketing team, people who are curious and close to the work, helps guide experimentation, share learnings and set realistic expectations about what AI will and won’t do.
Match AI use cases to measurable marketing goals
AI experiments and integrations lead to more positive results when they are tied to clear objectives. That could mean using AI tools to reduce acquisition costs on social media or applying them to drive greater personalisation as part of an omnichannel approach.
For mid-market brands, email and SMS are often the most controllable and cost-effective channels; this is where AI can have an immediate and measurable impact. AI can help send more relevant content at scale by supporting more refined personalisation based on previous engagements and optimising send times and subject lines. These improvements can accelerate the impact mid-market companies can have on their category and customers.
Focusing energy on these owned channels first is a practical place to begin. It builds a business case with clear metrics by showing teams the tangible value of AI in their day-to-day work, and creates a foundation you can extend into other touch points like paid media and CRM.
Iterate, measure and scale what works
AI tools become more useful the more you use them; they learn from data over time. Increasingly, AI will shift from being seen as content generation aid to a strategic partner that helps design, execute, and continuously optimise your desired outcomes.
That makes iteration crucial. The goal is not to roll out AI everywhere all at once; it’s to start by proving value in priority areas, then scaling those wins across channels and segments.
Mid-market businesses in ANZ face a double challenge: fewer customers and often lower baseline brand loyalty compared to their larger enterprise peers. At the same time, they have the agility that many larger organisations envy. When implemented practically and strategically, AI can tilt that equation in their favour and help them punch above their weight.
ANZ’s mid-market marketers have already shown they’re willing to adopt early. The next step is to turn that early momentum into durable edge by balancing ambition with discipline, and making AI an equaliser in 2026 and beyond.
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