I recently reviewed the November MYOB Mid Market report, which surveyed 506 businesses across Australia and New Zealand. The key findings are encouraging: these organisations are optimistic about the future and eager to invest in innovation for growth. Both Australian and NZ businesses list data and AI technologies among their top five investment priorities for the next five years.
But what does "prioritising data and AI" really mean?
Based on our experience working with this market segment, we see consistent trends:
- Strong preference for off-the-shelf solutions that are easy to support
- Modularity is important given diverse software ecosystems
- Legacy software requiring integration focus
- Small IT teams centred on core application support (especially ERP) that prefer short, targeted expert services delivering rapid value
With that context, here are some practical recommendations for mid-market organisations looking to act on their data and AI ambitions, split into short-term and mid-term horizons.
Short-Term Recommendations
Boost Specific Functions with AI-Enabled Apps
A practical starting point is investing in off-the-shelf AI software that enhances specific functions. Generative AI improves productivity for information workers, enabling companies to accomplish more with existing resources. Examples include:
- Microsoft 365 Copilots: Expedite document creation, generate email follow-ups from meeting transcripts, and provide productivity enhancements across the suite
- Adobe Firefly: Accelerates creation of assets by creative teams
- Jummbo: Shortens the time required to prospect new customers
- AI-generated proposal builders, an emerging solution category worth watching
For organisations already using Microsoft 365, Copilot is often the lowest-friction entry point. It operates within the applications teams already know and respects existing security boundaries. Our Copilot training programme is designed to help teams get practical value from these tools quickly.
Publish Internal Chatbots
Many mid-market organisations have intranets and document stores containing valuable information that employees struggle to locate. Creating and publishing internal chatbots has become straightforward and can significantly improve user experience and productivity.
A word of caution: security considerations are critical. Document access must be scoped carefully to prevent sensitive information from reaching unauthorised personnel. Getting the permissions model right from the start avoids problems as usage scales.
Increase Team Awareness and Skilling
One of the most overlooked steps is simply encouraging teams to understand emerging technologies, particularly generative AI, so they can identify competitive advantages. This can be achieved through:
- Hands-on experience with new off-the-shelf AI apps
- Consulting existing vendors about their AI roadmaps
- Accessing free online training like Salesforce Trailhead and Microsoft Learn
- Considering short courses or bespoke training from institutions like RMIT Online
We have found that organisations where leadership actively supports AI skilling see faster adoption and better outcomes. It does not require a large budget, just a deliberate effort to build awareness.
Mid-Term Recommendations
Automate the Back Office
As AI tools mature, organisations can deliver "agentic experiences" using generative AI, accelerating workflows that were previously slowed by document review or creation stages. Microsoft's Copilot Agent and Azure AI Agent Service announcements make agentic workflows increasingly achievable.
Consider a practical example: auto-approving supplier PDF terms received via email if they comply with your legal team's criteria, and routing exceptions for human review only. This type of targeted automation can remove significant friction from procurement and compliance processes without requiring a full digital transformation programme.
Uplift Your Data Estate
While cloud data warehouses remain relevant, the industry is moving toward enriching data with AI and incorporating real-time feeds. This represents a transition away from traditional data warehouses toward integrated AI and analytics platforms built on the Apache Spark ecosystem. Depending on budget and sophistication level, Microsoft Fabric and Databricks are both strong options worth evaluating.
The key consideration for mid-market organisations is starting with a clear use case rather than attempting a broad data platform migration. Identify the specific business questions your current reporting cannot answer, and work backward from there.
Uplift Your Own Apps and Customer Experiences
Three examples illustrate the types of innovation now within reach for mid-market organisations:
Self-service customer experiences: Outdated IVR systems have long been a source of customer frustration. Advanced self-serve voice bots can now handle inquiries efficiently, drawing on comprehensive business process and policy knowledge. They can take action without human intervention, such as informing customers of item stock locations and placing holds.
AI-enhanced workflows: CRMs have traditionally offered customer sentiment analysis but struggled to go beyond basic metrics. With generative AI, organisations can now summarise long-form text into concise, actionable insights. Coles, for instance, uses AI to summarise customer feedback for store managers, turning large volumes of unstructured data into practical intelligence.
High-quality data insights: Data pipelines have traditionally focused on ingesting data into reporting platforms. These pipelines can now feed insights back into operational databases. For example, a logistics provider could use AI to forecast shipment arrivals and display that information in customer portals, or trigger proactive notifications based on estimated time of arrival.
Where to Start
The MYOB report confirms what we see on the ground: ANZ mid-market organisations recognise the potential of data and AI, and they are ready to invest. The challenge is often knowing where to begin and how to move from intention to practical outcomes.
Our recommendation is to start with the short-term actions, particularly AI-enabled apps and team skilling, because these build capability and confidence for the more ambitious mid-term initiatives. Each step informs the next, and the compounding effect of early wins tends to accelerate progress across the organisation.
If you would like to explore how these recommendations apply to your organisation, our AI Accelerate Workshop is designed to help mid-market teams identify and prioritise the AI opportunities that will deliver the most value for their specific context.
Ready to put your data and AI priorities into action?
ANZ mid-market organisations are investing in data and AI, but turning priorities into outcomes requires a clear starting point. We help teams identify the right opportunities and move from planning to delivery.