NZ Mid-sized Businesses Lag on AI Investment Returns

A MYOB-commissioned survey of 500 New Zealand mid-sized businesses shows most have yet to realise meaningful returns on AI investment. MYOB executive general manager Paul Voges said Australian firms are doing a better job at combining the five pillars that drive ROI, leaving many NZ firms only partially prepared. Reported barriers include cybersecurity and data privacy (43 percent), skills and change capacity (40 percent), governance, risk and compliance (32 percent), cloud and integration readiness (30 percent), and a lack of standardised processes.

The survey frames ROI as dependent on five interlocking elements:

• •Processes (standardised, repeatable workflows),
• •Data (integrated, high-quality datasets),
• •AI strategy (clear use cases and prioritisation),
• •AI governance (risk controls, compliance), and
• •Workforce capability (training and change management).

MYOB highlights a practical split: businesses running AI on legacy, siloed systems predominantly report time savings, while organisations with AI embedded in core systems report stronger commercial signals such as revenue growth and improved profit margins.

Mid-market organisations globally face the same trade-offs: a short-term focus on point tooling delivers efficiency but not strategic value, whereas platform-level integration plus governance and people investments unlock commercial outcomes. This survey quantifies those dynamics for A/NZ, showing foundation gaps are the primary constraint, not lack of appetite for AI. For practitioners, the implication is clear: experiments and pilots must be coupled with data plumbing, cloud/integration work, and governance to move from tactical automation to sustained business impact.

Expect vendors and system integrators to push packaged offers that tie tooling to data integration and governance. Follow-up metrics to look for are cohort outcomes by technology stack and time-to-commercial-impact for firms that upgrade integration or invest in workforce capability. "A business with solid data but low workforce capability, or AI tools without the appropriate governance, is not future-ready, it's partially prepared and still heavily constrained," Voges said.