Is your organisation ready to use AI for finance effectively?

AI for finance is no longer a future consideration. According to a recent global AI report, 72% of organisations surveyed in Australia and globally are already using AI in some form across their finance operations. Across Australian organisations, tools that automate reporting, flag anomalies and support scenario planning are either already in use or under active evaluation. But access to AI tools is not the same as being prepared to use them well. That is why Minerva created the AI Readiness Diagnostic, a practical assessment that helps organisations understand whether their data, systems, planning processes and governance are ready to support AI safely and effectively. Once completed, participants receive Minerva’s AI Readiness for Finance & Data Teams Handbook, which explains the seven readiness areas and what to prioritise next.

A recent example shows why this matters. Deloitte agreed to partially refund the federal government after a $440,000 report was found to contain AI-generated errors, including fabricated references and an invented quote attributed to a court judgment. For finance and data leaders, the lesson is clear: AI is only as reliable as the data and governance behind it. Without the right checks in place, AI can turn small data issues into confident but unreliable outputs.

Why does AI readiness matter for finance and data teams?

Finance teams face growing pressure to deliver faster insights, more reliable forecasts and cleaner reporting. A strong AI implementation can help FP&A teams move beyond manual reporting and into more proactive decision support, from variance analysis and scenario modelling to forecasting and report commentary. AI has the potential to improve the way finance teams plan, analyse performance and support business decisions.

However, these benefits depend on the quality of the foundations underneath. Without trusted data, connected planning processes and clear governance, AI does not create clarity. It simply turns fragmented inputs into faster, more confident-looking outputs.

Where does your organisation sit today?

Fragmented. Data is manual, disconnected or inconsistent. Reporting is time-consuming and reconciliation absorbs significant capacity. The priority is improving data quality and consolidating reporting before introducing AI.

Emerging. Some systems are connected and early AI use is possible, but data quality or governance still create limitations. The focus is standardising processes and identifying two or three use cases most likely to deliver near-term value.

AI-ready. Structured data, mature planning processes, trusted reporting and clear governance are in place. The next step is moving from experimentation to systematic implementation across planning cycles and reporting workflows.

What does an AI readiness assessment involve?

An AI readiness assessment looks at whether an organisation has the right foundations across seven core areas: data foundation, planning maturity, reporting visibility, technology architecture, governance, people capability and use case clarity. At Minerva, we approach this as a business question, not just a technology question. The AI Readiness Diagnostic assesses these areas in a structured way. Once you complete it, you receive the AI Readiness for Finance & Data Teams Handbook, which walks through each area in more detail.

One of the most important areas in the diagnosis is use cases tied to measurable outcomes. AI only becomes useful when it is linked to a clear business problem, not just a new tool. For finance and data teams, this could mean using AI to support forecast variance analysis, automate report commentary, detect anomalies earlier, model different scenarios or give leaders faster visibility into performance.

The handbook you receive after completing the diagnostic walks through the other readiness areas in detail, helping you understand which foundations may need attention and what steps to take before scaling AI across finance, planning and decision-making.

How Minerva helps organisations prepare for AI

Minerva helps organisations make their data useful. Our work spans data foundations and analytics, enterprise performance management and technology implementation meaning we can assess AI readiness across all the areas that matter and help organisations address gaps in a practical sequence. As more Australian organisations scale AI, what sets the winners apart isn’t tool access, but readiness. Getting your data, planning and governance right first is the path that makes AI productive instead of risky. It is the one that actually works.