AI is moving quickly, but for finance teams, the real opportunity is not simply adopting another tool. The real value comes from using AI inside trusted business systems, connected to governed financial data and shaped around the decisions finance teams need to make every day.
Hosted by Leverage Technologies in partnership with Sage, this AI Masterclass unpacked how Sage Intacct, intelligent finance agents and connected ERP data can help finance leaders reduce manual work, improve visibility and adopt AI with stronger controls around accuracy, permissions and data governance.
AI in ERP Needs Business Context, Not Just Technology
A key message from the Masterclass was that AI should be applied to specific business outcomes, not introduced as a standalone technology project. Finance teams are already surrounded by data, reports and workflows. The value of AI comes when it is connected to the right process, grounded in trusted ERP information and governed by the same permission structures that control what each user should be able to see and do.
The insight for finance leaders is that AI does not need to replace existing financial controls to be useful. It should strengthen them by reducing repetitive work, surfacing exceptions earlier and helping teams focus on higher-value analysis. The process for improving uptake of AI in your ERP can include:
- Starting with business processes and outcomes before choosing tools
- Using deterministic business logic where rules-based automation is enough
- Applying generative AI where natural language, reasoning and broader context add value
- Keeping humans involved in approval, validation and final decision making
Financial information is highly sensitive, so AI needs the right controls before it is used with ERP data. The better approach is to use AI that understands business context, respects user permissions and works from trusted ERP information rather than disconnected spreadsheets or uncontrolled tools. As Leo Dreyer speaks about in the video; “AI is only as useful as the context and data that you give it”.
Sage Intacct Brings AI Into the Flow of Finance Work
For Sage Intacct customers, the practical advantage is that AI capability is being brought into the finance system where work already happens. The Masterclass demonstrated how Sage Copilot and finance intelligent agents allow users to interact with financial data using natural language. Instead of manually searching through lists or building reports from scratch, users can ask questions, view analysis, explore supporting detail and understand how the system arrived at an answer.
In practical terms, this means a finance user can move from asking a question to seeing supporting analysis without leaving the system of record. Outstanding supplier invoices, AP priorities and simple financial investigations become easier to explore, while the prompt library helps users understand how to ask more useful questions. For Example, you can now ask; “List AP bills over $3,000 for this month”. The value is not just speed. AI embedded inside the ERP can work with existing user permissions and trusted financial data, which gives finance teams a safer and more practical starting point than sending sensitive information into disconnected AI tools.
Practical AI Use Cases for Finance Teams
The strongest use cases are not abstract. They sit inside the finance tasks that teams already complete every day, where small improvements in speed, accuracy and visibility can create meaningful operational value.
Accounts payable automation is one of the clearest starting points. AI and machine learning can help capture invoice data, match invoices against purchase orders and support three-way matching. The value for finance teams is less time spent on manual invoice handling, fewer processing bottlenecks and stronger control over supplier workflows. Outlier detection shows a different kind of value. By reviewing journal entries and flagging anomalies before they are posted, AI can help finance teams identify unusual transactions earlier, reduce the risk of errors and protect confidence in the numbers before reporting is finalised.
From Embedded AI to Connected Agentic Workflows
Embedded Sage Intacct AI provides a strong starting point, but the opportunity is the ability to extend trusted ERP data into broader business workflows without losing control of access, permissions or context.
MCP connectors allow external AI tools to interact with ERP data in a more controlled way. The value is not simply that users can ask questions in natural language; it is that those questions can be answered with current business data, scoped to the user’s permissions and connected to real financial or operational processes. The LevCore platform demonstrated how deterministic ERP data and AI-driven analysis can work together. The important insight is that AI can help generate dashboards, analyse ageing, identify customer patterns and prepare board-style finance views, while the underlying data remains grounded in the ERP.
This creates practical opportunities such as:
- Asking natural language questions about cash position and financial performance
- Creating refreshable accounts receivable ageing dashboards
- Identifying customer and product patterns that may reveal upsell opportunities
- Drafting transactions for human review before pushing them into the ERP
- Generating board-style finance packs from trusted ERP data
The common thread across each example is control. AI can support analysis, reporting and workflow automation, but permission-aware access, audit history and human validation remain essential when the work affects financial or operational data.
Responsible AI Adoption Starts With Governance
AI governance is not a compliance afterthought. For finance teams, it determines whether AI can be trusted with sensitive business information, financial reports, supplier data and customer records. One of the biggest risks is shadow AI, where employees use personal or free AI tools with company information without understanding how that data may be retained, processed or used. For finance teams, the risk is higher when information includes P&L data, customer records, supplier details or confidential management reports. The value of good governance is confidence. Businesses can move faster with AI when staff know which tools are approved, what data can be used, who is allowed to access it and where human review is required before outputs become decisions or transactions.
Before scaling AI across finance and operations, organisations should be clear on:
- Whether data is retained, trained on or processed outside Australia
- The difference between where data is hosted and where AI inference is processed
- How user permissions are applied when AI accesses ERP data
- How outputs are reviewed before decisions or transactions are completed
- Whether the business has a clear AI policy and approved tools list
The objective is not to slow AI adoption. It is to make adoption safer, more useful and better aligned with the way the business manages sensitive information.
Where Finance AI Is Heading
The future of finance AI is less about replacing finance teams and more about changing the way work is orchestrated. As AI removes more repetitive work, finance teams can spend more time reviewing exceptions, interpreting trends and guiding business decisions. Human judgement remains critical, especially when recommendations need to be validated or actions affect financial records. A practical starting point is to choose one focused use case, prove the value, confirm the governance model and then expand. This helps finance leaders build confidence without trying to transform every process at once. That approach allows finance leaders like CFOs to move from curiosity to controlled adoption, building confidence in AI while keeping business outcomes, data protection and human accountability at the centre.
If you have questions about AI within your ERP or compliant AI use, please get in touch.
Brett has more than 20 years of business software sales and company management experience. Brett has been involved in more than 300 ERP projects. His passion is customer satisfaction, making sure every client is more than just satisfied. Brett wants our customers to be driven to refer their friends and peers because we offer the best services and technology available and because we exceeded their expectations.