If 2023 was the year AI – especially generative AI – captured global attention, and 2024 the year of experimentation, then 2025 will be the year businesses move past exploration phases to put in place plans to unlock real, measurable value from finance artificial intelligence.

Focusing specifically on the finance function, AI adoption is on an upwards swing. In 2024, 58% of finance functions leveraged AI, a notable rise from 37% in 2023. In fact, 75% of Australian companies say they are currently using or piloting AI in financial reporting, with this figure expected to hit 100% within the next three years.

As the initial excitement around AI fades, it’s becoming evident that the real value lies in embedding AI into core financial processes.

Think AI applications in finance like financial reporting, budgeting, forecasting, and auditing – all areas where AI can automate once-human tasks, improve data accuracy, and provide real-time insights. In the years ahead, AI won’t just be about cutting-edge tech promising transformation. Instead, it will be about seamlessly integrating AI into the systems we already rely on, making them smarter, more efficient, and responsive.

You can expect vendors to release increasingly intelligent and seamless tools too, ones that enable businesses to integrate AI directly into their existing workflows – so much so that AI will become almost invisible, working quietly in the background to offload the time-consuming load once shouldered by finance teams.

With the hype of previous years giving way to a focus on practical implementation, the question becomes – how do we actually achieve this?

Let’s explore the practical steps for embedding AI into finance workflows, so you too can turn AI’s potential into real-world results.

Start with clear objectives

Before diving into the technicalities, you need to understand what AI can do for your specific business needs. So, start by defining clear objectives for how AI can improve your finance workflows.

• Are you looking to automate routine reporting tasks?
• Improve accuracy in forecasting?
• Enhance real-time data analysis?

By setting these goals up front, you’ll have a clear sense of direction and avoid getting caught up in flashy tech that doesn’t align with your objectives.

Assess current systems and data infrastructure

You can’t embed AI effectively if your existing systems aren’t up to scratch. Take stock of the tools and platforms you’re currently using within your finance function. Ask yourself what’s working well and what’s holding you back? Pay particular attention to your data quality and availability – AI thrives on good data, so ensuring your data is clean, structured, and accessible is a prerequisite for building a strong foundation for AI integration.

Identify high-impact areas for AI integration

Once you’ve defined your objectives and assessed your systems, the next step is pinpointing where AI will add the most value. Think about areas where repetitive tasks can be automated or where real-time insights can make a significant difference, such as in budgeting or financial reporting. Prioritise these AI use cases in finance strategies to get the most impact out of your AI investments. It’s better to start with a small but impactful implementation, than to try and tackle everything at once.

Choose the most fitting solutions beyond AI

Not all AI tools are the same, and this is where things get interesting. As AI adoption becomes more mainstream, vendors are releasing tools specifically designed to integrate seamlessly into existing finance workflows. Whether you’re looking for automation in financial reporting, smarter budgeting, or predictive analytics, there are a range of tools and even entire business suites – that will fit around your current systems and are scalable for the future.

For example, cloud ERPs like NetSuite come with a range of finance-first AI features that can really level up your financial processes. Or, if you’re working with smaller accounting platforms, solutions like Xero or QuickBooks also offer some lighter AI-driven features that help streamline tasks like invoicing, reconciliation, and cash flow forecasting. This step is really about understanding what you need now and where you want to go. The process of evaluating AI tools is just one part of the broader decision around selecting the right systems. You need to think about how these tools will fit with your existing infrastructure, how they’ll scale as your business grows, and how they’ll serve your team’s evolving needs.

Build internal expertise and partnerships

When integrating AI into finance workflows you do not want to rely on external vendors or consultants alone. Invest in upskilling your finance team with basic AI knowledge and data literacy. This way, you’re not just outsourcing everything, you are empowering your team to make informed decisions about AI’s role in your organisation – a move that will pay off in the long run.

Implement gradually, scale as you go

Rome wasn’t built in a day, and neither will your AI-powered finance function be. Begin by embedding AI in one or two key areas where the impact is most likely to be felt quickly. This could be automating routine reporting tasks or using optical character recognition for processing invoices. Once you’ve got those initial capabilities dialled in, you can scale up to other parts of your finance function. Taking a gradual approach means you’re not throwing everything at once, and you can quickly adjust as you go.

Focus on continuous improvement

Any new capability will require continuous monitoring and refinement. As your team gets more comfortable using AI, regularly review how well it’s meeting your objectives.

• Are the tools performing as expected?
• Are they providing the insights you need?

Get feedback from your team and refine the system based on their experience. This cycle of testing, learning, and improving will ensure your AI investment continues to deliver value in the long run.

Ensure data governance and compliance

Anyone working with numbers will know not to overlook the importance of AI governance in finance. AI relies on data, and you will need that data to be accurate, unbiased, and compliant with regulations. Establish clear policies around data usage, protection, and access, and make sure your AI tools are aligned with these policies. With finance being a highly regulated space, this step is essential for mitigating risk and maintaining trust in your systems.

Measure success and demonstrate value

Finally, you will want to track the success of your AI initiatives. Use KPIs to measure the impact on your finance function – whether that’s through increased efficiency, cost savings, or faster decision-making. Don’t just measure outputs (like time saved) – focus on the real business outcomes (such as financial accuracy or better insights). Demonstrating clear, tangible value will help secure ongoing investment in AI and build confidence across your organisation.

EBOOK: Building an AI in finance strategy

A business leader’s guide to unlocking AI’s potential in finance.

Curious about what AI can do for finance? Download our free eBook to discover practical strategies and real-world insights on finance-led AI initiatives that will transform the finance function into a true powerhouse of data-driven insight and efficiency. Download your copy >

Ready to reinvent finance with AI?

For finance, AI’s real impact isn’t in the grand gestures, but rather in quietly transforming the way finance functions operate. By following a clear strategy – defining objectives, optimising systems, and scaling gradually – you can select and finetune the tools needed to embed AI seamlessly into workflows, turning AI’s potential into measurable results that redefine efficiency and decision-making.

Learn more:

• AI in finance: Your guide to building a future-ready financial function
• Why AI skills will be essential for your finance team in 2025 >
• The powerful ways AI is transforming cloud ERP: a practical guide >
• The AI capabilities hidden in cloud ERP >
• The newest and most powerful NetSuite AI capabilities >
• All the biggest NetSuite AI enhancements announced at SuiteWorld >
• NetSuite EPM and the stellar rise of AI in finance >
• Infographic: What AI really means for the finance function in Australia >