How to Move Beyond the Buzz and Lay the Right Foundations for AI-Ready Financial Operations

What if the key to making financial operations more strategic isn’t only investing in smart technology, it’s laying the right data foundations to make the technology work as it should?

Modern finance and accounting (F&A) teams are under immense pressure to deliver sharper insights, drive cost-efficiency, and respond to a rapidly evolving technological landscape, all at once.

Artificial intelligence (AI) is no longer a buzzword at the edge of the boardroom; it’s a core topic of conversation. However, many F&A teams risk skipping a crucial step in the race to modernise: laying the groundwork for achievable digital transformation.

BlackLine’s Principal Value Architect in Asia Pacific, Mike Goldsworthy, recently delivered a presentation on this very subject at CFO Day in Sydney.

F&A teams that fail to use clean, standardised, and accurate data risk leveraging flawed insights to make strategic business decisions, leading to flawed outcomes.

Accurate and standardised data doesn’t just make transformation easier; it makes it possible. Using a foundation of trusted data lets you incorporate AI and automation to take you from doing to strategising.

If we get better data out more quickly, we’re going to improve profitability for the organisation. Even more so, MIT research reveals that companies operating in real time had 62% higher revenue growth and 97% higher profit margins than those that weren’t.

However, there’s another layer here: governance. High-quality data must also be traceable, secure, and auditable. This isn’t just about performance; it’s about accountability. Increasing regulatory scrutiny makes data integrity critical to compliance, and F&A leaders can’t afford to treat it as anything less than a top priority.

Automation unlocks efficiency and delivers real return on investment (ROI). Process inefficiencies, including manual work and data manipulation, drain productivity, slow decision-making, and increase the risk of error, making them as much of a financial issue as they are an operational one.

Automation that is layered in helps eliminate redundancies and rework. It builds structure, turning transformation into a scalable, repeatable process by streamlining workflows rather than masking inefficiencies and creating additional complexity.

It also reduces onboarding friction by empowering teams to get up to speed faster when automated systems clarify responsibilities, standardise actions, and limit exceptions. The result is increased internal confidence and greater consistency across customer-facing outcomes.

Goldsworthy said, “Some of the challenges I’ve seen with AI projects, and any automation project, are the rush to get the ship moving. It’s not efficient to throw automation at various parts of the process without really thinking through that data layer first and having to stop a project, unwind it, or rework it sometime in the future.

“Having a singular lens across all of your data lets you identify weak spots, the Achilles heel of process, which gives you an opportunity to direct your focus there for a quicker ROI and lower cost.”

These days, there’s a bit of apprehension about AI. Common questions include:

• How can we use AI?

• How are my peers using AI?

• Are we behind with AI?

• Where do we start with AI?

BlackLine has purpose-built AI embedded into our solutions to solve challenges for F&A professionals. Its configurable, opt-in capability means we will work with you to tailor the implementation to your business goals.

We use AI to solve real F&A problems, like high-volume transaction matching, anomaly detection, and predictive forecasting.

We don’t buy into the hype of AI for the sake of it. We’ve invested in purpose-built, functional AI tools that create space for strategy and are grounded in finance logic. We believe that trust in AI starts with control, and finance teams must stay in control.

The organisations succeeding with AI today are the ones who’ve treated it as a strategic partner, not a saviour. They’ve done the hard work of preparing their data and refining their processes.

Now, they’re reaping the benefits in the form of faster close cycles, greater agility, and deeper insight.