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At a glance
By Adam Turner
Moving beyond producing monthly reports and toward continuously monitoring business performance, the future finance and accounting professional is more of a strategic adviser than a number-cruncher.
While Microsoft Excel offers a formidable array of data analysis and visualization features, it is not always the best tool for the job. While capable of working with vast amounts of data, there still comes a point where Excel starts to groan under the load — especially when merging data sets.
Real-time data
A new generation of tools such as Tableau and Power BI specifically focus on business intelligence and advanced data visualisation, which assists finance professionals to interpret data and convey those insights to stakeholders.
Now, the rise of artificial intelligence (AI) has spawned planning and forecasting tools like Anaplan and OneStream, allowing professionals to more easily explore complex “what-if” scenarios.
Meanwhile, AI assistants like Microsoft’s Copilot, OpenAI’s ChatGPT and Anthropic’s Claude can integrate with a wide range of finance tools to help uncover actionable insights.
Automatically drawing on real-time data from across an organisation, this new generation of AI-powered analysis allows finance teams to quickly identify risks and opportunities as they emerge, and improve forecasting to support more proactive decision-making, says associate professor Andrew B. Jackson from the School of Accounting, Auditing and Taxation at UNSW Business School.
Insights into action
The goal is not to replace Excel, Jackson says, but rather to complement it with tools that allow finance teams to focus more on interpretation and decision support.
“The biggest shift in finance is that technology is increasingly handling the number-crunching, while humans are being asked to provide the judgement,” he says.
“The finance professionals who thrive in this new world will be those who can turn data into decisions and insights into action.”
While AI-powered tools might speed up processes, finance professionals now require the skills to craft insightful queries and prompts, as well as the critical thinking to not take AI at face value and instead delve deeper to interpret outputs.
“More dashboards do not automatically lead to better outcomes. The downside of these tools is that real-time data can create information overload if organisations do not focus on the metrics that matter,” Jackson says.
“Increased use of AI also creates a greater reliance on data quality, because poor data can lead to poor decisions.”
Focus on higher value
Along with helping finance teams extract business insights from vast swathes of data, new technology is also reducing the need to shuffle paperwork. This frees professionals up to focus on higher-value tasks that still require the human touch.
When it comes to managing finance workflows, Robotic Process Automation (RPA) bots follow preset rules to quickly accomplish repetitive tasks. More advanced AI agents are goal-oriented, with the ability to learn and adapt with minimal human intervention.
The two can work together, with AI agents managing a team of specialist RPA bots to handle complex cross-platform workflows with improved exception handling.
Jackson believes accounting and finance professionals’ ability to communicate insights and influence decisions will be a key differentiator in this future work landscape.
“Technical accounting knowledge remains important, but analytical thinking and business understanding are becoming even more valuable,” he says. “In many ways, the future finance professional looks more like a strategic adviser than a spreadsheet expert.”
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