Can a Finance Organization Become Truly Autonomous?

This article was originally posted on Forbes.com, Jul 10, 2023.

With the recent advancements in large language models—the artificial intelligence (AI) models behind ChatGPT—it's become clear that the future of business is intertwined with AI-powered tools. From communications to logistics and everything in between, AI has the potential to not only streamline and optimize the way we work but also influence future decisions.

In accounting, AI is poised to transform organizations through real-time financial analysis, predictive analytics, risk management and more. The result is expected to be a more efficient, data-driven finance operation than could previously be achieved.

We're driving steadily toward this autonomous finance organization. But what will that organization look like, and how soon will we get there?

What does an autonomous finance organization look like?

Finance organizations have been automating their processes for years using rules-based tools like RPA. However, the bar isn’t “automation” anymore; it’s “autonomy.” Template-driven tools can be rigid, cumbersome and expensive to implement and maintain. They also often require a considerable amount of manual labor. This is unsustainable for large organizations that process tens of thousands of accounting transactions a month. The agility and resiliency that finance organizations need to navigate economic uncertainties require much more.

AI, in contrast, can go beyond automation to achieve efficiency, accuracy and autonomy. When applied to finance and accounting functions, AI can offer significant advantages. Because AI adapts and applies logic, it helps organizations classify invoices, manage approvals and match purchase orders autonomously with greater accuracy and speed than humans. Rich data feeds into dashboards and financial reports, helping finance leaders derive valuable information from transactions in real time and make better decisions faster.

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In the near future, I believe that AI will similarly master real-time financial analysis, predictive analytics and sophisticated risk management using advanced levels of intelligence.

Real-time financial analysis is the continuous monitoring, processing and analyzing of financial data as transactions and other events occur, providing finance professionals with immediate insights into financial health and performance. Real-time financial analysis requires a few key components. First, the accounting and financial systems must be seamlessly integrated, allowing data to flow and synchronize across various platforms in real time. Second, AI-powered tools capable of rapidly processing and analyzing large volumes of data are required to make sense of the constant influx of financial information. Third, a robust and secure IT infrastructure is necessary to support the high-speed processing and storage of data, as well as protect sensitive financial information.

Predictive analytics is another significant development for finance departments, enabling finance teams to forecast trends and identify potential opportunities or challenges before they materialize. Using AI-driven predictive models, businesses can make data-driven decisions and effectively plan for the future, mitigating risks and capitalizing on new opportunities.

Risk management practices can also benefit from these advancements in real-time financial analysis and predictive analytics. By continuously monitoring and processing financial data, AI-powered tools can help provide finance professionals with immediate insights into potential risks such as liquidity issues, credit risks or market fluctuations and help them respond more quickly and effectively to mitigate their impact. By leveraging these predictive insights, businesses can make data-driven decisions to address potential risks proactively, helping them minimize losses and capitalize on opportunities.

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When will we get there?

Like many forms of technology before it, AI technology has advanced exponentially in recent years. However, with the advent of large language models, that growth curve has skyrocketed. At this time last year, the autonomous finance organization might have looked a decade off or more, but today’s technology may bring it about in two or three years—or even sooner.

But, also like other disruptive technologies, the adoption of these advanced AI technologies in finance departments may lag behind their availability. After all, if we woke up tomorrow and all cars were self-driving, many commuters would opt for a bike or a train until they saw for themselves that the roads were safe. Implementation will inevitably be the rate-limiting factor on this road to a fully autonomous finance organization.

How do we drive finance into the future?

Added together, these technologies could transform the finance profession and empower accountants to drive strategic decision-making in their businesses. AI-powered tools can free up accountants to focus on strategic planning, financial advising and other higher-value activities that require their expertise by placing existing transaction and analytics work on autopilot. This shift has the potential to improve the efficiency of accounting processes and enhance the value accountants bring to their businesses and their clients.

Most importantly, despite doom-and-gloom forecasts that predict the demise of our profession at the hands of AI, I believe the future of accounting is exciting. AI can create opportunities for enhanced, agile decision making in finance organizations. I feel that it’s time for finance organizations to embrace these advancements and drive their organizations toward a more efficient, sophisticated, data-driven future.

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