“If it ain’t broke, don’t fix it.” This famous defense of the status quo was popularized in 1977 by Bert Lance, a Georgia banker and Director of the U.S. Office of Management and Budget under President Jimmy Carter.
It is apt that such wisdom would come from a banker, especially one who served, albeit briefly, as America’s chief financial officer (CFO). Anyone who has ever wrestled with trying to derive insights from disparate accounting and production systems through the collection, reconciliation and compilation of data on any significant scale can attest to the disruption involved when trying to change things. Change is a costly and time-consuming endeavor, involving significant change management, tons of data validation and verification – to name a few challenges – that would render any rational person reluctant to venture down that road. All of which may explain why CFOs rank among most reluctant – and least knowledgeable – company executives when it comes to adopting and seeing the value of artificial intelligence (AI), according to a recent global survey by Protiviti and ESI ThoughtLab.
To date, such reticence to consider the opportunities offered by AI has not posed much of a threat, as only a small minority of companies (16 percent) reported they are gaining significant value from AI. However, that number is expected to increase more than three-fold over the next two years as the world leaps into the so-called “cognitive age.” In the last fiscal year, businesses spent an average of $36 million on AI; that investment will increase by nearly 10 percent over the next two years. Reluctant CFOs would be well advised to consider how they would keep up – or take the lead on – these initiatives as their companies take the leap. A learning curve for those executives is expected – for example, in understanding the difference between data improvement and governance and the key value-driving applications of machine learning (ML) and AI.
To successfully manage a leap into the cognitive age, organizations will need to address a wide range of challenges, from uncertain ROI and limited AI talent, to concerns about cybersecurity and regulatory compliance. And it is important to remember that AI often creates fear among rank-and-file staff that the technology will eliminate jobs.
CFOs should not be watching from the sidelines as change takes place. They can play an important role in this transformation by helping to identify specific areas where AI and ML can provide better insights to the organization and championing pilots to provide practical proof of ROI.
Insights From the Survey
Advanced AI is already creating measurable value in essential areas of business, including improved planning and decision-making, enhanced customer experience, better risk management, reduced costs, increased customer retention and improved employee engagement. In cybersecurity, the ability of AI to spot trends and outliers within massive amounts of data is proving extremely beneficial. In finance, a similar capability could be deployed to detect fraud. The larger the company, the greater the expected gains regardless of application.
Over the next two years, most businesses will be applying AI to practically every function, including a more effective management of the workforce, labor productivity, customer and vendor behaviors, product development and risk management. AI applications in finance specifically are expected to double in two years – while 28% of companies today report a positive impact of AI on finance, 57% are expected to do so in just two years. The benefits of AI are more clearly perceived by companies that are leaders in the space (43%) versus those who are less experienced (28%).
Practical Proof
As is often the case with new technologies, people often get blinded by the gadget, and lose focus on the desired outcomes. CFOs, by virtue of their outcome-focused mindset, can add significant value in an AI initiative, by helping to identify small pilot projects and documenting the ROI.
One place to start might be the implementation of the new rules on lease accounting, which can be extremely complex depending on the company but which nevertheless contain many standard parts. Some companies have managed to reduce the time to review a single lease from six hours to a couple of minutes. Advanced AI has been used to accelerate loan processing and other data-heavy activities. The efficiency gains and added value in terms of improving process effectiveness cannot be ignored.
Using AI to develop risk models combines the power of more effective risk management and cost reduction. What previously might have required 6,000 man-hours and a team of data scientists can be accomplished by AI much faster and at a dramatically lower cost.
AI and ML present a great opportunity for finance to use advanced analytical techniques to provide more forward-looking, insightful information for forecasting and decision making. By providing insight and support for business cases and helping to drive ROI decisions, CFOs can bring their financial acumen and challenge to business cases to help the organization focus on the most promising opportunities for utilizing AI/ML. Moreover, they can play a key role in helping the organization understand if the ROI is being achieved post implementation.
Call to Action
We encourage CFOs to take a look at the survey results – with many companies having accomplished major data initiatives milestones, including in finance data, AI/ML is ripe for utilization. Finance leaders must look beyond finance and data reporting to AI-driven customer and competitive data initiatives, as some of that data is found in traditional finance processes like accounts payable to accounts receivable. Things may not be broke just yet, but they certainly could be more efficient, generate more value and help push the organization to the leader line.
Read additional posts on The Protiviti View related to AI.
