2024 Industry Outlook: What matters most to CEOs and CFOs

High interest rates eating into profits have been a rising concern for businesses over the last few months. While interest rates can influence the cost of capital and impact financial decision-making, profitability remains a core driver of financial strategy in the long term. Financial leaders are making changes in their operating methods as part of a broader effort to increase profitability despite existing issues, according to new research by Grant Thornton.

But all is not so rosy. Despite increased profitability high up on their agendas for 2024, 28% of Chief Financial Officers are hardly optimistic about the economy changing for the better and expect economic conditions to remain flat in the coming year. While uncertain interest rates are the leading concern this year and next, numerous other challenges continue to persist, including supply chain issues that remain a top concern for many (55%).

To tackle these challenges, financial leaders are increasingly turning to advanced technological solutions to make data-driven decisions for improved efficiency and cost-effectiveness. Recent advances in AI are gradually becoming the popular choice and go-to solution for executives looking to solve a variety of legacy problems. Almost one-third (30%) of financial leaders are already using advanced AI functions in their finance processes, and an additional 40% plan to implement AI in this area in the next year.

“They [CFOs] are looking at how they can drive the business. And they’re focusing on technology upgrades to deliver that ROI,” said Paul Melville, national managing principal of CFO Advisory at Grant Thornton.

Generative AI (Gen AI) is making inroads in banking, finance, and other sectors. To stay ahead of the curve, 43% of organizations are using recent Gen AI applications, up from 30% the previous quarter, while others (45%) are still exploring its potential use cases. In terms of the supply chain, Gen AI trains on the reorganization and classification of heaps of data, such as logistics information, sales history, inventory records, and supply and demand scenarios to streamline processes and operations by making better recommendations.

Although banks and financial institutions have been deploying artificial intelligence (AI) applications across a variety of use cases for years, including lending and managing credit risk and fraud, Gen AI in financial services is still in its infancy. Regulatory bodies are being nudged to set the right rules and guardrails covering AI given its growing popularity, emerging use cases, and associated risks revolving around ethics, privacy, and security violations. There is also a heightened sense of concern among experts to prevent a recurrence of a situation similar to the BNPL industry that has expanded quickly to the extent that the speed of this growth has likely outpaced efforts to create consistent and transparent industry standards to some degree. 

Despite these concerns, a majority of CEOs and CFOs align on the idea of investing in AI and its functionalities to remain competitive even if it means moving into totally uncharted waters. On the other hand, some employees maintain the stance that much more remains to be done around educating the enterprise on the nascent technology, skill sets, and infrastructure to implement it effectively and limit risk. 

Implementing AI requires a substantial initial financial investment varying according to the models businesses might want to adopt – and whether they decide to build, partner, or buy the software. Costs may include new or upgraded infrastructure, hiring or training the existing workforce, and compliance and regulatory requirements.

37% of CEOs plan to reapportion capital from other investment budgets, 34% will raise new capital from scratch, and 26% indicate allocating capital especially assigned for technology budgets, according to a new survey by EY.

Financial leaders who haven’t jumped on the bandwagon yet but eventually plan to have already introduced formal training in their organizations on the use and possible applications of Gen AI, according to research by Grant Thornton. Successful implementation and enterprise-wide adoption, however, will likely depend on a comprehensive understanding of the benefits and drawbacks of the technology, and identifying and prioritizing the right use cases among other key considerations.

Besides AI, distributed ledger technology and machine learning are some of the evolving technological trends financial leaders (70%) say they are keen to explore moving ahead. 

All this evidence indicates that investing in technology remains a critical goal for leaders even in the face of economic and geopolitical instability, as a way to offset increases in operational costs and improve profit margins going into 2024.