Redefining AI Leadership in the C-Suite

Who makes decisions within organizations about investments in artificial intelligence tools? Who should? The company CEO and CIO (or other senior technology leaders), of course, but who else?

We contend that while CFOs may not think of themselves as leaders of artificial intelligence for their companies, they can make a bigger leadership impact when it comes to AI strategy and adoption.

There are two key reasons. The first is that CFOs are heads of the finance function, and many finance processes and tasks can be performed by AI. One survey of U.S. organizations found that 24% of finance managers are currently using AI, and another 50% expect to use it within three to five years.

The second reason is that CFOs are usually the primary custodians of “value for money” appraisals and as such should provide oversight on AI investments. A 2018 Deloitte survey on trends in CIO reporting relationships found that 28% of CIOs report to the CFO. This is significant in terms of AI because a 2020 survey of global AI adopters from Deloitte found that IT is the single most likely area (with 47% listing it as a “top two” application domain, and cybersecurity in second place, with 22%) where companies will apply AI and automation to tasks and processes frequently repeated activities. These include rebooting servers, monitoring networks, supplying user passwords, and capturing and monitoring trouble tickets, or initiatives like helping to validate and prioritize cybersecurity threats. When CIOs make the case for AI investments, CFOs should be alongside the effort, integrating financial evaluations with technology strategy.

While AI is likely to dramatically affect business practices in the future across the C-suite, it’s already having an impact today. In other words, the time for CFOs to step up to AI leadership is now.

If an organization is to transform its finance function with AI capabilities, or to employ a wise investing approach to AI in general, leadership from the CFO is essential.

Opportunities for AI Within Finance Functions

The finance function offers many areas for using AI, and it’s worth ticking through some of them. One of the primary areas to deploy robotic process automation (RPA) is the financial period close, where reporting typically involves the extraction of data from multiple systems, consolidation and reconciliation of journals across the organization, and data transfers from internal groups and to regulators. Invoicing, too, involves structured, repeatable activities and information access. RPA is perfectly suited for these types of work — it can reduce the burden on human workers, improve cycle times, and reduce mistakes.

Tax, audit, and compliance functions are also well suited for AI. AI can extract supplier contract terms and match them to goods and services delivered. Employee expense report information can be checked against corporate policies. The speed and constant work of AI systems typically means that 100% of transactions can be audited rather than just a sample. Other forms of AI can be used for forecasting, estimating demand (typically using external data), and assessing risks, including conducting appraisals of brand damage from problems such as security breaches.

The use of AI for finance functions is taking root. In the 2020 global AI adopter survey, 8% of respondents put finance in the top two application domains. But in a 2018 Deloitte survey of enterprise AI, 37% of large U.S. organizations were pursuing use cases with AI involving risk management, 29% on cases involving forecasting applications, and 23% on cases addressing tax, audit, and compliance issues — all of which touch on finance.

Admittedly, AI applications in finance thus far have been relatively pedestrian. However, the future of intelligent financial applications is likely to be much more dramatic. Most transactions will be automated, replacing outsourcing as a way to achieve productivity. Finance functions will likely be staffed by substantially fewer people, all of whom understand AI and how to add value to it. Budgets, forecasts, financial analysis, and approaches to improving financial performance will likely be based on machine learning models trained by internal and external data.

These developments will be particularly important in the COVID-19 economy; some AI companies, for example, have already developed approaches to using AI to minimize accounts payable cash outflows. Some companies are basing rapidly changing demand predictions on external data such as surveys, mobile phone data on consumer movement away from home, and even sensor data from consumer thermometers.

Many of the external services offered to finance functions — auditing, consulting, and tax advice — will also be automated and substantially more intelligent; Deloitte, for example, is rolling out AI-supported audits now. In 10 to 20 years, we expect that CFOs will oversee a stable of algorithms and AI applications that will make their function more successful and efficient than it has ever been.

Opportunities for AI Within Finance-Related Functions

CFOs who lead business functions such as IT and procurement may be responsible for sponsoring and overseeing AI applications in these areas. AI, of course, can ultimately can lead to substantially greater productivity in IT functions, especially in industries where IT is becoming the “factory” for financial services and e-commerce businesses and others. However, Deloitte’s 2020 enterprise AI survey found that 62% of executives view cybersecurity as one of their top three concerns about AI, so CFOs may want to play a leadership role there.

A variety of AI applications can be employed in the procurement domain, including spend classifications, supplier risk assessments, automated contract reviews, and chatbots for routine supply ordering. Even when procurement does not report to the CFO, it may be wise for finance chiefs to pay attention to this area and insist on some of these capabilities because of the implications they could have on the financial health of the business.

Oversight of AI Investments

CFOs usually have the oversight role for their companies’ spending and investing activities. Many businesses are spending significant amounts on AI — 53% of respondents to the Deloitte 2020 survey said their companies had spent more than $20 million annually on AI technology and talent, and 71% report that they will spend more on AI in the coming year.

The Deloitte survey data also suggests a large majority — 81% — of the longer-term users of AI have seen returns on their AI investments, with a payback period of less than two years. CFOs can help ensure that high levels of value from AI continue to be achieved by creating systems and processes for reviewing investment proposals, moving AI systems toward production deployment, and assessing the value of systems post-implementation. These moves are particularly important in the difficult economic climate we are likely entering.

Despite the fact that AI is a relatively new technology, each investment should be intended to deliver financial value to the organization — even though not all of them will pay off. CFOs can play a role similar to that of a venture capital partner, doing whatever is necessary to clear the way for AI initiatives to succeed and creating a higher likelihood that they will provide a high return on investment.

The AI-Oriented C-Suite Exec: Key Tactics

CFOs and other C-suite executives who focus on AI technology today will begin to reshape the divisions they lead. There are five specific tactics to move toward this goal:

• Set personal examples for other senior executives. CFOs can explore the different types of AI technologies and learn which ones are most relevant to specific use cases. In team meetings of the finance function, CFOs might use their AI knowledge to suggest particular projects and technologies. In gatherings of senior management teams, CFOs can motivate other leaders to adopt AI within their own business functions and units.
• Meet with AI companies. Taking meetings, especially with companies of finance-oriented AI applications, will help CFOs learn what’s possible. It will also help prioritize which companies to work with.
• Select AI projects to advocate for as executive sponsor. For a CFO, the executive sponsor role might mean overseeing projects that are particularly relevant to the finance function, or those that need more focus on achieving returns on investment.
• Create specific roles to advance AI in the function — and even consider adding a small center of excellence. At least some practitioners with deep understanding of both AI and finance would be needed to staff these positions. Such roles could also be part of a centralized center of excellence on AI if the company has created one.
• Establish an educational initiative for team members to learn more about AI. The goal here would be to help all finance employees understand how to add value to AI in finance, accounting, and other specialized topics.

Together, these activities can make the CFO one of the most important executives in a company’s journey to effective use of AI. If an organization is to transform its finance function with AI capabilities, or to employ a wise investing approach to AI in general, leadership from the CFO is essential.