AI for the CFO: Empowering your organization with AI finance strategies

In today’s middle market business landscape, the capabilities of artificial intelligence and the utilization of AI technologies are rapidly evolving, making AI an indispensable tool for finance and accounting leaders. As these advancements continue to evolve, chief financial officers must adapt, fully leveraging AI tools and technologies to optimize their operations for better efficiency and shape the strategic vision of their organizations.

Demonstrating how quickly AI has advanced in the middle market, the recent RSM Middle Market AI Survey: U.S. and Canada found that 78% of middle market executives are either formally or informally using AI. But only 20% of organizations feel they have integrated AI meaningfully, and 67% using generative AI report they need outside help to get the most out of that tool. With the growth and potential of AI solutions, CFOs have a significant opportunity to transform key processes and shape the strategic direction of the business.

RSM US LLP Principals Jonas Melton and Brad Collins, along with RSM Canada Director Praveen CP, explored the current state of AI and its application and potential to strengthen the finance function during RSM’s recent webcast A practical approach to artificial intelligence for the CFO.

Below, we take a look at some critical details for CFOs to consider when developing an AI strategy, as well as issues, opportunities and potential use cases for many AI tools and applications.

The CFO’s role in AI adoption

With AI reshaping the financial landscape, CFOs are becoming more strategic leaders within the organization, guiding AI teams through AI adoption to navigate complexities, optimize performance and drive future growth. Finance leaders are the champions of this critical transformation, inspiring responsible AI use while fostering a data-driven culture within the organization.

CFOs have four key areas of responsibility that guide comprehensive and successful AI adoption and integration:

• Vision and strategy: Establish a clear vision for AI integration within finance teams, outlining the strategic purpose and potential to drive efficiency, innovation and growth.
• Leading by example: Actively use AI tools within key processes and decision making, while continuously learning about new advancements to champion their integration within the finance team.
• Ethical considerations and governance: Prioritize responsible AI use by establishing ethical guidelines, ensuring data integrity for reliable results and continuously monitoring AI systems to optimize performance and mitigate risks.
• Implementation and change management: Initiate AI adoption with targeted pilot projects to showcase its value, carefully select appropriate AI solutions for finance team needs, and proactively manage change through clear communication and celebrating successes.

“CFOs and senior finance executives can no longer afford to be passive observers in this revolution,” said CP. “In order to thrive in this new era, finance leaders must actively embrace artificial intelligence and take on a more crucial leadership role to ensure successful adoption of AI within their organization. This means going beyond simply just understanding the technology. It requires an intentional mindset and a commitment to ethical implementation, as well as a proactive approach to change management.”

CFOs and senior finance executives can no longer afford to be passive observers in this revolution. In order to thrive in this new era, finance leaders must actively embrace artificial intelligence and take on a more crucial leadership role to ensure successful adoption of AI.

Praveen CP, Director, RSM Canada

Key issues

Given AI’s vast potential, companies can leverage the technology in many ways to drive increased revenue, margin and earnings. In the 2024 Gartner CEO and Senior Business Executive Survey, three of the top four areas in which respondents said they intended to use AI to help maintain or grow net income were as follows:

• Redirection of capital through the targeted and deliberate deployment of automation to handle lower-value activities and tasks
• Increased business intelligence, analysis and predictability across larger data sets and data volumes
• Upskilling of existing talent across finance and accounting to enable the leveraging of machine learning, generative AI and other automation tools to increase organizational efficiency and optimize performance

By effectively leveraging all forms of automation, including AI, accounting and finance teams can drive efficiency and directly support overall business growth. Opportunities include:

Analyzing: By implementing tools that review documents and detect improper integration, companies can find errors and anomalies in data sets to create more reliable data—supporting the overall completeness and accuracy of organizational financial information. Analysis through automation also directly supports key growth activities, including volumetric and financial-driven analysis of revenue-generating streams, channels and products/services being sold.

Predicting: Using historical data, companies can identify unusual patterns to prevent fraudulent activities and project collections risk based on customer patterns.

Generating: Teams can leverage AI to summarize emails and documents, gather information and answer questions, and generate draft accounting policies.

However, when integrating innovation to strengthen key financial processes, companies may find it difficult to determine the best strategy. While AI has become a popular solution, it might not always be the right fit for some organizations. In some cases, a challenge can be resolved more effectively using another type of advanced technology, such as robotic process automation (RPA).

“When it comes to solution planning, always ask, do you truly need to deploy another AI model, or can RPA suffice?” said Melton. “RPA is simply more logic-driven automation.”

In addition, if AI is the answer, CFOs need to determine whether to buy or to build—that is, embed AI in the existing technology stack or develop a more customized AI solution.

“Always weigh the benefits of leveraging AI built-in existing technologies versus building custom models, factoring in cost, security and data quality,” Melton added.

Always weigh the benefits of leveraging AI built-in existing technologies versus building custom models, factoring in cost, security and data quality.

Jonas Melton, Principal, RSM US LLP

AI use cases for finance and accounting

When identifying potential use cases, companies should consider several tools and solutions that can increase efficiency, boost productivity and strengthen business insight. Some business needs will require support from a single application, but multiple AI tools can also come together to address more complex challenges. The depth of the solution depends on the specific requirements.

“Developing a strong AI use case requires a strategic approach,” said CP. “It starts with identifying key areas and establishing a framework. Monitor industry trends and analyze data to uncover opportunities where AI can improve efficiencies. Brainstorm with your team and take a collaborative approach with a strategic focus on outcomes. Clearly defined business goals and aligned AI are the key to outperforming the desired goals.” Praveen CP

CFOs can accomplish several key objectives by leveraging AI functionality built into the following Microsoft applications that already exist within many organizations:

• Copilot Studio: Creates and deploys chatbots
• Power Automate: Utilizes RPA to facilitate workflows across applications and services
• Azure OpenAI Service: Delivers advanced AI large language models for integration with applications
• Azure Storage: Provides scalable and secure cloud storage
• Azure Functions: Allows developers to deploy event-driven functions
• Azure AI Search: Enables advanced query and data retrieval using AI

CFOs can also take advantage of advanced AI features and functionality within digital tools and applications such as the following:

• Basware: Converts machine-readable PDFs to e-invoices with 97% accuracy
• BlackLine: Summarizes documents and financial statements with accounts receivable payment forecasting and intercompany transactional data review
• HighRadius: Predicts customer payment and deduction validity with remittance management and financial data insights
• Workiva: Provides financial reporting as well as insight into sustainability, audit and risk
• Coupa: Detects fraudulent spending and provides workflow guidance and contract intelligence
• Workday Adaptive Planning: Identifies anomalies and enables predictive financial forecasting

In addition, AI plays a significant role within the tax ecosystem for data extraction, document and footnote drafting, rule application, and decision-making support. Further, when raw data from enterprise resource planning systems is mapped and consolidated to assess taxability, AI can generate robust interactive and predictive insights. These insights optimize scenario planning, uncover savings opportunities and enhance strategic outcomes with greater accuracy and efficiency.

Potential AI use cases for tax include:

• Transfer pricing documentation
• Pillar Two disclosures
• Merger and acquisition analysis, due diligence and scenario planning
• Tax dispute preparation
• High-data-volume compliance tasks, such as uniform capitalization and depreciation
• Adaptation of new business scenarios to existing processes
• Identification of connections between jurisdictional and specialty gaps
• Tailored communications

“Looking at family-owned middle market businesses, the greatest transference of wealth in history will occur over the next decade-plus.” said Collins. “We are focused on creating applications in our tax ecosystem, like CorporateSight^®, FamilySight^®, PartnerSight^® and PartnerSight Private Wealth, to leverage data effectively. By doing so, CFOs can analyze and anticipate the tax implications of various financial decisions in real time and plan for the future.”

We are focused on creating applications in our tax ecosystem to leverage data effectively. By doing so, CFOs can analyze and anticipate the tax implications of various financial decisions in real time and plan for the future.

Brad Collins, Principal, RSM US LLP

Frequently asked questions

The takeaway

Like many other key business functions, AI has the potential to revolutionize the finance function and further establish the CFO as a strategic leader within the organization. However, while finance leaders may know where they need to focus their energy, they may need additional support to determine what tools to leverage or whether AI is the optimal solution compared to other strategies such as RPA.

Ready to get started? RSM’s experienced AI advisory team understands the enterprise AI journey and the foundational elements necessary to generate increased value and reduce risk. Contact our team to learn more about how AI can transform your key business operations.