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Strategic AI integration, governance and risk in finance

Businesses are preparing to incorporate AI into the finance function and anticipating how to manage risks. 

In brief

  • Hundreds of AI use cases for the finance function are in progress, with potential to change operations and take financial planning and analysis next level.
  • To remain competitive, organizations need to balance AI concerns with opportunities.
  • As regulations evolve, transparency in AI use is key to effective AI governance.

As artificial intelligence (AI) and generative AI (GenAI) revolutionize business with advancing capabilities, excitement surrounding AI is undeniable. Market sources forecast AI investment to approach $200b globally by 2025.i

AI has the potential to impact finance functions by automating processes and enhancing decision-making. In conversations among Fortune 250 CFOs, EY teams found that while organizations are at different stages in their AI journey, all admitted to having done some experimentation, and about half had defined projects or other capabilities in use today.


However, widespread use of these tools raises serious concerns about data privacy, security and compliance. Businesses must focus on an accountable and ethical AI approach, but there is hesitation among business leaders. In the October 2023 EY CEO Pulse survey, 62% of respondents acknowledge the urgency of acting on GenAI to keep pace with their competitors, and 61% express reservations due to the uncertainties surrounding AI strategy. 


During a recent EY webcast, more than 2,800 CFOs, finance professionals and board members heard from EY leaders about AI capabilities and use cases within finance and audit, as well as the importance of risk management and governance.


An audience poll showed that 38% said the most promising finance industry use case for AI is financial planning and analysis. Organizations are also investigating AI use for the financial close process, demand planning, sales forecasting, operations planning and generating the management discussion and analysis (MD&A).


Where AI is deployed outside finance — such as product development, sales and marketing — finance will also play a critical part in strategy, resource allocation and managing the application of AI in areas with promising ROI.

1. Embrace AI, cautiously 

With the advent of accessible GenAI tools in the past few years, AI is almost deceptively easy to use, said Sam Peterson, EY Financial Accounting Advisory Services, Global Data and AI Leader. While AI is now highly capable across a wide range of tasks in the finance function, he issued a caution: taking advantage of these capabilities for business use requires highly specialized functional domain and data expertise.

Output depends on how users prompt, query and train the AI and what data the AI uses.

“The productivity gains, and even the quality gains from using AI, very much depend on how humans use the AI, what tasks they use it for and how skilled they are at using it,” Peterson said.

Action item: 

  • Engage your workforce. AI is creating excitement among employees, but also stress and anxiety because many job types and tasks will be impacted, Peterson said. Emphasize that AI’s strength is in how it integrates technology and how it enables professionals to do more meaningful, valuable work.


2. Prioritize data strategy 

Organizations that are positioning themselves to get ahead are investing in AI-ready data strategy and governance, advised Deirdre Ryan, EY Global Finance Transformation Leader. She cautions organizations to carefully deliberate how they use sensitive data, including personal data from employees or customers. “We want to ensure that data can be trusted and it’s secure.”

Now is also the time to make sure professionals understand the possibilities of this technology so organizations reimagine how work is done to optimize benefits. The good news, Ryan told those on the webcast, is that while many use cases and proof of concepts have been deployed, most organizations are at the beginning of their GenAI journey. “It’s unlikely that your competitors are that far ahead of you.” That being said, companies that evolve quickly will have a competitive advantage.

While effective use of AI involves prioritizing the capture and analysis of valuable data, the opposite is also true. “Generative AI puts data on steroids, so bad or dirty data makes situations worse when generative AI is paired up to it,” counselled Kris Pederson, EY Americas Center for Board Matters Leader.

Action items: 

  • Establish standard architecture. Focus on cleaning up the data structure first, so that tools work effectively to tap both structured and unstructured data and interrogate it.
  • Invest strategically. Prioritize data that provides a true competitive advantage. 


3. Identify known risks

Concerns about data confidentiality, security, privacy and cyber risks are not new. However, their severity has been amplified by the widespread use of AI. The amount of information exposed because of the use of AI increases the vulnerability to cyber threats and raises third-party risk, along with legal, compliance and brand and reputation risks, said Richard Jackson, EY Global Artificial Intelligence Assurance Leader. 

Organizations now have to think about managing these risks and regulating AI and technology-related activities. However, Jackson said, organizations also need to be aware of another risk — the risk of falling behind.

“It’s easy to talk ourselves into why we shouldn’t use this because of all these risks, but there is a fundamental market competitiveness that all organizations face,” he said. “There is also the risk of missing out on the revenue growth opportunities by not using this technology to its capability.”

Action item:

  • Take inventory. Understand the use of AI, its scope and impact of how it is being used across your organization. Understand where and how your third parties are using AI and Gen AI in theirs.
It’s easy to talk ourselves into why we shouldn’t use this because of all these risks … There is also the risk of missing out on the revenue growth opportunities.

4. Adjust to the regulatory landscape

As AI use proliferates, the need for clear regulation and transparent reporting is evolving. President Biden’s 2023 executive order established a voluntary set of programs and expectations. In Europe, a proposed regulatory approach emphasizes obligations backed by law and penalties. Both highlight an expectation that organizations will identify their use of AI in their systems, along with assessing the risks within those processes and how it impacts the users.

In an audience poll about their organization’s maturity in assessing the implications of announced public policy guidance, 20% of attendees were aware of the various requirements but have not yet started their regulatory assessment. More than twice that number, 42% of our audience, were not at all aware of the regulations.

Begin by enhancing existing systems, Jackson said. Leverage your existing governance and compliance structures and build them out at scale, across functions and organizations.

Action item: 

  • Think globally. Regulations will have an impact across jurisdictions.


5. The board plays a strategic role

AI governance has become a prominent topic in boardrooms and EY Center for Board Matters discussions. Boards are engaging with AI leaders, chief information officers and chief information security officers regularly, Pederson said.

They are looking at how organizations are using AI to drive revenue and identify opportunities, as well as labor ramifications and workforce training, but she emphasized risk management as one of the board’s key duties. Boards are responsible to guide an organization’s AI strategy and oversee its responsible use, she said. They are instrumental in instilling trust, accuracy and privacy, and ensuring robust AI governance.

Action items: 

  • Get hands-on. Become comfortable talking about AI and GenAI to help the company embrace innovation. Boards should be knowledgeable about AI technologies, including its biases, and lead with curiosity to stay informed — balanced with risk management.
  • Communicate with the board. The board is a strategic resource in guiding the company’s AI strategy in a responsible and transformative manner. Keep the board informed about evolving regulations related to AI, machine learning, data privacy and emerging technologies in relevant jurisdictions and how company compliance is monitored.


While AI and GenAI adoption has the potential to transform business and finance operations and enhance decision making, it also brings additional challenges with data privacy and regulatory compliance. Strategic AI integration, effective risk management and a proactive approach, combined with board guidance, are necessary for organizations that want to stay cautious while gaining a competitive edge.

To listen to the entire webcast, click here.

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