Generative AI’s Potential to Revolutionize Finance

by Dipti Gulati

Generative AI has the potential to generate tremendous value for the finance function and broader enterprise.


Generative AI’s potential to revolutionize finance

The scope and scale of the issues within a financial executive’s purview today can be staggering. Compounding the complexity is having to operate against a backdrop of an uncertain economy.

Finding ways to harness disruption, the latest being the potential of Generative AI, to anticipate and act on the evolving expectations of the finance function amidst complexity can serve as a differentiator to long-term value.

Generative AI’s significance is in its ability to leverage large language models (LLMs), generate multiple forms of media including image and audio, among other breakthroughs. It’s creating the tools that can help professionals boost productivity, extract insights, and generate opportunities for efficiency and revenue growth.

This AI boon comes at a pivotal time when financial executives are increasingly expected to serve four diverse and challenging roles - steward, operator, strategist, catalyst. Here’s how the transformative power of Generative AI can be applied to complement human skills across four key responsibilities of your role as a financial executive, as well as additional considerations as you explore:  

  • Steward – With a foundational responsibility to meet compliance mandates and financial reporting regulations, Generative AI can be applied to improve efficiency and adaptability. For example, Chief Accounting Officers may leverage Generative AI on top of existing documentation to support accounting research by responding to questions, summarize guidance, and determine compliance with regulations and policies.
  • Operator – Financial planning and analysis is one of the highest use cases of Generative AI today according to a recent Deloitte survey of CFOs. One interesting application growing in interest from CFOs is leveraging Generative AI to prepare for quarterly earnings calls. The technology can be applied to analyze previous call transcripts to identify key themes, plan for various scenarios, and anticipate and prepare for questions from the investor community.  
  • Strategist – Preparing to present to the board or other internal stakeholders related to long-term investments, or M&A activity, can be augmented by understanding how Generative AI can be applied to these types of decision-making. The technology can help predict and pre-empt strategic macroeconomic developments and provide quick answers to evolving questions.
  • Catalyst – Agents of change accountable for results want the execution on agreed upon strategic initiatives to be successful. Generative AI can aid in the monitoring and assessment of those initiatives as well as help in determining optimal strategies from assessing corporate development deals, and running due diligence, to identifying opportunities for capital optimization.

Key considerations to keep central to your planning when it comes to exploring Generative AI include:

  • Talent – Talent availability and retention is a critical issue many organizations face—finance organizations are no exception. Add the need to have tech savvy members of your finance team, and it can be a daunting challenge. 60% of surveyed CFOs said bringing in talent with Generative AI skills over the next two years is either extremely important or very important. As leaders, fostering a culture of continuous learning sets an expectation that your teams need to understand the dynamic forces impacting change and growth. It can help your teams develop and hone the skills today that are needed for tomorrow, so identify and encourage external training programs, and hands-on learning.
  • Cybersecurity – According to the Deloitte and Center for Audit Quality (CAQ) Audit Committee Practices Report, cybersecurity is the No. 1 priority of surveyed audit committees over the next twelve months. With the promise of Generative AI to improve processes, it can also pose cyber risks if proper guardrails are not in place. For example, deepfakes, created using Generative AI, can be used to get around voice and facial recognition access controls and the targeting of the financial sector is on the rise. According to a Wall Street Journal report, deepfake incidents in the fintech sector increased 700% in 2023 from the previous year. However, Generative AI tools can also be used to identify and predict such attacks, allowing enterprises to get ahead of them.
  • Trust – Foundational to all Generative AI efforts is a responsibility to keep trust at the center for all stakeholders. When engaging with audit committees for example,  they will likely want to understand Generative AI impacts on the finance function and risk mitigation strategies. Organizations will have to create transparent, and proper usage and governance models that address the entire Generative AI lifecycle from ideation to design, development, and deployment. Having a Trustworthy AI framework can help develop ethical safeguards to manage risks, improve user confidence and trust, and capitalize on the returns related to the use of Generative AI.

While the benefits of Generative AI today is very much still at the process level to improve efficiencies and productivity, over time, it has the potential to generate tremendous value for the finance function and broader enterprise. The promise of the technology represents a new way of making decisions, therefore it is imperative for the finance function to participate in shaping the strategy and execution. The time is now to design your Generative AI strategies for a transformative future.

Dipti Gulati is CEO, Audit & Assurance at Deloitte & Touche LLP.


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