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Home Technology

Three distinct generative AI conversations CFOs must conduct

FutureCFO Editors by FutureCFO Editors
October 2, 2023
AI

Image by Geralt on Pixabay

There are three distinct generative AI conversations that CFOs, especially those from large enterprises, must conduct, said Gartner recently.

According to the advisory firm,  80% of finance functions of large enterprises will use internal AI platform by 2026, as leadership teams do not want to fall behind peers.

However, as the chief steward for an organisation’s financial health, CFOs must balance the risks and rewards of tools like generative AI, said Mark D. McDonald, senior director analyst in the Gartner Finance Practice.

“CFOs should have those three distinct generative AI conversations across leadership circles to ensure that reasonable expectations are established, and the use of generative AI creates value without introducing unacceptable risks,” he advised.

Those three distinct generative AI conversations are as follows, according to Gartner.

Debunk the hype to avoid inflated expectations
Generative AI presents the potential for businesses to comprehensively navigate their data’s growing complexity and volume with ease. 

However, the technology’s limitations introduce several real challenges to this objective, leading Gartner to consider it at a peak of inflated expectations. 

CFOs should partner with senior technology leadership (e.g., CIO, chief data officer, chief information security officer) to distinguish hype from reality and share results with other executive leadership team members.

Current generative AI solutions represent a collection of modern innovations, including deep learning, natural language processing, reinforcement learning and graph networks, all of which deliver remarkable outcomes. 

However, the extensive number of parameters and connections used to create these outputs prevent any transparent reconciliation of the algorithm’s response.

This observation includes an inability to determine if the algorithm has developed unstated objectives or if it is basing conclusions on inaccurate, irrelevant, unethical, or even illegal information. 

Such limitations form the backbone of conversations that CFOs must have with leadership circles when considering the use of generative AI.

Define generative AI use cases that are aligned, responsible, and actionable
With an understanding of generative AI’s limitations, CFOs can responsibly direct a conversation with management teams aimed at defining use cases. 

They must collaborate with operational management, executive leaders, and representatives from the user community to define actionable generative AI use cases that align with the organization’s overall strategy and risk tolerance.

As with any AI solution, the best use cases exploit a specific business’s strengths and defend its weaknesses.

Copying use cases from other companies will likely not have the same impact in an organisation with different circumstances. 

Instead, aligning generative AI’s fundamental capabilities to a business’s unique strategies and objectives delivers a value that differentiates a company from its competitors.

Develop generative AI governance and guidelines for acceptable use
Generative AI requires human oversight to ensure that outcomes adhere to the nuance of human judgment and fairness. While generative AI’s output may appear human-like and compelling, the results may not always be accurate, unbiased, or reliable.

CFOs should engage legal, HR, audit, security, and other relevant corporate support functions to establish usage guidelines to minimize security, compliance, regulatory and other intellectual property risk.

This discussion must also include the potential impact to the workforce, company culture and necessary training.

Related:  Five generative AI use cases for CFOs
Tags: CFO issuesfinance functionGartnergenerative AI
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