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How can CFOs ensure AI adoption lives up to the hype?

How can CFOs ensure AI adoption lives up to the hype?
on June 11, 2024
How can CFOs ensure AI adoption lives up to the hype?

CFOs in 2024 continue to face an identity crisis, as new technologies, continued labor shortages and an expanding footprint of responsibilities are rapidly transforming the day-to-day role of finance leadership.

At the heart of this shift is—you guessed it—artificial intelligence, which has been cast as both a boon and a burden to finance teams. That’s because finance leaders are on the front line of both AI deployment and regulation within many businesses—while also being on the hook to ensure new technology deployments deliver on their sky-high promises. 

On the one hand, research from Cognizant shows that AI has the potential to spur more than $1 trillion in economic growth within the United States. This includes a 3.5 percent gain in productivity, with an expectation that AI will greatly impact more than half of jobs by 2032.

So far, however, the AI transformation has yet to pay off for the vast majority of businesses that rushed to embrace the latest tools over the past year. Despite an onslaught of new AI solutions flooding the market, most CFOs are still patiently waiting to see the transformative results.

Generative AI in particular has been used for “at least one business function” among 65 percent of the more than 1,300 companies surveyed worldwide—up from just 33 percent 10 months ago, according to McKinsey

The payoff, however, has been much slower: Only 5.2 percent of companies polled credit generative AI with delivering more than 10 percent of earnings before interest and taxes (EBIT).

This begs the question: Why are teams adopting tools like generative AI if the hype has yet to translate to reality?

What is analytical AI—and where to deploy it

The answer, at least in part, lies in tempered expectations: Much of the “AI revolution” within the workforce has only taken root in the past year or two, with many practitioners still figuring out the best use cases, while solutions providers themselves are finessing their offerings as they gather market intelligence.

But there is also a distinction that must be established between generative AI tools, ala ChatGPT, and analytical AI solutions. 

“Generative AI is no longer a novelty […] The leading companies are the ones that are focusing on reimagining entire workflows with gen AI and analytical AI rather than simply seeking to embed these tools into their current ways of working,” McKinsey Senior Partner Alex Singla said in a statement. 

Analytical AI tools are ones that leverage business intelligence to automate insights and inform processes. So while you may leverage ChatGPT or generative AI tools to speed up production, analytical AI solutions are ones that help teams work smarter.

These include solutions that simplify data collection, data cleansing, and bringing together data sets that may have been previously siloed to help human practitioners better understand their work at hand. 

For finance leaders and CFOs in particular, it’s analytical AI solutions that hold the greatest promise, offering ways for finance teams to keep pace with the rapid rate of change across their workforce and the larger economy. 

According to recent research from the AICPA, new analytical AI solutions “makes it possible [for finance leaders] to create new and better business models and more precisely match value to cost.”

This is valuable for at least two major reasons. First, by combining and aligning disparate data sets for analysis, analytical AI solutions can unlock new perspectives into the business that CFOs can act on—whether that’s poor ROI on certain R&D investments, or inefficiencies elsewhere in the business that may have been hidden in a silo. 

AI tools for co-sourcing on key finance projects

Another critical use case is the ability for finance teams to leverage AI-driven tools to better execute strategic initiatives or special projects. 

In a recent interview with CFO Brew, Deloitte managing director Chris Chiriatti explains that given the continued constraints on staff—with 84 percent of CFOs reporting a substantial talent shortage in 2023, according to data from Milliams Marston—finance teams should not be afraid to look outside for support on special projects or specialized initiatives.

As Chiriatti explains, “it’s recognizing that the financial reporting landscape continues to evolve, and with resources being constrained as they are, it’s very difficult for anyone within an organization—CFOs in particular—to be able to see all and be all.”

Take, for example, applying for R&D tax credits. While this can unlock critical funding that can help teams extend their operational runway and drive even greater innovation, navigating tax code and compiling a claim that passes the increasingly-high scrutiny of regulators can itself be a full time job for finance professionals.

Leaving that money on the table is simply not an option—especially for early-stage businesses who may rely on it for product development, but also for more mature companies that need to stretch their investments as far as possible to achieve growth. 

But when teams partner with experts in the field that leverage analytical AI to optimize their processes and practices—while maximizing claim totals and even handling audit defense—CFOs and finance leaders can focus on other priorities, including driving more AI ROI. 

Boast has helped CFOs across North America streamline the R&D tax credit claim process while maximizing their access to innovation capital to extend their runway. Talk to one of our experts today to see how we can help you. 

CFO AI adoption FAQ

  1. Why are businesses adopting AI tools like generative AI if the results have been underwhelming so far? The adoption of AI tools, including generative AI, is still in its early stages, with many businesses still figuring out the best use cases. However, there is a distinction between generative AI tools and analytical AI solutions, which hold more promise for finance teams.
  2. What is analytical AI, and how is it different from generative AI? Analytical AI tools leverage business intelligence to automate insights and inform processes, such as simplifying data collection, data cleansing, and combining disparate data sets for better analysis. In contrast, generative AI tools like ChatGPT are primarily used for content generation and production tasks.
  3. How can analytical AI benefit finance leaders and CFOs? Analytical AI solutions can help finance teams keep pace with rapid changes by unlocking new perspectives into the business, identifying inefficiencies, and enabling more precise matching of value to cost. These solutions can combine and align data from different sources, providing valuable insights for decision-making.
  4. How can CFOs leverage AI tools for special projects or initiatives? Given the ongoing talent shortage, CFOs can partner with external experts who leverage analytical AI to optimize processes and practices for specialized projects or initiatives, such as R&D tax credit claims. This allows finance teams to focus on other priorities while maximizing access to innovation capital.
  5. What is the role of co-sourcing in AI adoption for finance teams? As financial reporting landscapes continue to evolve, and resources remain constrained, it can be challenging for CFOs and finance teams to handle everything in-house. Co-sourcing with external experts who leverage analytical AI can help finance teams tackle specialized projects or initiatives more effectively while freeing up internal resources for other priorities.


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