G&A in AI: Increasing Adoption and Early Use Cases for Finance and People Team Leaders

In mid-2023, the headlines from The Circle on Generative AI in HR were: “too early,” “a lot of hype,” and “not enough practical applications.” Fast forward to one year later, and the conversation has moved from potential use cases to ways CXO leaders are applying AI in creative ways to save time, money, and effort in their G&A functions. 

And yet, AI is still not widely used across growth-stage companies. In a survey of finance and people team leaders in The Circle, 43 percent said they use the technology once a week, while 24 percent said they rarely or never use it. 

During a recent discussion with The Circle, Michele Evans, an AI Advisor and CEO at NxtWaves who has been consulting with CXOs on embracing AI throughout their organizations, and Ben Gammell, the Chief Financial Officer at Brex, shared how CFOs and CHROs can increase AI adoption across their companies. In addition, The Circle members shared early AI use cases for running more efficient G&A operations within their growth-stage companies. 

AI Adoption Starts with Company Leaders 

According to The Circle’s survey, the top tools that finance and people team leaders are using are ChatGPT and Perplexity. However, widespread AI usage is relatively low in most organizations, according to Michele. From her experience consulting with companies, approximately 80 percent of individual employees rarely or never use AI in their work. This shows there is considerable opportunity for company leaders and their teams to embrace and engage with this technology. 

While some companies envision using AI to reduce their workforces, Michele sees AI as an opportunity for companies to make their employees more effective in their work. Think empowering employees, rather than decreasing head counts. 

Early research backs up the view that AI promises a leap in human capability. An MIT study showed that team leaders who used ChatGPT were 37 percent more efficient in their work when using ChatGPT. This time saved can then be applied to higher-level and more creative tasks. 

“AI adoption starts with company leaders. This isn’t something we can delegate.” —Michele Evans, AI Advisor and CEO at NxtWaves

One step toward implementing AI may sound obvious, but it is practical: put an AI app, such as ChatGPT and Perplexity, on your phone, so that it becomes something that you can interact with more easily, especially during breaks in your day. AI is, in many ways, a habit that should be cultivated daily.

Consider Assigning An AI Team to Test Out Use Cases Before You Deploy It Across Your Organization 

One of the more challenging aspects of introducing new technology at an organization is that everyone already has a full-time job; now they are asked to fulfill another task by experimenting with the new tool. 

To navigate this, Brex built a specific AI team to test use cases for its company before any were rolled out across teams or in customer experiences. 

“The AI group was kept separate from the greater company to allow them to have more space to explore different ways AI could help us better serve customers. This allowed us to build our AI uses around the needs of our customers, rather than for the sake of AI.” —Ben Gammell, CFO, Brex

Brex’s test-and-learn approach has allowed Ben and the team to better understand where and how to allocate resources to AI, and to see a clearer picture of the costs associated with it. As Brex integrates AI into its core business, the longer-term goal for the AI team is to re-integrate into their functions and to continue to educate and expand AI to the rest of the engineering, product, and design teams at scale.

Set a Rolling AI Policy and Learn By Committee 

Because AI usage is still in the initial innings, Michele recommends that companies develop guidance on how to use the technology, rather than set rules that are inflexible to change. “Because things are moving so quickly with AI, company policies change often. I’d recommend having a one-pager of do’s and don’ts that is regularly updated based on the technology changes and how your company is using AI.” 

In addition to creating an AI team, companies can also form a department committee that brings together leaders from different functions to share where and how they use the technology. These leaders should include someone from the IT team to ensure the technology is being used properly.

Finance: Early Use Cases

An early trend for finance leaders is that they are integrating AI into their finance tools and systems. Members shared the following use cases:

1. Recap Content: Summarizing lengthy reports and outputs (not creating the numbers themselves). 
2. Review Data: Using AI to compare actual financial results, highlight anomalies, and analyze disparate data sets. AI can then indicate what might be driving the changes and discrepancies. 
3. Automate Compliance: Finance teams can use AI to ensure that T&E policies are followed by using AI to identify and flag any items against company policy. (i.e. with Brex) 
4. Cash Reconciliation: A solution used when a company receives a transaction data dump from its bank’s API and then uses AI to characterize the transactions. Once verified by a human it is automatically posted to the company’s financial management system. This moves a manual process to a (nearly) automated one. 

People Team: Early Use Cases

An early trend for people team leaders is that they are leveraging AI in stand-alone, single-use ways (i.e. not necessarily building AI into existing platforms). Members shared the following use cases: 

1. Leadership Development: Using AI (Bunch AI) as a leadership coach that delivers bite-sized leadership lessons that support an employee’s development journey. This is especially beneficial if you have a limited training budget. 
2. Data Analysis: To analyze HR analytics in real-time and provide answers based on the data sets (i.e. with Presidio). 
3. Data Summaries: To analyze engagement survey results to uncover themes and trends in a way that doesn’t allow for human biases. 
4. Interview Support: To summarize job interviews and turn transcripts into takeaway notes.
5. Strategic Outlines: To help junior employees build out business use cases, with ideas on how that information can be turned into a project plan. (Using this tool to reduce some of the managerial education workload in the company.)

The Takeaway:

As the conversation around AI moves from theoretical to real use cases, more finance and people team leaders are applying AI to their companies to save time, money, and effort in G&A functions. This enhances team effectiveness and efficiency, enabling these functions to become strategic, trusted advisors. With AI handling repetitive tasks, teams can focus on high-impact, strategic initiatives.  Still, there remains significant room for improvement in AI adoption across tech companies. 

Since the technology has moved beyond the hype phase, company leaders can share their early AI wins and learnings across their companies for greater usage. 

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