Gen AI: Why finance should lead
The finance team is uniquely positioned to unlock generative AI’s enormous potential for the entire enterprise. Here’s how it works.
Generative AI has quickly moved from an intriguing new technology star to a potential business-transforming supernova.
Indeed, for many organizations today, the Gen AI discussion is no longer “Should we do it?” but “How do we do it?” Leading companies are fully leaning into Gen AI’s potential to accelerate growth and reimagine how the company works, as our recent KPMG surveys have shown, with 8 in 10 business leaders citing Gen AI as their company’s top priority and most impactful go-forward opportunity.
But where do you start? The answer, for many companies, is the finance team, as we detail in our new report, “Why finance should lead the adoption of generative AI.”
Many of Gen AI’s unique superpowers—combing through complex data, spotting inaccuracies, identifying opportunities, and generating high-quality business forecasts and reports—are precisely why finance should be the tip of the spear on Gen AI adoption and execution for the entire enterprise.
An intelligent pairing
Gen AI is a rapidly emerging subset of the larger AI umbrella that includes established technologies such as predictive modeling and machine learning, which have already demonstrated real results for businesses in areas such as improved forecasting accuracy and increased business process automation.
To date, these now-proven AI tools have largely relied on well-structured data to deliver clearly defined outputs. Enter Gen AI, which significantly expands AI’s capabilities in several powerful ways. Gen AI is able to mine both structured and unstructured data (audio, video, images, PDFs of competitors’ public filings, news and weather reports, etc.) and create high-quality, human-level outputs that can be customized in multiple ways—from executive summaries, to real-time forecast updates, to detailed reporting for multiple business teams.
Now overlay those Gen AI-powered capabilities with the finance team, and its charter to:
- Be the steward of all types of data from across the company, both internal and external
- Improve the speed, accuracy, and value of business intelligence and forecasts
- Manage multiple types of reports, from one-pager board-level summaries all the way through to detailed compliance filings
- Identify strategic opportunities and risks
- Dynamically connect the company across the front, middle, and back offices.
In so many ways, then, the finance team is uniquely equipped to lead the whole organization on that “How do we do it?” challenge of Gen AI, guiding an execution strategy that fully considers the opportunities, risks, and tradeoffs of the technology’s potential applications across the enterprise.
Once the organization is ready, generative AI solutions are available and relatively simple to roll out. Building them as complements to existing AI systems can provide a new layer of contextual value-add to data.
From the KPMG report, “Why finance should lead adoption of generative AI”
Beyond just being uniquely suited to lead on Gen AI, finance is also in pole position to benefit from Gen AI’s unique applications most immediately. Here are six ways finance teams are already exploring Gen AI to enhance functions and deliver more value:
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Some of the capabilities mentioned above are already on the leading edge of Gen AI execution, with 83 percent of business leaders reporting their finance and accounting teams were actively exploring the technology to improve data insights, financial planning, and budgeting.
In many cases, these new applications are available and relatively simple to roll out. But rather than stand-alone technologies, these new Gen AI applications for finance are deployed as an extension of the organization’s existing AI platform—creating the model for how the company can more seamlessly extend the technology to other business functions down the line.
A roadmap to deliver
Of course, leading on Gen AI means managing the risks and obstacles as well. The finance team will have to help the organization balance and quantify the delta between quick action and risk mitigation in every possible use-case.
Gen AI will require strong governance, a clear understanding of potential ethical and regulatory concerns, and unflinching partnerships—both across the organization and with external technology providers. Among the most immediate concerns:
Our report expands further on these concerns, identifying an actionable, eight-step “get-started” plan that can empower the finance team to lead on Gen AI in partnership with the whole organization, building an institutional framework for Gen AI that matches the organization’s risk tolerance, cultural complexity, and investment appetite for technology-led transformation.
Dive into our thinking:
Generative AI guidance for CFOs
Learn more about the “get-started” plan and check out the full report.
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