Supercharge your Finance workforce with GenAI
Create a roadmap for success
Knowledge workers in finance鈥攁nd across the enterprise鈥攈ave significant opportunities to capture value and reshape the workforce with the use of generative artificial intelligence (GenAI). Realizing these opportunities would require identifying and augmenting previously hard-to-automate tasks.聽
Beyond the hype: What's in store for finance?
GenAI goes a long way toward solving one of the biggest pain points in finance: manual processes. Labor-intensive systems increase the risk of human errors, consume valuable resources, and limit real-time insights. While GenAI is not a replacement for human judgment鈥攁t least not in the foreseeable future鈥攖eams can work聽smarter聽with GenAI as a starting point.
Given the broad role for finance in strategy and risk management, finance professionals are uniquely positioned to spearhead GenAI. But they first need to determine the potential value of GenAI across their enterprise through the lens of workforce capacity and productivity.
As complex analytical creativity and decision-support activities are automated, finance can scale and do a lot more with less. The traditional pyramid structure鈥攚ith inputs from a large base of people being reviewed and updated at every layer of a smaller team鈥攚ill transform into a diamond when first-pass insights are processed by GenAI.
This transformation leads to increased efficiency, both within finance and across commercial and operational functions; however, it raises the need to care for compliance.聽
Connecting GenAI to enterprise strategy, business value, financial goals and the workforce with great clarity is critical to launching and scaling a successful GenAI program.
Per Edin
乐鱼（Leyu）体育官网 Principal
GenAI has the potential to increase the speed and quality of intelligence and drive better business outcomes.
For example, cycle times to develop financial commentary and analysis, which are significant for most organizations, can improve exponentially through GenAI.
From the perspective of enterprise performance management, GenAI can use internal data sets to develop preliminary insights, recommend actions to mitigate risks, or capture opportunities. It can also integrate external data, such as competitive intelligence, in a faster, more effective way to improve decision making.
With growing possibilities for GenAI tools, new roles and skill sets are emerging. Prompt engineering, creative design thinking, and a drive for continual learning are increasingly important. Strong foundational competencies in data and analytics are essential to interpreting and working with insights generated by AI tools.聽
Yet many finance professionals are still figuring out how to implement the technology on a day-to-day basis. In a KMPG webcast , Reshaping your Finance Workforce with Generative AI, 66 percent of finance professionals said they are in 鈥渓earning mode鈥� when it comes to their level of awareness and experience with GenAI.
GenAI alone will not solve all problems
GenAI is another component that needs to be integrated into the digital ecosystem. Organizations still need to drive standardization and adoption of other technologies, such as cloud solutions, machine learning, and robotics for data sets that get value from GenAI.
- Accelerate growth:聽Enabling faster, more effective innovation and investment decisions
- Improve profitability: Integrating GenAI across systems to enhance forecasting and enable optimal resource allocation
- Increase profitability and efficiency:聽Focusing on knowledge workers and capabilities
- Enable dynamic risk management and compliance:聽Proactively addressing governance, regulatory requirements, and ethical dilemmas
Drawing a roadmap for talent
Another major pain point for finance is attracting knowledge workers with GenAI skills. The skillset is not as specialized as coding or regulatory compliance. It鈥檚 more about adopting GenAI and learning how to apply the solutions. Yet this talent pool is in high demand and costly, so organizations would be well served to map out a training program.
Key roles, both unique to a business and common across front-, middle-, and back-office functions, represent significant opportunities for efficiency. An enterprise value roadmap is the place to start.
Finance can navigate by identifying discrete use cases that have a direct impact on growth, gross margin, cost takeout, and people. The goal should be to achieve tangible quick wins that will naturally build momentum. 聽
Adopting a unified approach for technology and the workforce is critical. We recommend a methodical three-step method to drive workforce transformation with GenAI:聽
1: Identify the roles most affected by GenAI and quantify the impact on the work they perform.聽
2: Develop proof-of-concept pilots and outside-in analyses, focusing on capacity gains, job deconstruction, and role augmentation. Then test, deploy, and scale.
3: Reshape the workforce structure by rethinking your operating model and talent agenda in alignment with GenAI. This will inform the overall workforce strategy.聽
A data-driven view can be the basis for an integrated plan that quantifies estimated value and investment.
Return on investment depends on your strategy, sector, and business model.聽The ROI can come from growth and increased revenue, both organic and inorganic. It may come from profitability based on better pricing, dynamic pricing, or operational efficiency.聽The success criteria must be defined and tie back to your strategy so you can prioritize. Where are the best tactical opportunities for the near-term versus strategic long-term goals?聽Finally, consider the competitive environment and threat that AI may have on your business model. New products or services may be needed. Strategic alliances with vendors or partnerships could be necessary.
Closing thoughts
As companies begin building their AI capabilities, creating strategic partnerships with the right vendors will help support short- and long-term transformation goals. Now is the time for chief financial officers to consider the commercial and operational applications of GenAI that will have the most impact.聽
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