Source: Deloitte
As of the end of 2022, Generative AI has fully stimulated the public's imagination about the future. Consumers and businesses have been using artificial intelligence for years: conversing with voice assistants like Siri or Alexa, automating repetitive daily tasks, and using algorithms to identify data correlations and patterns. In recent years, AI applications capable of generating original content or digital artwork have rapidly become well-known, heralding the dawn of an era in which artificial intelligence imitates human creativity.
Wherever we go, people are talking about Generative AI. We are at the forefront of a major technological revolution—a significant change for both our personal lives and the business sector. For businesses, Generative AI has the potential to revolutionize the end-to-end value chain of exponential automation, from front-end customer engagement to new revenue sources and back-office functions such as finance. As a result, CFOs need to lead the strategic transformation brought about by artificial intelligence.
Understanding Generative AI
The initial applications of Generative AI may include generating concise and coherent text summaries (such as meeting minutes), transforming existing content into new formats (such as converting text into visual charts), or analyzing the impact of implementing new regulations. The ability to generate novel and unique content represents a clear transformation in the capabilities of artificial intelligence, shifting AI from being a tool that empowers work to a potential capable assistant, and possibly even enhancing human abilities to drive progress in human civilization.
CFOs and financial leaders should start strategizing now and consider how Generative AI will impact finance functions and business in the future.
The Significance of Generative AI in the Finance Field
Generative AI is data-driven, and as the finance field relies on massive amounts of data, leveraging Generative AI to empower finance is the most suitable choice.
Achieving future strategic planning: CFOs may face the challenge of integrating financial data, operational data, and business data, and providing insightful recommendations. Generative AI-driven predictive models can review large datasets in a very short time, display immediate and continuous data trends, and achieve real-time monitoring and forecasting.
Enhancing financial operational automation: CFOs seek to improve efficiency, reduce operating costs, and focus on improving work experiences. Generative AI-driven "agents" further transform the way queries and searches are conducted, and in the future, they may provide tailored content based on individual needs and communication preferences. Generative AI can also enhance the efficiency of financial analysts.
Collaboratively generating financial statements and management reports: While CFOs may not fully trust that AI will generate audited financial statements in the short term, they may be open to it completing initial drafts of reports. Initial drafts of internal and external financial reports completed by highly reliable Generative AI can save finance personnel a significant amount of time at month-end and quarter-end.
Enhancing continuous control monitoring and detection capabilities: CFOs need to be more vigilant in anticipating and mitigating risks, which is more important than ever. Generative AI can analyze transactions in real time and immediately identify issues, thereby enhancing risk management processes with unlimited, synchronous, and continuous anomaly detection. It can also monitor the connection between financial systems and data lakes and promptly alert the finance technology team.
Improving tax processing agility: CFOs hope for greater flexibility and agility in tax functions to create more value. Generative AI solutions in the future may automate tax calculations, generate tax documents (customized according to specific stakeholder and tax authority requirements), and analyze the impact of new regulations, making the tax department more agile.
Finding strategic positioning early in collaboration: Stakeholder management is becoming increasingly complex, and the time for investor relations departments to research strategic information is constantly being compressed. Generative AI models can be trained based on company-specific data, including historical financial data, business department leadership reports, new business and marketing information, historical investor relations materials, and publicly available regulatory and economic information, to generate initial drafts of stakeholder materials.
"A Gartner study shows that 80% of CFOs surveyed in 2022 plan to invest more in AI in the next two years, and about two-thirds of respondents believe that through this investment, their functions will achieve autonomous operation within six years."
The Limitations of Generative AI
Generative AI's Impact on Finance Talent
Finance professionals may need to develop and strengthen skills related to Generative AI, such as how to design prompts (i.e., ask good questions) to obtain the desired results, how to identify potential biases, how to confirm the quality and effectiveness of generated outputs, and how to monitor model performance over time.
Although Generative AI is expected to achieve productivity gains and cost savings, its potential threats should not be overlooked. Generative AI may fundamentally change finance functions. Leading organizations have already initiated pilot programs and are rapidly expanding. In the short term, Generative AI will further automate financial analysis and reporting, reduce risks, and optimize financial operations. However, the impact of Generative AI goes beyond this. With its ability to process large amounts of data and rapidly generate novel content, Generative AI is expected to bring about unforeseen disruptive changes.
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