The Quick Read
- Generative AI’s impact on productivity could add trillions of dollars in value to the global economy each year [1], while 86% of financial services executives plan to increase AI-related investments by the end of 2025 [2].
- 64% of finance chiefs believe that generative AI will be running many of today’s finance tasks within the next six years, but less than 21% use machine learning, prescriptive analytics, and other generative AI tools [3].
- Firms that rush to over-implement AI technologies risk errors. Augmenting people’s skills and capabilities is where the most ambitious companies are headed. Power skills—communication, learning, negotiation—will increase in importance as AI resolves routine work.
AI is set to revolutionise the workforce. As the cost of knowledge drops, CFOs face new challenges in understanding the allocation of resources and long-term financial strategy.
As we set course on a period of job-related turbulence, CFOs will seek to balance the short, mid, and long-term risks and rewards associated with AI-powered innovations. Above all they, along with all business leaders, will look to make sure the benefits of AI are realised by augmenting humans, not replacing them.
What’s the risk?
The potential of generative AI is perhaps unparalleled. But companies who rush to over-replace human talent risk organisational instability.
Removing resources and placing too much trust in these relatively new generative technologies can leave organisations vulnerable to errors. For example, Google CEO Sundar Pichai says ‘hallucination problems’ - when a large language model (LLM) generates false information - are still a considerable risk factor and the full causes of these faults are still unknown [4].
Organisations that redistribute too many staff at once risk talent vacuums, yet a failure to invest in generative AI products and policies may also leave organisations vulnerable to a lack of trade knowledge and best practices, leading them to fall behind.
Ignoring AI also poses the risk that it is used unofficially across the company in an unregulated way: 46% of employees admit they’re using AI without their employer’s consent [5]. Sharing sensitive organisational information with new and developing generative AI platforms, needless to say, carries risk. Rushing to implement monitoring systems might seem like a simple solution, but adding layers of surveillance erodes trust. Going back to basics - investing in access controls, two-factor log-ins, and reinforcing security compliance - is perhaps more important than ever.
What’s the reward?
McKinsey currently rates the efficiency gains from generative AI at 60-70% [1]. These gains aren’t simply a result of cutting time. Natural language searches are transforming our understanding of knowledge and skill efficiency is moving from retention to analysis.
AI can analyse and learn from multiple formats. They do this by using “natural language models”. These are the ways that models combine text, audio, video, and image to learn and create something new. These are known as “multimodalities”, and they can help employees to work in formats they’re more comfortable with. Inclusivity can also increase as employees can work with information from multiple sources, informing deeper and more nuanced finance models and projections.
The new generation of AI also offers adaptability or personalisation algorithms. Staff can benefit from increased efficiency in learning programmes — only learning what is necessary.
CFOs who understand the realities of AI can leverage its potential to create a more accessible and fluid workforce, working across departments and evolving the role of finance teams as the technology advances.
The Deep Dive
AI entrepreneurs like Jensen Huang, of the recent trillion-dollar silicon chip NVIDIA, are talking about the upcoming period of turbulence as the nature of work evolves.
The true value of AI lies in augmenting human performance, not replacing it. In a world where many CFOs are evolving their practice to a more strategic role, what are the skills they need? How about their teams? And which positions will still exist, and which will be improved by automation?
AI in finance teams
Increasing efficiency is a regular priority for CFOs. Tomorrow’s AI-augmented roles could see the majority of today’s rote tasks sourced to AI, with the strategic, big-thinking, creative tasks freed up for human employees.
Through robotic process automation (RPA), routine manual processes and rules-based tasks such as downloading an attachment, scanning the contents, and entering the information into a form can be taken off finance teams’ workloads. With this routine work complete, finance teams can spend more time on insight, analysis and strategic work that is of more value to the company.
AI can help here too, for example by drastically reducing the time it takes to discover outliers in financial reports and forecasts, identifying potentially missing, incomplete or incorrect datasets. There’s even the potential to use AI to adjust budgets and forecasts in real-time.
Without the need to crunch data, tomorrow’s CFOs will have the ability to concentrate on more valuable insights, creativity and lateral thinking, where humans excel.
However, as we transition to asking platforms detailed questions and receiving rich, detailed answers, CFOs need to invest time in the learning and development of their teams [6]. Just 14% of employees have received training on how AI will change their role [7].
CFO skills
CFOs are responsible for some of the most strategic judgement calls on the board. So, while generative AI will provide more data and information, the strategic CFO will evolve their practice to concentrate on higher-level analysis, peer-to-peer communication, and those ever-difficult judgement calls.
For example, predictive analytics can improve management practices such as scenario planning and simulative forecasting. Meanwhile, in an area such as supply chain management, data on climate, trends, politics and economics can be analysed in real-time alongside financial data to enable strategic decision-making. For the CFO, getting that decision-making right will depend on improved data analysis skills and greater collaboration with colleagues across departments.
It will also ultimately mean greater collaboration with AI itself, where humans and machines are employed as equal agents in the process. This is known as cooperability, using reinforcement from human learning (RLHF) to inform generative AI.
CFOs can use the potential of cooperability to simulate almost anything. Take the HR practice of people analytics [8]. This analytical method takes real-time data to inform policy, improving well-being in the workplace. CFOs and CHROs can collaborate, identifying solutions to staff problems. They can, for example, check staffing for inclusivity or model future staffing patterns. Used well, AI can help CFOs and other senior leaders in the business to build human-centric organisations.
But every tool comes with its own risks. Outsourcing all our decision-making to generative technologies opens us up to liabilities. CFOs risk embedding errors into the substrate of their businesses and must not overestimate efficiency gains. By pushing cost-saving too aggressively, CFOs risk giving staff insufficient time and effort to learn how to use AI well, how to fact-check all outputs and create something valuable for their business.
CFOs also need to understand how to invest in generative AI. With 46% of employees using generative AI without consent, organisations are at considerable risk of data leaks [9]. CTOs who lead a C-suite AI strategy will allow CFOs to leverage the potential of AI to safely create new, exciting and effective strategies.
Generative AI has potential that no one quite understands yet. By understanding the rewards and risks of the technology, CFOs can lead their organisations into the future. One where the human skills of cooperation, communication and collaboration will always be critical.
To learn more about the trends and risks occupying CFOs minds today, read the American Express 2023 CFO Survey.
Sources:
[1] McKinsey, The economic potential of generative AI: The next productivity frontier, 2023
[2] ThoughtSpot, AI: The Future of Financial Services
[3] Gartner, Move Towards an AI-Forward, Autonomous Finance Future
[6] Management Today, Why L&D should be at the forefront of the AI revolution, 2023
[9] Bloomberg, Samsung Bans Staff’s AI Use After Spotting ChatGPT Data Leak, 2023