Finance leaders are aware of the complexities and challenges that include driving business growth. From navigating the intricacies of enterprise-wide digitization to adapting to changing customer spending habits, the responsibilities of a CFO have never been more varied.
Amid this complexity lies a possibility. CFOs can harness the transformative power of generative AI (gen AI) to revolutionize finance operations and unlock latest levels of efficiency, accuracy and insights.
Generative AI is a groundbreaking technology that can transform the finance industry as we understand it. By using advanced language models and machine learning algorithms, Gen AI can automate and streamline a wide selection of economic processes, from financial evaluation and reporting to procurement and accounts payable.
Recognizing the tremendous advantages of adopting AI in finance
According to a study by IBM®, firms which have successfully implemented AI of their financial processes profit from the next benefits:
- 33% faster budget cycle time
- 43% fewer bad debts
- 25% lower costs per paid invoice
However, to successfully integrate AI into finance operations, a strategic and well-planned approach is important. AI and AI initiatives can only be as successful because the underlying data allows. Companies often adopt various data initiatives to support their AI strategy, from process mining to data governance.
Once the best data initiatives are in place, you ought to construct the best structure to successfully integrate AI into finance operations. This could be achieved by defining a transparent business case that outlines the advantages and risks, securing the needed funding, and establishing measurable metrics to trace ROI.
Next, automate labor-intensive tasks by identifying and targeting tasks which might be suitable for AI generation automation, starting with use cases to mitigate risk and inspiring worker adoption consistent with their real-world responsibilities.
You also need to use new-generation AI to fine-tune FinOps by implementing cost estimation and tracking frameworks, simulating financial data and scenarios, and improving the accuracy of economic models, risk management, and strategic decision-making.
Prioritizing responsibility with trusted partners
As finance leaders navigate the AI ​​landscape, it’s critical to prioritize responsible and ethical AI practices. Data lineage, security, and privacy are primary concerns that CFOs must proactively address.
By partnering with trusted organizations like IBM that adhere to strong trust and transparency principles and pillars of trust, finance teams can ensure their Gen AI initiatives are built on a foundation of integrity, transparency and accountability.
Download the AI ​​in Finance Guide