The office of finance has always played a critical role in driving financial and operational improvements year after year. However, when organizations rely on outdated tools and fragmented processes, progress stagnates. Many still manage financial and operational planning through spreadsheets or disconnected, siloed datasets. These inefficiencies create barriers to optimization, leading to more silos and duplicated efforts and disjointed operations.
Finance leaders today face mounting pressure to do more with less. With rising economic volatility, shifting market conditions, and increasing compliance demands, the traditional ways of managing finance are no longer sustainable. AI is no longer an option; it is a necessity. Organizations that delay AI adoption risk being left behind as their more agile competitors gain speed, accuracy, and deeper insights that fuel better decision-making.
Transforming Finance with AI
AI is redefining finance; AI-driven workflows can offer significant improvements in efficiency by enhancing data quality, reducing human forecast bias, and increasing forecast accuracy. In the Procure-to-Pay process, AI models can help identify fraudulent invoices to significantly reduce financial risk. In Record-to-Report, AI automation streamlines subledger reconciliations and risk-based reconciliations, driving efficiency. In Financial Planning & Analysis (FP&A), augmented intelligence powers algorithmic forecasting models and generates natural language insights, driving consistency and accuracy in financial planning. Organizations that integrate AI into their financial operations can respond quickly to changes in market conditions, reduce cycle times, and make data-driven decisions with confidence.
By automating routine tasks, AI can empower finance teams to focus on the strategic aspects of their roles, fostering a more agile and responsive financial function. The true value of AI lies in its ability to move finance teams beyond tedious back-office work and toward delivering greater strategic value and business impact.
Why Wait? The Cost of Inaction
Finance teams that delay AI adoption can face serious challenges. Without AI, forecasting remains prone to errors from human forecast bias, financial close cycles remain sluggish, and resources are spending valuable time on manual data reconciliation. The longer an organization waits, the harder it can become to catch up. Those that fail to act may struggle to remain competitive as industry leaders harness AI to drive efficiency, reduce costs, and unlock real-time insights.
The Deep Impact of AI on FP&A
Augmented intelligence is making its way into approximately 40% of finance workflows, enabling teams to prioritize high-value activities such as scenario-based decision-making. AI-driven finance processes drive tangible outcomes, such as fast financial closing cycles, accurate forecasts, and better management of risk. By reducing manual interventions, AI can accelerate the financial close process, while its ability to detect anomalies and refine metrics drives actionable insights.
By adopting AI in FP&A, organizations can unlock efficiency gains and make high-quality decisions.
IBM’s AI & Automation Driven Transformation
AI and automation transformation has helped drive $3.5B in savings.
In finance, AI “touchless/low touch forecasting” helped to deliver a benchmark of 95% forecast accuracy. This AI-infused forecasting solution has increased financial planning & analysis productivity 40% since 2021 by integrating our AI ladder including watsonx.ai and IBM Planning Analytics.
Deploying Agentic AI for automation transformation in 2024, is projected to drive an annual 90% reduction in cycle times by automating manual journal processes.
IBM deployed many of these solutions on-premises, with similar capabilities available on IBM Cloud, AWS, and Azure, allowing organizations to tailor their AI strategies to their infrastructure needs.
We have transformed our roles from executing back-office processes to growth enablers ... propelling the business forward.
David Trager
IBM Strategy and Transformation Leader, Chief Data Office
Plan Together, Win Together
Collaborative forecasting integrates insights from multiple departments and brings proactive planning and adaptability to shifts in market conditions. Once teams align on up-to-date data, AI can take forecasting to the next level by:
- Automating data analysis, freeing teams to focus on strategic initiatives.
- Mitigating human errors, bolstering predictive accuracy.
- Enabling "low touch/no touch" forecasting, where AI handles heavy lifting.
The Path to Real Business Impact with AI
Successfully adopting AI requires more than just data; it requires your own trusted and governed data. Without accurate, auditable, and complete datasets, AI models can drift, leading to unreliable results.
IBM’s internal use of Planning Analytics exemplifies this, delivering a touchless / low touch, AI-powered forecasting process that utilizes time-series models to improve accuracy based on historical data and trends.
AI-powered forecasts require at least twice the number of historical periods as the forecast horizon to deliver reliable results.
To maximize AI's potential, businesses should deploy solutions that can scale with growing data, integrate all financial and operational data into a collaborative, governed environment, and leverage in-memory analytics for speed and efficiency. Additionally, embedding generative AI into the forecasting process can enhance predictive accuracy and decision-making.
Generative AI: The Forecasting Edge You Need Today
Generative AI is revolutionizing forecasting by automating predictive analytics, detecting anomalies, and incorporating external drivers such as weather, market trends and consumer behavior. Finance teams can choose either a traditional time-series forecast or an enhanced multivariable forecast.
More than just a tool, Generative AI can provide finance teams with the flexibility to choose forecasting methodologies that best fit their business needs; helping them allocate resources effectively and adapt to market dynamics with precision.
AI in Finance Is No Longer Optional—It’s Essential
For businesses of any size, integrating AI into finance functions can empower your workforce to achieve more with less. It drives transformation from manual, spreadsheet-based analysis to data-driven decision-making. By automating key processes, you can not only boost efficiency, but you drive resilience and agility allowing decision makers to respond quickly in today's dynamic business environment.
The future of finance is AI-powered, collaborative, and insight-driven. The question is no longer whether to adopt AI—it is about how fast you can integrate it to drive business impact. AI in finance isn’t the future; it’s the present. The time to act is now.
