Guide · June 26, 2025

The CFO's Guide to Leading with Foresight: AI-Driven Scenario Planning

Key takeaways

Traditional forecasting falls short amid volatility and disruption — AI built for Finance helps model a wide range of potential futures for faster, more resilient decisions.
Scenario planners can reforecast earnings within a week 77% of the time, versus just 41% for organizations that don’t use scenario planning (FSN survey).
Scenario planners are nearly twice as likely to forecast a year ahead with confidence (31% vs. 16%).
Manual, spreadsheet-driven processes hold most organizations back: scenario planners are far less likely to have spreadsheets that severely limit variables (23% vs. 80%).
Endeavour Energy cut forecasting time 99.7% (two days to ten minutes) and lifted forecast accuracy from 94% to 98% with OneStream’s SensibleAI Forecast.

Introduction

In an era marked by persistent economic volatility, geopolitical instability, and rapid technological disruption, Finance leaders are under more pressure than ever to anticipate the unexpected. Traditional forecasting methods, while still valuable, often fall short in a world where market conditions can shift overnight. For CFOs and Financial Planning and Analysis (FP&A) teams, the challenge is no longer just about accuracy — it’s about agility, resilience, and readiness.

For most CFOs and FP&A teams, change has become an ever-present constant. Yet despite the most advanced technologies available, predicting the future with 100% accuracy is still impossible. AI solutions are often touted as a magic bullet that can solve every problem for everyone, creating mistrust especially in the Finance community. AI built for Finance — purpose-built, AI-powered scenario planning, not AI for resumes or for checking grammar — equips organizations to model a wide range of potential futures, enabling faster, smarter decisions in the face of ambiguity. It doesn’t replace the human element of forecasting entirely, but it does enrich the process. By leveraging the explosion of available data and AI automation capabilities, Finance can move beyond reactive forecasting and look forward to a proactive strategy. This approach not only helps identify risks and opportunities earlier but also empowers teams to act decisively — outpacing competitors and safeguarding long-term performance.

Why Scenario Planning Matters

Organizations that make the time for scenario planning see measurable improvements in budgeting, planning and forecasting results, according to the FSN survey. In fact, 77% of organizations that utilize scenario planning can reforecast earnings within a week. Nearly double the number of scenario planners (31%) can forecast a year ahead compared to their non-scenario planning counterparts (16%). The value of incorporating scenario planning generates improvements across many areas of the forecasting process, shown below.

Scenario planners outperform non-planners on every FSN stress test

Reforecast earnings within a week41%77%

Forecast a year ahead with confidence16%31%

Forecast revenue within ±5%41%54%

Forecast earnings within ±5%36%54%

Make a minor budget change within half a day58%83%

Roll out a budget change to templates within half a day65%92%

Reflect a change in all reports within half a day40%67%

Make a simple hierarchy change within half a day30%50%

FSN survey stress tests: non-scenario planners vs. scenario planners
Capability	Non-scenario planners	Scenario planners
Reforecast earnings within a week	41%	77%
Forecast a year ahead with confidence	16%	31%
Forecast revenue within ±5%	41%	54%
Forecast earnings within ±5%	36%	54%
Make a minor budget change within half a day	58%	83%
Roll out a budget change to templates within half a day	65%	92%
Reflect a change in all reports within half a day	40%	67%
Make a simple hierarchy change within half a day	30%	50%

Source: FSN survey.

Unfortunately, however, despite these huge benefits to financial outlooks and results, the adoption of scenario planning remains low. But why? Well, performing scenario planning with outdated technologies, manual processes and manual data gathering is often inaccurate and inefficient. In other words, planning under such circumstances simply takes too much time to provide valuable insight.

Business Challenges

Why are so many organizations slow to adopt scenario planning despite its demonstrated value? When the process relies on too much manual intervention, Finance lacks control and repeatability in the process. These shortfalls lead to too much time wasted wrangling and analyzing data and leaving too little time to draw meaningful insights that lead to strategic decision making. Relying on fragmented silos of spreadsheets and legacy corporate performance management (CPM) software for planning needs ultimately results in disjointed processes around technology and inhibits key collaboration and business agility required to drive performance in an environment where speed is king.

Scenario planners are less likely to use spreadsheets

Spreadsheets severely limit the number of variables80%23%

Data is actively managed as a corporate asset16%67%

Scenario planners vs. non-scenario planners on spreadsheet reliance and data management
Metric	Non-scenario planners	Scenario planners
Spreadsheets severely limit the number of variables	80%	23%
Data is actively managed as a corporate asset	16%	67%

As a result, the overwhelming majority of organizations cannot find sufficient time and manpower to engage in effective scenario planning. A major contributor is a lack of maturity in technological enablers; organizations currently leveraging scenario planning are doing so with better technology and better processes. For CFOs and FP&A teams seeking to enable their business partners with effective scenario planning, automating and streamlining the process with AI built for finance will improve accuracy and eliminate painful, time-consuming manual processes. Finance leaders who successfully do so can confidently lead their organizations through unprecedented levels of uncertainty.

Creating Agility with AI-Powered Scenario Planning

AutoAI solutions such as OneStream’s SensibleAI™ Forecast break down the barriers that have traditionally held back Finance and operations teams by powering scenario planning with time-series ML forecasting across hundreds or even thousands of targets — and do so at scale within a seamless user experience and single solution.

The benefits of AI-powered scenario planning include the following:

Enhanced Speed and Accuracy

AI-powered scenario planning automates many manual tasks involved in traditional scenario planning, ultimately reducing the time to generate and share the results. In addition, in today’s digital economy, companies have access to more data than ever. AI can process this ever-growing data and consider additional business intuition — such as events, pricing, competitive information and weather — to produce more accurate scenario predictions. AI-enabled scenario modeling can automate a lot of the repetitive, menial tasks required in scenario planning and provide more time for analysts to develop strategic recommendations for the organization.

Improved Risk Management

Finance can identify and react to potential risks easier and quicker, as well as more effortlessly capitalize on opportunities by leveraging AI-powered scenario planning. For instance, AI can incorporate substantially more drivers, both internal and external, to automatically identify correlations, patterns and anomalies across thousands of products and locations, which can then be used to make better-informed decisions on managing risk and preparing for potential scenarios. This efficiency will dramatically cut down the amount of time needed to complete various “what-if” analyses to better plan for the rapidly changing environment. Now, planners can focus more on leveraging the potential scenarios rather than producing them.

Better Cross-Functional Collaboration

Machine learning has the capability to forecast at very granular and frequent levels to support processes such as demand planning and S&OP processes where planning by product and/or region is required. Such forecasting can be done on a daily or weekly basis. These processes drive cross-collaboration between operational and financial scenario planning. In essence, effective scenario planning looks across the organization for various scenarios that might impact financials, negatively or positively, and that process requires cross-functional collaboration outside the Finance department and across various lines of business. Engaging in scenario planning creates a process by which scenario planners broaden their awareness of external influences and appreciate the importance of including a wide range of inputs in planning, budgeting and forecasting.

Increased Strategic Decision-Making

Ultimately, all the benefits gained through AI-powered scenario planning result in better strategic decision-making. By analyzing more data faster and with better accuracy, analysts can then use their time to take a more comprehensive approach to various possibilities and how they would impact the company’s financial health. This approach gives Finance leaders visibility into how various scenarios would impact cost of goods sold (COGS), gross margin, EBITDA, cash flow and other important financial metrics that are critical KPIs to understand when navigating uncertainty. All leaders want timely and accurate insights to increase performance efficiently and effectively, and AI-powered scenario planning will help leaders do just that.

Customer Story: Endeavour Energy

One of our customers is Endeavour Energy, a major electricity network operator in New South Wales, Australia. They serve 2.7 million people across a vast and diverse 25,000 square kilometer footprint. From coastal suburbs with 80% solar uptake (compared to the state average of 25%) to bushfire-prone bushland and mountainous terrain, Endeavour’s network faces unique operational challenges.

2.7M
people served across Endeavour Energy’s network
25,000 km²
service area, spanning coastal, bushfire-prone, and mountainous terrain
12 weeks
to implement OneStream’s SensibleAI Forecast solution
2
people on the lean implementation team

Rapid growth driven by the Western Sydney Aerotropolis and a surge in data center development — each consuming power equivalent to 15,000 homes — has added further complexity to forecasting and infrastructure planning. With data centers expected to double and consume 8% of total grid power by 2030, Endeavour faced a critical challenge: forecasting revenue and demand for customers that don’t yet exist. Historical forecasts were off by 6% to 8% annually, and the volatility was compounded by a recent SAP go-live that unlocked granular data across one million customer accounts.

That’s when OneStream stepped in. In just 12 weeks, Endeavour implemented OneStream’s SensibleAI Forecast solution with a lean team of two and support from OneStream. The results were transformative. The Finance team, without needing coding expertise or dedicated data scientists, could now run scenario models on demand, including testing impacts of La Niña weather or shifting data center loads. Endeavour then empowered its Finance team to own and operate the forecasting process, eliminating key-person dependencies and accelerating decision-making.

Forecasting time: a 99.7% decrease

FromTwo days

ToTen minutes

Forecast accuracy over six months

From94%

To98%

mean squared error improvement over EDI

mean squared error improvement over the human-adjusted EDI

With OneStream, Endeavour Energy has not only improved forecasting precision but also built a scalable, agile foundation to support the region’s explosive growth, ensuring the lights stay on for millions of Australians, today and tomorrow.

Conclusion

AI-powered scenario planning offers significant benefits to Finance professionals navigating today’s rapidly changing business environment. Despite this demonstrated value, however, many organizations continue to under-utilize scenario planning due to a lack of time and technology to support a process that requires substantial amounts of data for anomaly detection. AI-powered scenario planning unleashes the true value of Finance teams by enabling faster decisions, increasing better and more frequent collaboration, and increasing forecasting accuracy to drive better strategic decision-making with AI built for finance.

At OneStream, we call this Intelligent Finance.

Request a demo → See how OneStream’s SensibleAI™ Forecast brings AI-powered scenario planning to your Finance team.

FAQ

Frequently asked questions

What is AI-powered scenario planning?

It’s AI built for Finance — purpose-built for scenario planning, not generic AI for resumes or grammar-checking — that helps organizations model a wide range of potential futures. It doesn’t replace the human element of forecasting; it enriches it, letting Finance move from reactive forecasting to a proactive strategy that identifies risks and opportunities earlier.

Why does scenario planning matter for CFOs and FP&A teams?

Per an FSN survey, organizations that use scenario planning see measurable gains: 77% can reforecast earnings within a week, versus 41% of organizations that don’t use scenario planning. Scenario planners are also nearly twice as likely to forecast a year ahead with confidence (31% versus 16%).

What’s holding organizations back from adopting scenario planning?

Outdated technology and manual, spreadsheet-driven processes. Scenario planners are far less likely to have spreadsheets that severely limit the number of variables they can model (23% versus 80% of non-planners), and far more likely to manage data as a corporate asset (67% versus 16%).

What are the main benefits of AI-powered scenario planning?

Four stand out: enhanced speed and accuracy, improved risk management, better cross-functional collaboration, and increased strategic decision-making — all driven by AI’s ability to process more data, surface correlations and anomalies, and free analysts from repetitive manual work.

How did Endeavour Energy use OneStream’s SensibleAI Forecast?

In just 12 weeks, Endeavour Energy — an Australian electricity network operator serving 2.7 million people — implemented SensibleAI Forecast with a lean team of two. Forecasting time dropped 99.7% (from two days to ten minutes) and forecast accuracy improved from 94% to 98% over six months, without needing dedicated data scientists.