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

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.

Why Scenario Planning Matters

Business Challenges

HOW A RAPIDLY GROWING ENERGY PROVIDER SHARPENED THEIR FORECAST ACCURACY ANDCUT FORECASTING TIME WITH SENSIBLEAI

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CONCLUSION

CUSTOMER SUCCESS

Creating Agility with AI-Powered Scenario Planning

BUSINESS CHALLENGES

Why Scenario Planning Matters

Introduction

Creating Agility with AI-PoweredScenario Planning

CONCLUSION

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 (see Figure 3) 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.

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 (see Figure 2). Scenario planners can make changes to the budget, roll those changes out to data entry templates, reflect those changes in reporting to stakeholders and make changes to hierarchy structures within half a day — and do it all in higher numbers across the board compared to those who don’t use scenario planning. 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.

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 (see Figure 1). 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.

SCENARIO PLANNING PROCESS

FIGURE 1: SCENARIO PLANNING

STRESS TESTS

Scenario Planner

Do Not Use Scenario Planner

SPEED

1. Able to reforecast earnings in under a week?

DIRECTION

2. Able to forecast a year ahead with confidence?

ACCURACY

3. Able to forecast revenue to within +/- 5%? 4. Able to forecast earnings to within +/- 5%?

AGILITY

5. Able to make a minor change to the budget within half a day? 6. Able to roll out a minor change to budget holder’s templates in half a day? 7. Able to reflect a minor change in all reports within half a day? 8. Able to make a simple change to a hierarchy in half a day?

77%

41%

31%

54% 54%

83% 92% 67% 50%

16%

41% 36%

58% 65% 40% 30%

Scenario planners are twice as likely to be able to forecast a year ahead.

FIGURE 2: SCENARIO PLANNING FSN STRESS TESTS

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.

SCENARIO PLANNERS LESS LIKELY TO USE SPREADSHEETS

23%

80%

% of organizations whose spreadsheets severely limit the number of variables

67%

16%

% of organizations whereby data is actively managed as a corporate asset

SCENARIO PLANNERS

NON-SCENARIO PLANNERS

FIGURE 3: SCENARIO PLANNING COMPARISON

AutoAI solutions such as OneStream’s SensibleAI™ Forecast (see Figure 5) 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 for targets — and do so at scale within a seamless user experience and single solution (Figure 4).

FIGURE 4: SEAMLESS USER EXPERIENCE AND SINGLE SOLUTION

The Benefits of AI-Powered Scenario Planning Include the Following:

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.

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.

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 (Figure 5) and appreciate the importance of including a wide range of inputs in planning, budgeting and forecasting.

FIGURE 5: SENSIBLEAI FORECAST FEATURE LIBRARY PAGE WITH EXTERNAL VARIABLES

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.

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. 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.

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 process that 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 builtfor finance.

AT ONESTREAM, WE CALL THIS INTELLIGENT FINANCE.

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Enhanced Speed and Accuracy

IMproved risk management

better cross-functional collaboration

increased strategic decision-making

35%

10%

FIGURE 6: IMPROVED ACCURACY WITH SENSIBLEAI FORECAST

MEAN SQUARED ERROR IMPROVEMENT OVER EDI

MEAN SQUARED ERROR IMPROVEMENT OVER THE HUMAN-ADJUSTED EDI

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. Forecasting time decreased 99.7%, from two days to ten minutes. 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. Forecast accuracy also improved from 94% to 98% over six months, thanks to continuous model training. Endeavour then empowered its Finance team to own and operate the forecasting process, eliminating key-person dependencies and accelerating decision-making. 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.