15 FP&A statistics on forecasting, spreadsheets, and AI adoption

The FP&A software market was valued at $3.9 billion in 2025 and is projected to reach $9.7 billion by 2033. Finance teams still spend hours consolidating data, updating forecasts, and checking numbers across spreadsheets.

Finance teams need current data behind their forecasts and reports. Aleph connects financial data to existing spreadsheet workflows, and Aleph Agent brings governed data into AI-assisted analysis. Finance remains responsible for assumptions, trade-offs, and approvals.

Key takeaways

• FP&A software spending is growing: The market is projected to grow from $3.9 billion in 2025 to $9.7 billion by 2033.
• Spreadsheets remain central to planning: Research found that 52% of FP&A teams use Excel as their primary planning tool. Finance teams need tools that work with their existing models.
• AI users report stronger forecast quality: In the 2024 FP&A Trends Survey, 65% of teams using AI/ML rated their forecasts as good or great, compared with 40% of teams not using AI/ML.
• Forecasting still involves manual work: 29% of organizations take more than 10 days to finalize a forecast, and only 9% have fully automated driver-based modeling.

Measuring AI adoption in FP&A

The 2024 FP&A Trends Survey found that 6% of surveyed organizations were using AI or machine learning in FP&A. PwC found that 28% of finance departments were using AI for forecasting in 2024. The surveys cover different populations and measure adoption differently, so their results aren't directly comparable.

1. Only 6% of FP&A teams reported AI adoption in 2024

The 2024 FP&A Trends Survey found that just 6% of surveyed organizations were using AI or machine learning in FP&A. The figure shows how limited AI adoption was among the survey's respondents at the time.

2. 28% of finance departments used AI for forecasting

Research from PwC found that 28% of finance departments were using AI for forecasting in 2024, while another 39% planned to use it within the following 12 months. These figures come from a different survey population than the 6% adoption figure above.

Aleph Agent connects Claude, ChatGPT, and Gemini to live, structured financial data through Aleph. It brings Aleph's mappings, audit trails, and traceability into those workflows. The Agent inherits the permissions of the person using it, so each user sees only the data they're allowed to access.

Building and updating forecasts

Forecasting depends on current actuals, clear assumptions, and a process for revisiting the plan. These benchmarks show how often teams update forecasts and how long the work takes.

3. 63% of FP&A professionals struggle to predict beyond six months

Research found that 63% of FP&A respondents couldn't make reliable predictions more than six months into the future. For finance teams building annual budgets or multi-year plans, this makes it harder to rely on a single forecast without revisiting assumptions as conditions change.

4. 29% of teams take more than 10 days to finalize a forecast

Nearly 29% of organizations take more than 10 days to finalize a forecast. That's a long time to wait when revenue assumptions, headcount plans, or spending priorities can change before the numbers are ready.

5. 49% of companies use rolling forecasts

Forty-nine percent of companies used rolling forecasts in 2024, up from 47% in 2023. Rolling forecasts let finance teams update projections as new actuals and business assumptions become available, keeping the plan current as business conditions change.

6. 45% still rely on static planning methods

Despite the use of rolling forecasts, 45% of companies still rely on static planning methods. A static plan records assumptions at a point in time. Finance teams have to revisit those assumptions as hiring plans, revenue expectations, and operating costs change.

7. Only 9% of organizations have fully automated driver-based modeling

Only 9% of organizations have fully automated driver-based models. For many finance teams, updating a forecast still means changing assumptions, checking formulas, and making sure the numbers tie out across different models and systems.

8. 65% of AI users rate their forecasts as good or great

The 2024 FP&A Trends Survey found that 65% of organizations using AI/ML rated their forecasts as good or great, compared with 40% of organizations not using AI/ML. The survey reports higher self-rated forecast quality among AI/ML users. It doesn't establish that AI alone caused the difference.

AI can help finance teams investigate budget-versus-actual movements. Aleph's AI Variance Analysis helps finance teams investigate budget-versus-actual differences and month-over-month changes. Users can drill into the underlying data to review what's driving a movement.

Connecting spreadsheets to live financial data

Excel and Google Sheets remain central to budgeting, forecasting, and reporting. Aleph's native add-ins connect existing models to live data from ERP, CRM, and HRIS systems.

9. 52% of FP&A teams still use Excel for planning

Research found that 52% of FP&A teams use Excel as their primary planning tool. Spreadsheets remain central to budgeting, forecasting, and reporting, even as teams adopt more specialized FP&A software.

10. 22% can run scenarios within a day, but 21% cannot run them at all

Scenario planning capabilities vary widely across organizations. The 2024 FP&A Trends Survey found that 22% can run scenarios within a day, while 21% cannot run them at all. When a team can't test scenarios quickly, even a straightforward question about hiring, revenue, or spending can turn into hours of spreadsheet work.

Aleph's Spreadsheet Add-Ins provide two-way synchronization with live financial data. Finance teams can keep their existing models in Excel and Google Sheets, then double-click a number to inspect the underlying data without leaving the spreadsheet.

Tracking FP&A software spending

Spending on FP&A software reflects demand for budgeting, forecasting, and financial performance management tools. The estimates below cover different market segments and should be read as separate projections.

11. The FP&A software market is projected to reach $9.7 billion by 2033

Verified Market Research estimates that the FP&A software market will grow from $3.9 billion in 2025 to $9.7 billion by 2033. The projected growth reflects continued spending on budgeting, forecasting, and financial performance management software.

12. Cloud-based FP&A tools for public companies were projected to reach $8.5 billion in 2026

In a 2024 report, MGI Research projected that the market for cloud-based FP&A tools among publicly traded companies would approach $8.5 billion in 2026, with a three-year compound annual growth rate of 28%.

This estimate covers a more specific market segment than the broader FP&A software forecast. It points to continued investment in cloud-based planning tools, particularly among companies managing complex reporting and forecasting requirements.

13. The AI in FP&A market is projected to grow at a 34.8% CAGR through 2034

The global AI in FP&A market is projected to grow at a 34.8% compound annual growth rate from 2025 to 2034, reaching approximately $4.77 billion by 2034, up from $240.6 million in 2024.

That projection shows how much spending researchers expect to flow into AI-related planning tools. For finance teams, the practical question is whether those tools can work with their financial data, models, and reporting processes.

Assessing FP&A team performance

Growth-stage companies often need to consolidate financial information across entities, update forecasts before board meetings, and explain changes in revenue or spending. The survey results below cover FP&A teams broadly. They do not isolate VC- or PE-backed companies specifically.

14. Only 19% of teams report being optimized or performing well

The 2024 FP&A Trends Survey found that only 19% of FP&A teams described their performance as optimized or performing well. Many teams still spend substantial time collecting data, checking numbers, and maintaining reports instead of working on financial analysis.

15. 35% of AI users report optimized or strong FP&A performance

The 2024 FP&A Trends Survey found that 35% of teams using AI/ML reported optimized or strong FP&A performance, compared with 17% of teams not using AI/ML.

The survey reports an association between AI usage and stronger self-reported team performance. It doesn't establish that AI use caused the difference. Data quality, planning processes, and the team's ability to use the tools also affect performance.

Assessing where AI fits in FP&A

Comparing AI adoption across surveys

AI adoption varies across finance teams. PwC found that 28% of finance departments were using AI for forecasting in 2024, while the FP&A Trends Survey reported 6% AI/ML adoption among its respondents. The studies cover different populations and use different measures, so the results should be read separately.

The practical question for finance teams is where AI can take on repeatable work. It can help pull together governed data and investigate changes. Finance retains responsibility for assumptions, trade-offs, and decisions.

Using AI to investigate finance data

The survey results point to several areas finance teams can examine:

• Higher self-rated forecast quality among AI/ML users: 65% rated their forecasts as good or great, compared with 40% of nonusers.
• 63% of FP&A professionals struggle to forecast reliably beyond six months.
• 29% of organizations take more than 10 days to finalize a forecast.
• 52% of FP&A teams use Excel as their primary planning tool.
• Only 9% of organizations have fully automated driver-based modeling.

Aleph connects financial data and keeps spreadsheet models tied to source systems. Its spreadsheet integrations provide two-way synchronization with live data, and users can double-click a number to inspect the underlying record. AI Variance Analysis helps finance teams investigate budget-versus-actual movements and review the data behind them.

Aleph Agent works in the Aleph app, Slack, Teams, spreadsheets, Claude, ChatGPT, and Gemini. It brings live, structured financial data, mappings, and audit trails into those workflows, with permissions inherited from each user. Finance teams can hand repeatable process work to the Agent while retaining control over assumptions, trade-offs, and approvals.