When spreadsheets first entered the world of finance, many viewed them as an easy way to augment their ERP systems that were complex and difficult to modify. Today, it’s nearly unheard of to run financial planning and analysis (FP&A) processes without them. Spreadsheets didn’t diminish the role of financial experts; they amplified their strategic value by enabling agile and unconstrained financial modeling.
Artificial intelligence (AI) is at a similar inflection point, particularly within financial planning. Some organizations still perceive AI as just a way to help minimize manual tasks within complex landscapes and processes. However, this viewpoint can introduce a critical blind spot for any organization seeking to be agile and forward-looking.
AI has graduated from a buzzword to a fundamental component of modern FP&A. As finance teams increasingly aim for agility, precision, and strategic foresight, AI’s true potential should be recognized and built into core planning processes, so that it can be leveraged to make faster, smarter, data-driven decisions.
The business case: AI embedded in the planning cycle
For AI to be effective in financial planning, it can't be a bolt-on solution. It must be woven into the fabric of the planning cycle, guided by strong governance and ethical principles. The most impactful AI is one that lives within the same platform where budgets are set, forecasts are generated, and scenarios are modeled.
Anaplan has AI capabilities at the core of our unified planning platform, ensuring that intelligence operates on a consistent and secure data foundation. Anaplan Intelligence is designed for the enterprise, bringing predictive forecasting, anomaly detection, and intelligent recommendations into the workflows that FP&A teams use every day. With AI embedded within our planning models, we ensure that the insights are explainable, auditable, and directly relevant to your business context.
How financial planning transforms with AI
Teams that embrace integrated AI don't just produce plans faster; they produce more intelligent and resilient plans, easily incorporating updated drivers and variables. The practical benefits of AI in financial planning are clear and compelling:
| Benefits | The challenge | The AI solution |
|---|---|---|
|
Enhanced forecast accuracy |
Traditional forecasts are often hindered by human bias, incomplete data sets, and an inability to process complex, non-linear variables. |
AI algorithms can analyze vast internal and external data sets, whether structured or unstructured, identifying hidden drivers and removing human bias to produce more accurate and reliable predictions. |
|
Reduced cycle times |
Manual data gathering, consolidation from multiple spreadsheets, and validation can turn forecasting into a lengthy, resource-draining ordeal that takes weeks or even months. |
AI automates data integration and analysis, reducing the planning and forecasting cycle from months to days, or even hours. |
|
Deeper strategic insight |
Analysts spend significant time on low-value data wrangling, leaving little opportunity for the high-value strategic analysis the business actually needs. |
By automating repetitive tasks, AI frees analysts to focus on interpreting the "why" behind the numbers and acting as true strategic partners to the business. |
|
Dynamic scenario modeling |
Manually creating and comparing a handful of scenarios is so time-consuming that it limits an organization's ability to prepare for market volatility and unexpected events. |
AI allows teams to run dozens or even hundreds of scenarios in minutes, stress-testing plans against a wide range of potential outcomes and building true organizational resilience. |
A blueprint for leading your AI transformation
For leaders, bringing AI into the finance function is more than a technical implementation; it’s a change in management and culture. It requires a deliberate approach focused on building trust, capability, and strategic value.
1. Shift the narrative from "adoption" to "augmentation":
Instead of introducing AI as a tool the team must adopt, frame it as a capability that will augment their expertise. The goal isn't to replace human judgment but to elevate it. Communicate a clear vision where AI handles the repetitive, low-value work, freeing up your team to focus on strategic analysis, business partnering, and decision support — the work that truly adds business value.
2. Champion "glass box" intelligence over black boxes:
Trust is the currency of finance. A "black box" AI that provides answers without explanation is a non-starter. Demand and champion "glass box" intelligence, where the logic is transparent and the drivers are explainable.
3. Cultivate a culture of strategic inquiry
Don't just train your people on how to use a tool; teach them how to ask better questions with the tool. The most valuable skill in the age of AI is strategic inquiry. Encourage your team to challenge the AI's assumptions, run "what-if" scenarios, and use the insights to build a more robust and resilient plan. This transforms your team from model operators into business strategists who can pressure-test the future.
4. Measure value, not just activity
The true return on investment (ROI) of AI in financial planning isn’t just about reducing cycle times. While efficiency is a benefit, the real value lies in the quality of your decisions. Shift your metrics to track outcomes that matter:
- Forecast accuracy: Are your AI-driven predictions consistently more accurate than previous methods?
- Decision velocity: Is your business able to make critical decisions faster because of more timely insights?
- Resource allocation: Are you reallocating capital and resources more effectively based on smarter demand and supply planning?
By focusing on these strategic KPIs, you connect your AI investment directly to business value.
