Five Surprising Takeaways on Adopting AI in FP&A
Recent analysis reveals five takeaways that explain both the slow adoption rate and a realistic path forward.
Takeaway 1: The Adoption Gap Is Not Apathy, It Is Paralysis
FP&A teams are not ignoring AI. Many are stuck waiting for a perfect, enterprise-wide solution. Large transformation programs feel risky, slow, and difficult to justify, which leads teams to delay action altogether. The result is paralysis, not resistance.
Takeaway 2: The Real Barriers Go Beyond Budget
Cost matters, but it is only one part of the challenge. Several structural barriers make large-scale AI adoption difficult.
Volatile business environment. Global uncertainty, including changes in 2025 U.S. tariffs, pushes companies to prioritize agility and cash preservation over long-term transformation programs.
High costs and long time horizons. SMEs typically spend 50k to 250k on pilots and 250k to 1.5 million on full rollouts, with timelines of 9 to 36 months. Multinationals may invest 3 million to 15 million or more over three years.
Skills gaps and workforce readiness. Many FP&A professionals still rely heavily on Excel and lack experience running or validating AI outputs.
Rapid AI evolution and obsolescence risk. Tools evolve quickly, raising concerns that today’s investment could be outdated within months.
Global and regulatory complexity. Data privacy rules, language requirements, and regional work habits complicate deployment across borders.
Integration challenges. Poorly integrated tools can increase manual work instead of reducing it.
Together, these factors make a big-bang approach impractical for most FP&A teams.
Takeaway 3: The Smart Path Forward Is a Bridge Strategy
Instead of waiting for a large transformation, FP&A teams can adopt a bridge strategy. This approach focuses on small, flexible, low-cost, and user-friendly AI tools that solve specific problems today.
As Freddy Li notes:
“Such a short-term approach balances immediate productivity demands with careful investment and prepares the ground for further, deeper use.”
This strategy allows teams to gain value now while reducing risk and preserving optionality for future enterprise solutions.
Takeaway 4: Start With Low-Risk, High-Annoyance Tasks
The bridge strategy works best when applied to tasks that consume time but carry limited risk. Automating these activities delivers fast wins and builds confidence.
Examples include:
Slide preparation
Report sending automation
Model formula or coding recommendations
Memo structure drafting
These tasks are common pain points in month-end, reporting, and planning workflows, yet they do not require complex judgment or system integration.
Takeaway 5: Give the Team a Toolbox, Not a Monolith
Successful adoption depends on how tools are selected and governed.
Effective principles include:
Favor extensions of existing software, such as Excel add-ins or Copilot-style tools.
Keep costs and training requirements low so professionals with minimal AI knowledge can use them.
Maintain flexibility by testing different tools across functions or regions.
Let professionals choose which tools add the most value to their own workflows and provide feedback.
Assign clear ownership to monitor tools, update guidance, and maintain a simple approved list.
This approach embeds AI into daily work instead of forcing teams to adapt to a single, rigid platform.
Conclusion: Build the Bridge Before You Need the Highway
Large-scale AI platforms will eventually reshape FP&A, but waiting for the perfect solution carries its own cost. A bridge strategy allows teams to capture immediate productivity gains, build practical AI knowledge, and experiment in a controlled environment.
By starting small, FP&A teams can move past AI paralysis and begin building toward a more capable, AI-enabled finance function.
Question for finance leaders: What is one repetitive, low-risk task your team could address with a simple AI tool this quarter?
Source: Li, Freddy. A Bridge Strategy: How FP&A Teams Can Adopt AI Step-by-Step. FP&A Trends, December 11, 2025.