AI in planning: benefits, barriers, and best practices

Generative AI offerings have flooded the Corporate Performance Management (CPM) market, but measurable returns depend on adoption, not novelty. Nucleus research found that early adopters benefit most prominently from generative AI copilots and first-draft automation by deflecting most routine financial inquiries, reducing reporting errors and rework by 20 to 30 percent during review and close cycles, and easing onboarding and cross-functional access to financial data. These gains translate into reclaimed analyst time, faster close cycles, and broader adoption of planning tools beyond finance. However, benefits are not automatic. Data quality, governance, and explainability determine success far more than model sophistication. Organizations that deploy AI on fragmented or poorly governed data see trust erode and value stall, while those that invest first in clean, integrated data and finance-led configuration realize faster time to value and higher ROI. For finance teams, generative AI does not replace judgment. Instead, it removes repetitive work and raises the ceiling on analysis, but only when paired with deliberate change management and disciplined execution.