Digital Transformation and Generative AI: Moving from Pilots to Execution in 2026
Finance chiefs are facing a year of rapid technological change. A recent survey of 200 North American CFOs showed that half of finance leaders rank digital transformation among their top priorities for 2026, and 87 % predict that artificial intelligence (AI) will be extremely or very important to their finance department’s operations. Nearly half of those surveyed say they plan to automate processes to free employees for higher‑value work, and 54 % cite integrating AI agents into finance workflows as a top transformation priority. For CEOs and CFOs, digital transformation is no longer a buzzword; it’s a strategic imperative.
From pilots to scalable solutions
Adoption remains uneven. A McKinsey survey of 102 CFOs found that 44 % used generative AI across at least five finance use cases in 2025 and 65 % plan to increase their investment, yet most organizations have not scaled beyond isolated pilots. Many pilots break down under real‑world conditions because they are poorly integrated into core processes. In other words, finance teams are experimenting with AI, but only a few have turned pilots into production‑ready systems.
When AI is embedded within finance workflows, the payoff is considerable. McKinsey highlights a global consumer‑goods company that deployed a generative AI assistant to help finance professionals deliver variance analysis and budget insights. The tool saved an estimated 30 % of analysts’ time by automating number crunching and drafting reports. Across multiple industries, finance teams that have scaled AI report spending 20–30 % less time crunching data, allowing them to focus on strategic decisions.
Why 2026 will be different
Experts interviewed by CFO Brew believe 2026 will mark a turning point. Siqi Chen, CEO & CFO of Runway, predicts that software will finally catch up to the capabilities of large language models, enabling tasks like forecasting and variance analysis to shift from human‑led processes to AI‑powered workflows. As the effort required to reach “good enough” drops dramatically, finance teams gain economic leverage because the cost of high‑quality analysis declines.
Expert insights highlight a common theme: digital transformation succeeds when it focuses on data governance, integration and outcomes—not isolated experiments. AI and automation are enablers, but transformation requires people, processes and controls to evolve in tandem.
Recommendations for finance leaders
Identify high‑impact use cases. Start with workflows that consume the most time or constrain decision‑making—closing the books, forecasting and scenario analysis, working‑capital management, and report generation. AI excels at synthesizing large data sets and generating draft analyses.
Build a single source of truth and robust governance. Fragmented systems undermine AI initiatives. Consolidate financial and non‑financial data into a unified platform, enforce data quality standards, and establish controls for security and privacy. Without this foundation, AI will merely automate erroneous processes.
Integrate AI into core processes. Move beyond pilots by embedding AI agents directly into finance workflows—for example, by using AI assistants during planning sessions or automating variance analysis. Measure productivity gains and decision quality to demonstrate value.
Develop talent and change management. Reskilling finance teams to work alongside AI is critical. CFOs should invest in training, recruit digitally savvy talent and encourage cross‑functional collaboration.
Prioritize ethics and controls. Effective transformation requires strong governance. Establish frameworks for AI ethics, data security, auditability and regulatory compliance.
Digital transformation is the top finance priority for 2026. Survey data show that CFOs plan to integrate AI agents, automate processes and invest heavily in generative AI. Yet McKinsey’s research warns that most pilots fail because they are not integrated into core processes. By focusing on data governance, targeted use cases, integrated workflows and robust change management, finance leaders can move from experimentation to execution. Generative AI is no longer a futuristic concept—it is a practical tool that, when deployed thoughtfully, can unlock efficiency, insight and competitive advantage.