An AI adoption strategy is the structured plan an organisation uses to introduce artificial intelligence into its operations in a way that is controlled, scalable and aligned with business priorities. In finance, it defines how teams transition from manual execution to autonomous, AI-driven workflows, while maintaining compliance, operational resilience and data integrity. A strong strategy does not start with technology; it starts with identifying the high-volume, error-prone processes where AI can deliver measurable impact.
The first pillar is process selection: understanding which financial workflows generate the highest operational burden, reconciliations, supplier checks, document processing, exception handling, and prioritising use cases that combine feasibility with immediate value. The second pillar is governance: ensuring that any AI system introduced into finance includes proper supervision, auditability and alignment with internal controls. The third is change management: preparing teams to move from “doing the work” to supervising a digital workforce.
Phacet accelerates AI adoption by providing autonomous agents that integrate directly into existing systems and operate within the organisation’s governance framework. Instead of long transformation programmes or heavy reengineering, finance teams deploy agents incrementally, starting with targeted workflows and expanding progressively across entities. This reduces risk, shortens time-to-value and allows teams to build confidence through measurable improvements in accuracy, cycle times and workload reduction.
A successful AI adoption strategy ultimately reshapes the operating model: humans focus on judgment, oversight and strategy, while agents execute repetitive tasks end to end. The shift becomes especially clear when organisations implement autonomous AI agents across financial workflows, turning AI from a technological experiment into a core driver of operational performance.
