Agentic AI could lift corporate cash forecasting accuracy to 90%: EY

Treasury teams across Indian corporations currently dedicate up to 70 percent of their working hours to manual tasks, according to an assessment by EY India. This labour-intensive approach creates bottlenecks in financial planning and leaves limited capacity for strategic analysis and decision-making in treasury departments.

Agentic AI—autonomous systems capable of executing complex tasks with minimal human intervention—presents a substantial opportunity to reshape how treasury functions operate. By automating routine forecasting processes, these intelligent systems could elevate cash forecast accuracy to approximately 90 percent, a significant improvement over current benchmarks achieved through traditional methods.

The potential productivity gains extend beyond improved accuracy metrics. By reducing the time treasury professionals spend on data compilation, reconciliation, and routine calculations, organisations could redirect skilled resources toward higher-value activities including cash optimisation, liquidity management, and strategic financial planning.

For Indian companies managing complex multi-entity cash positions across diverse regulatory environments, the adoption of agentic AI could offer competitive advantages in real-time cash visibility and decision-making. As organisations accelerate digital transformation in their finance functions, treasury modernisation through intelligent automation is emerging as a critical priority for enhancing both operational efficiency and financial outcomes.