The adoption of artificial intelligence (AI) and machine learning (ML) tools is transforming back-office performance, introducing novel, sometimes unfamiliar ways of working. For financial leaders (CFO’s, treasurers, comptrollers, senior credit directors) and their teams, embracing these technologies for the purposes of Order-to-Cash operations requires understanding their potential to enhance performance, streamline processes, and achieve strategic goals.
Attaining these optimal results is near-impossible without a clear and well-planned roadmap, one that includes metrics and benchmarking. A company could focus on identifying “quick wins” as an initial strategy. But while there is often low-hanging fruit, such wins can be fleeting, inconsistent, or based too much on narrative and conjecture without a roadmap and metrics tracking. Building a solid roadmap for broader transformation is essential and critical.
The first of two part, this White Paper, authored by Emagia VP Tom Dobis, outlines the current autonomous finance landscape, delves into the importance of results-oriented data tracking, and, finally, set the stage for what existing as well as new metrics need to be part of financial leaders’ evaluation of the implantation and/or use of AI-powered solutions.
Click Here for Part-2 White paper of Measuring For AI Success: Proprietary Metrics to Drive High-Performance Finance in the AI Era