EY’s leadership recently addressed how AI is reshaping what junior accountants need to learn and how they need to learn it. The core message: as automation handles routine reconciliation and data entry, the mentorship model has to change. New finance professionals will spend less time on repetitive tasks and more time learning judgement, interpretation, and client communication from senior colleagues.
We hear versions of this from advisory and accounting companies across the DACH region. A finance director in Munich told us last month that their graduate intake now spends the first six weeks on soft skills and systems navigation rather than manual processing. The reason was simple: the manual work was already being handled by automation, so there was nothing for trainees to cut their teeth on in the old way.
For experienced finance professionals, this creates a quieter shift in how their own value is perceived. The premium is moving toward people who can explain the output of automated systems, spot where the model has made an assumption, and translate that for non-finance stakeholders. We placed a senior advisory manager in Zurich earlier this year after a process that focused heavily on stakeholder communication. The hiring panel spent most of their time on a scenario about explaining audit risk to a board unfamiliar with AI-assisted reporting. His technical credentials came up only briefly.
Hiring managers who want to test for this should consider how they structure interviews. Asking candidates to walk through a technical reconciliation tells you less than asking them how they would explain a flagged anomaly to a sceptical CFO. Companies across advisory, audit, and FP&A are building interview processes around exactly this kind of scenario question.
Prompted by reporting from CFO Dive. Read the original article.