If I were in corp risk at Wells right now—laid off or just waiting for the severance email—I’d be using every slow day to pivot and upskill instead of just riding it out. The bank’s own leadership is openly talking about cutting heads and leaning harder into tech and AI, so the writing’s on the wall.
I don’t say that to minimize how toxic and demoralizing it feels; this setup gives you zero incentive to do more than the bare minimum. But if they’re going to gut layers of risk and middle management anyway, the best move is to treat this as a paid transition period: do what you need to keep your job, and quietly retool for the next one.
If I were in your shoes, I’d be focusing on three buckets:
Data skills: Python and SQL so you can actually pull, manipulate, and analyze risk data yourself instead of just reading decks someone else built.
Analytics/BI: Power BI or Tableau so you can turn that data into something useful for decision makers.
AI/automation: enough to understand how “controls embedded in systems” actually work and where they fail, because that’s where future risk jobs will sit.
On the AI side, I’d definitely learn prompt engineering, especially the newer Socratic style approaches. Risk analysis is already about asking structured questions, exploring edge cases, and not stopping at the first obvious answer—so why not use the computer to generate the full list of “what ifs” and angles you might miss when you’re tired or burned out? You still provide judgment, context, and escalation decisions, but you let the machine help you exhaust the space of questions.
A simple practical way to start:
Take a regulation, policy, or control you already know.
Ask an AI (using Socratic-style prompts) to: “List every failure mode, edge case, incentive problem, and data-quality risk related to X. For each, generate questions a risk manager should ask to detect or prevent it.”
Iterate: keep asking “What else? What assumptions are you making? What would break this?” until the model runs out of steam.
Do that repeatedly and you’re not just “learning AI,” you’re turning your existing risk brain into something that pairs well with AI instead of being replaced by it. If/when severance comes, you walk out not just as “another displaced risk manager,” but as someone who can talk data, automation, and AI-assisted risk in interviews—and that plays a lot better in the current market than “I did policy and oversight until they cut the org.”