Beyond Hiring
How Firms Are Reskilling Around AI — So Talent Evolves, Not Evaporates
AI is no longer a distant disruptor — it’s reshaping how work gets done today. In industries like insurance, finance, and legal, the challenge isn’t whether AI will change jobs, but how firms will adapt their people to work alongside it.
Hiring external “AI experts” isn’t always the answer. The smarter strategy? Reskilling existing employees so their institutional knowledge combines with AI fluency. This protects client trust, reduces turnover, and builds long-term resilience.
Why Reskilling Matters More Than Ever
Vacancies are already expensive, but the shortage of AI-literate professionals compounds the problem. Instead of relying solely on external hires — which are costly and scarce — companies are increasingly turning inward.
Reskilling lets organizations:
- Preserve institutional knowledge that outsiders lack.
- Improve retention by investing in current employees.
- Build future-ready teams without waiting for the perfect hire.
As one McKinsey study noted, companies that actively reskill are 20% more likely to successfully integrate AI than those that don’t.
How Leading Firms Are Doing It
Several major organizations have already made AI reskilling a central part of their workforce strategy:
- Allianz offers a structured AI upskilling program — from foundational AI literacy to advanced prompting — helping employees across their insurance business build fluency in data and AI.
- At BCG, nearly 90% of employees now use AI, and the firm has integrated AI expectations into its performance evaluations.
- IBM is promoting a broader AI upskilling strategy, including its free SkillsBuild platform, to equip employees and learners with AI, data, and technical capabilities.
- In the insurance sector, Accenture observes that roughly 30% of workers will reach retirement age by 2030 — making generative AI upskilling a critical investment.
These examples show reskilling isn’t just theory — it’s a competitive necessity.
What Reskilling for AI Really Means
Reskilling doesn’t mean turning every employee into a data scientist. It’s about equipping professionals with the right mix of AI literacy and judgment skills:
- Prompt engineering basics: How to frame questions to get reliable AI output.
- Critical oversight: How to validate AI recommendations against compliance and professional standards.
- Workflow integration: Embedding AI into everyday tasks (claims review, document drafting, financial modeling) without losing human accountability.
It’s the combination of AI capability and professional expertise that drives value.
Designing a Reskilling Strategy
For firms in regulated industries, a thoughtful approach is key:
- Start with pilots: Train a single department or practice group before rolling out firm-wide.
- Blend learning modes: Micro-courses, peer mentoring, and real-world projects.
- Tie to advancement: Make AI fluency part of career progression, not an optional add-on.
- Measure ROI: Track time saved, error reduction, and client satisfaction improvements.
The Risks of Standing Still
Failing to reskill means:
- Losing competitive edge to firms that adopt faster.
- Frustrated employees who feel ill-equipped for the future.
- Higher turnover as talent leaves for companies investing in growth.
Put simply: ignoring reskilling isn’t neutral — it’s actively risky.
Conclusion
AI is here to stay, but people remain at the core of insurance, finance, and legal industries. The firms that thrive will be those that invest in reskilling their teams, blending human expertise with AI capability.
Talent doesn’t need to evaporate in the face of automation. With the right investment, it can evolve — becoming more valuable than ever.