Futureproofing Your Workforce in the Age of AI: What HR Leaders Are Doing Now
At a Davos breakfast with 15 HR and C-Suite leaders, one theme came through clearly: AI is compressing entry-level work and forcing companies to rethink how they build talent pipelines and evaluate candidates.
Leaders from Deloitte, TCW, Indeed, Salesforce, and ManpowerGroup shared how they're adjusting hiring, training, and assessments so they don't lose the next generation of managers while improving quality of hire today.
The entry-level squeeze is real
Elizabeth Faber, Global Chief People & Purpose Officer at Deloitte, said professional services will remain "human-led and technology-powered." The firm expects new AI-enabled businesses to create roles and growth paths, but the shift requires intention.
The takeaway for HR: don't hollow out your bench. Use AI to level up early talent rather than replace it entirely.
Apprenticeship still matters-even if analyst classes shrink
Melissa Stolfi, Chief Operating Officer at TCW, pointed to the long-term value of apprenticeship. Sitting in senior meetings, taking notes, building models-these "mundane" reps compound into leadership skills later.
TCW has reduced its analyst intake as AI handles parts of modeling and research, but it's keeping a pyramid structure to protect the pipeline. Less volume, more intentional development.
Beware the experience trap
Svenja Gudell, Chief Economist at Indeed, noted that in tech specifically, postings asking for 5+ years of experience have increased. Employers want people who can oversee AI agents and complex systems.
That works until the pipeline dries up. If no one invests in entry-level talent, there won't be mid-career candidates later. Meanwhile, other sectors like healthcare are easing experience requirements due to ongoing shortages.
AI-fueled applications are flooding recruiters-so change what you assess
Nathalie Scardino, President and Chief People Officer at Salesforce, shared that the company receives roughly two million applications each year and uses AI to augment recruiter capacity-but not to make hiring decisions.
The bigger change is criteria: less emphasis on tenure, more on learning agility and proof of adaptability. Candidates are asked to show real examples-using tools, managing relationships, and producing outcomes-rather than just list years and titles.
Skills over titles and tenure
Becky Frankiewicz, President and Chief Strategy Officer at ManpowerGroup, highlighted a gap: millions of resumes processed, yet many job seekers still don't land roles. AI can help scale screening and reduce bias if you train and test it well.
Expect a shift from "What was your title?" to "What did you actually deliver?" That mindset opens doors for nontraditional candidates and surfaces people who may not apply unless they meet every requirement.
What HR can do this quarter
- Protect the pipeline: keep internships, analyst programs, and rotations. Pair juniors with AI tools to accelerate learning instead of removing the work entirely.
- Rewrite job descriptions: define outcomes, core skills, and learning agility. Use work samples, job simulations, and structured rubrics to assess.
- Calibrate experience requirements: reserve "5+ years" for roles that truly need it. Offer cohort hiring or apprenticeships to rebuild early-career benches.
- Set AI guardrails in recruiting: let AI boost throughput, but keep humans accountable for decisions. Monitor for adverse impact and document audits. See the EEOC's guidance on AI in employment for baseline practices: EEOC AI Guidance.
- Invest in managers as coaches: train them to run AI-enabled workflows and to teach judgment, communication, and client handling-the skills juniors don't get from a prompt.
- Track the right metrics: time-to-Productivity with AI, internal mobility from early-career roles, diversity across funnel stages, and quality of hire by assessment type.
Practical tooling ideas
- Use AI to auto-summarize meeting notes so juniors can participate more and transcribe less-then review summaries together to teach context and judgment.
- Deploy research or data agents to prep briefs; have juniors validate sources and present insights to build analytical rigor - see Research for methods and best practices.
- Adopt a skills taxonomy and structured interview bank so assessments stay consistent across teams.
Why this matters
AI is shrinking repetitive work. If you over-optimize for short-term efficiency, you risk starving your leadership pipeline. If you shift to outcome-based assessments and prioritize learning ability, you can improve hiring now and still grow future leaders.
Want a fast start on upskilling your team? Explore curated AI courses by role here: Complete AI Training: Courses by Job. For macro context on skills demand, see the Future of Jobs Report.
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