Talent Edge Weekly - Issue #357

Redesigning entry-level and early career roles in light of AI, AI-enabled coaching, internal mobility, talent acquisition and hiring, and reskilling in the context of AI.

Author

Brian Heger
July 19, 2026

PRESENTED BY

Welcome to the new issue of Talent Edge Weekly!

First, a shout-out to Laura Nardi, Sr. Manager Global Talent Management at Delta Airlines, for referring new subscribers to Talent Edge Weekly. Thank you, Laura, for your support of this newsletter!

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My private community for internal HR practitioners

If you’re part of my private community for internal HR practitioners, Talent Edge Circle, we have two upcoming discussions you won’t want to miss.

On Wed, July 22, Dave Ulrich will join us for a 90-min discussion on Actions for HR to Create More Stakeholder Value.

On Thurs, July 30, we have a practitioner discussion on AI’s Impact on Organization Design (and the talent practices that follow).

I’m looking forward to both of these discussions. See you then!

THIS WEEK'S CONTENT

Below are links and descriptions of the topics covered in this issue. If you're interested in my deep dive, you can read the full newsletter.

Also, check out my job cuts tracker & Chief HR Officer move of the week, which is an excerpt from my CHROs on the Go platform.

 â¬‡ď¸Ź Now let’s dive in.

Brian Heger
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THIS WEEK'S EDGE 

AI & EARLY CAREER ROLES

A new article explores how organizations are redesigning entry-level roles for the AI era, including hiring for judgment and using various tactics to develop it faster.

AI's impact on entry-level and early-career roles continues to gain much attention. A few weeks ago, I shared a 42-page World Economic Forum report on redesigning, rather than eliminating, entry-level roles. And last week I shared PwC's 2026 Global AI Jobs Barometer report, which found entry-level roles in highly AI-exposed occupations are being "seniorized" to require judgment and people-management skills once reserved for experienced workers, growing 35% since 2019. This new McKinsey article builds on both, and one tactic worth zooming in on is how organizations are placing greater weight, in hiring and development, on factors such as judgment. Bank of America is one example. The bank held its 2026 intern class steady at nearly 4,000, redesigning roles around AI and using simulation exercises to accelerate the development of skills, such as judgment, for early-career workers. Some organizations are also using the "answer-key model," where employees complete an assignment independently, then compare their reasoning against an AI-generated response with a manager. Tracking whether that gap narrows over time is one indicator of developing judgment. One other point I would add is that if organizations are hiring early-career talent with these prioritized criteria in mind, they will need to reevaluate the tools they use, ensuring that they are valid and reliable. And if managers are going to coach early-career workers on skills such as judgment, organizations need to ensure managers are adequately equipped to do so. Both need to be factored into an organization's broader early-career strategy.

AI-ENABLED COACHING

A new study finds that a single AI chatbot coaching conversation can meaningfully reduce career-related anxiety and boost career optimism.

I recently had the pleasure of having Dr. Anna Tavis, Chair of the Human Capital Management Department at NYU and author of The Digital Coaching Revolution (2024), join my private community, Talent Edge Circle, for a 90-minute discussion on how AI-enabled and digital coaching are reshaping how organizations develop employees at scale. As this topic continues to generate strong interest among Talent Edge Weekly readers, I'm sharing this new research study. Researchers compared employees who used a career-coaching chatbot (just one small example of broader AI-enabled coaching capabilities) with a waitlist group that had not yet used it. The results found that a single conversation with a chatbot significantly reduced participants' negative affect (how anxious or distressed someone felt about their career situation) compared to the control group, and that this emotional relief was linked to greater clarity about their career goals and stronger career optimism. One implication is that a strength of this one capability is that it can help people feel less anxious about their careers, enabling them to think more clearly about their career options. While this is just one study, its randomized design still makes it a useful contribution that can help inform more research-backed evaluations of AI-based coaching technologies. For more on the topic of AI-enabled coaching, check out Tomas Chamorro-Premuzic's article, Does AI Coaching Work? And if you missed it, here is the 2026 Coaching Futures Report by the International Coaching Federation, which also covers AI-enabled coaching.

INTERNAL MOBILITY

My cheat sheet consolidates four of my individual cheat sheets on internal mobility (IM), helping identify opportunities for enabling IM within an organization.

Internal mobility (IM), or the movement of employees across roles and opportunities within the same organization, is a critical component of talent management. As HR practitioners work to strengthen internal mobility in their organizations, here is my one-page cheat sheet that consolidates four individual cheat sheets I previously created on different aspects of IM. Together, they can help identify opportunities for unlocking mobility: 1) manager behaviors that get in the way of talent movement (helps pinpoint where managers may be hoarding talent, intentionally or not), 2) policies that unintentionally minimize talent sharing (helps surface rules or norms quietly discouraging movement), 3) organizational barriers that limit access and visibility to opportunities (helps identify where employees feel they lack access or awareness) and 4) internal mobility metrics that help track progress (helps measure whether mobility efforts are actually working). Regarding internal mobility metrics, one example included is Net Exporter of Talent, defined as the extent to which a leader develops more high-performing employees who move on to roles elsewhere in the organization. This metric is important because it highlights where a philosophy of talent sharing is truly practiced versus where talent hoarding may be occurring, helping organizations better target subsequent actions and strategies.

TALENT ACQUISITION

A new study, published in Management Science and repurposed for HBR, finds that people regularly choose candidates who respond quickly, even when a higher-quality option is available.

A new study, published in Management Science and adapted for a broader audience in this new HBR article, explores how candidate response time, or how quickly someone replies to an employer's message, can influence hiring decisions. Researchers analyzed 11 million-plus Fiverr transactions (a global freelance marketplace) and conducted controlled experiments with over 8,600 participants. Response speed mattered: a one-hour delay made candidates 46% less likely to be hired, while a delay of more than 24 hours reduced the likelihood by 90%. In fact, people regularly chose candidates who replied quickly even when a higher-quality option was available. Faster replies were often interpreted as signs that candidates were competent, easy to work with, and likely to remain responsive. While the study is based on gig-work data, the research offers a useful prompt for examining where bias may quietly influence an organization's hiring decisions. Reflection for Hiring Managers: Think back to a candidate you considered a top hire at the time who ultimately underperformed and/or was not the right fit. What factors created that initial positive impression? Were those factors influenced by what personally impressed you more so than those factors that are more relevant and predictive of job performance? Reviewing these decisions can reveal hidden biases and help teams improve future hiring choices. As a bonus, I'm resharing my post highlighting a guide from the SIOP Foundation and CHRO Association with 13 questions for evaluating AI-based hiring tools, since bias can live in the tools we use to hire, not just in how we personally evaluate candidates.

AI & RESKILLING

A new 26-page report finds that while most organizations have invested in AI pilots and training, few have fundamentally changed how work is organized, and offers suggestions for closing that gap.

A new 26-page report from KPMG and Nasscom finds that while most organizations have invested in AI pilots, tools, and training, few have fundamentally changed how work is organized, decisions are made, or value is created. While there are various suggestions in this report for addressing this challenge, one section I want to highlight: redesign first, reskill second. It points to the issue that organizations often train people on AI tools before redesigning the work itself, when it should be the reverse. Here are a few questions I'd use to pressure-test any reskilling effort underway or in planning: What specific changes to how work is performed are driving this reskilling? What evidence supports these changes (data or speculation)? Are we reskilling people for roles/work as they exist today, or how they will be in the future? To help guide some of these discussions, I've previously shared a few related resources that might help: the World Economic Forum's report on redesigning core workflows around AI, HBS Working Knowledge's interactive tool for checking whether a specific occupation is more likely to be enhanced or eliminated by AI, OpenAI's AI Jobs Transition Framework for classifying how specific jobs are likely to change, and Anthropic's Labor Market Impacts of AI report on where AI usage is and isn't showing up yet. These are just a few of the many resources I have covered on my website at brianheger.com.

MOST POPULAR FROM LAST WEEK

PERFORMANCE MANAGEMENT

A new article explores how traditional performance metrics need to evolve in the context of AI-enabled performance. Proposes a three-layer framework.

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