Talent Edge Weekly - Issue #359

Talent reviews, early-career talent, impacts of AI on experienced workers, building HR for the agentic era, and impact of AI on organization design.

Author

Brian Heger
August 09, 2026

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Welcome to the new issue of Talent Edge Weekly!

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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.

TALENT EDGE CIRCLE - my private community

A special thanks to Dave Ulrich, often called the Father of Modern HR, for recently joining my private community for internal HR practitioners, Talent Edge Circle, as a guest speaker. We spent 90 minutes with Dave in a strategic discussion on the next evolution of creating stakeholder value through HR and human capability.

Dave is also the Co-Founder and Principal at The RBL Group, and I recommend checking out two learning opportunities from Dave and his colleagues at RBL:

HR Learning Partnership (HRLP). This is a 5-day immersive program (with additional virtual modules) where a company sends a team of five to transform their HR department.  

RBL Institute. This is a membership organization for companies wanting to co-create and master the latest HR thinking and action. They offer think tanks, webinars, advisory services, and coaching to member companies.

If you have interest in either of these opportunities, send a message HERE at RBL’s website, or email at [email protected].

And to go deeper with me and other internal HR practitioners on topics tied to your critical talent priorities, apply to my Talent Edge Circle.

Now let’s dive in.

Brian Heger
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THIS WEEK'S EDGE 

TALENT REVIEWS

My cheat sheet on the three interrelated tactics that determine whether a talent review leads to action or just conversation.

Many organizations conduct some version of a talent review. While the specific topics covered will vary by organization, themes range from identifying employees who can advance into larger, more complex roles, to managing unwanted retention risk, to ensuring succession depth for critical roles. One thing I have learned over the years of running many talent reviews across different industries is the real differentiator is strong discipline on what happens after the talent review, not just during it. And that discipline is informed by answering three interrelated questions: 1) Action plan clarity: what specific action are we agreeing to take as a result of this review? 2) Business leader accountability: who outside of HR owns this action? 3) Follow up: What is the timing and expectation for reporting back on the progress and outcomes of the actions identified, and what is the success metric for each action? These three are not independent checkboxes but rather are interconnected. For example, a clear and owned action with no check in date rarely happens on time, and an action with a deadline but no named owner rarely gets prioritized. While these three areas sound easy and fundamental, they are not consistently executed and sometimes are missed completely. To help put this into practice, here is my cheat sheet with a few ideas that can help identify opportunities for enabling more impactful talent reviews.

EARLY-CAREER AND REMOTE WORK

New research published in Administrative Science Quarterly, and repurposed for HBR, suggests remote work, not AI, is the stronger driver behind shrinking early-career opportunity.

Over the last few months, I have shared multiple resources on how AI is reshaping entry-level and early-career roles, from a section of Stanford's AI Index report on employment declines in AI-exposed junior positions to the World Economic Forum's report on safeguarding early-career pathways. New research published in Administrative Science Quarterly, and repurposed for this new Harvard Business Review article, introduces a different factor into this discussion: remote work. Researchers analyzed more than 50 million job postings across 28 European countries and ran a controlled experiment with 1,200 hiring managers, finding that remote roles required roughly 25 percent more skills, experience, and credentials than otherwise identical in-person roles, driven largely by the loss of informal, proximity-based mentoring that once let managers take a chance on potential over experience. When the authors tested AI exposure and remote work against each other directly, the remote work effect held while the AI effect largely disappeared. One implication for early-career strategy is that we should continue to widen the lens beyond AI and look at other factors, like remote work, shaping early-career outcomes.

AI & OLDER WORKERS

A recent analysis finds that workers 55 and older in highly AI-exposed jobs are leaving work earlier than expected, with the increase showing up mostly as unemployment rather than retirement.

Most of the current AI-and-jobs conversation, including my own recent coverage, has centered on entry-level role impact and the risk of failing to develop the next generation of leaders. But there are also impacts at the other end of the career tail: older workers ages 55 and older. A recent analysis from the Center for Retirement Research at Boston College finds that older, highly AI-exposed workers, such as programmers and accountants, are leaving work earlier than expected since ChatGPT's launch, with the increase showing up mostly as unemployment rather than retirement. For programmers, transitions out of work rose by more than 25 percent, compared with just 2 percent for painters, one of the lowest-exposure jobs studied. The author, Geoffrey Sanzenbacher, points to three drivers: automation directly displacing workers, employees choosing to exit rather than adapt, and, less commonly so far, AI-driven productivity gains that extend careers instead. The data so far suggests the first two are outweighing the third. A few practical questions: Do you have visibility into AI-driven exit patterns among workers 55 and older? Do your succession timelines account for earlier, involuntary exits? And are you equipping late-career workers in AI-exposed roles with a path to extend their careers, rather than exit? These and other questions have implications for workforce planning and talent strategy.

AI & HR FUNCTION

A new article on building HR for the agentic era includes a framework mapping the automation potential of specific HR processes into three levels.

As many HR leaders and their teams continue to think through the impacts of AI on HR's work, a new McKinsey article offers a few useful ideas. The one part I want to highlight is Exhibit 1, which maps the automation potential of specific HR processes, from candidate screening to payroll to benefits administration, into three levels: 1) fully automated (an agent completes the work end to end, no human involvement), like generating a verification letter; 2) fully automated in delivery (an agent runs the workflow, but a human owns policy and exceptions), like payroll; and 3) augmented (a human leads, an agent supports), like a business partner using agent-assembled analytics in a succession review while still owning the judgment call. A visual like this can help facilitate conversations within HR teams about where AI may reshape their work, and how new ways of delivering that work will require changes in the HR skill set. As HR work moves toward augmented, more consultative, judgment-based work, HR practitioners will need to continue to build capabilities to match. Against this backdrop, you should check out a four-part series by Deloitte, HR Reimagined 2.0., along with downloadable slides, which helps explain how AI will continue to shape the HR function, unlocking more opportunities for HR to create stakeholder value.

AI & ORGANIZATION DESIGN

Do You Want More Content on the Impact of AI on Organization Design? | Brian Heger

A quick post inviting readers into a recent Talent Edge Circle discussion on how AI is reshaping organization design. Includes a chance to weigh in on whether this topic becomes a recurring topic in the newsletter.

One of the things we do inside Talent Edge Circle, my private community for internal HR practitioners, is host Zoom discussions tied to the group’s current work priorities and initiatives. This past week the group tackled how AI is reshaping org design, with impacts ranging from span of control to decision-making accountability to a notable shift from pyramid to diamond-shaped organizational structures. Regarding span of control, for years most companies leaned on a standard ratio, something like five or more direct reports for senior managers, but the group agreed AI breaks that logic, turning span into a contextual design choice that can be shaped by several factors, including how embedded AI is in the work and absorbing routine coordination. The group began identifying those factors and how they could translate into a few meaningful manager archetypes, each with its own guidelines around how span might shift by archetype. For Talent Edge Circle members, the full recording and discussion notes are already up in the private forum. If you want to see more on AI's impact on organization design covered here in the Talent Edge Weekly newsletter, along with practical cheat sheets and more, please indicate so below so I can gauge interest.

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MOST POPULAR FROM LAST WEEK

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.

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