Talent Edge Weekly - Issue #356

AI's impact on early-career roles, 7 AI-based value levers, high-impact development roles, the impact of AI on performance evaluation, and the cognitive cost of change.

Author

Brian Heger
July 12, 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.

 ⬇️ Now let’s dive in.

Brian Heger
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👉️ P.S. Go deeper with me and other internal HR practitioners to accelerate your critical priorities. Learn about my private community, Talent Edge Circle.

THIS WEEK'S EDGE 

EARLY-CAREER TALENT STRATEGY & AI

A new report with a section on how AI is reshaping certain entry-level roles to require more senior-level skills, with implications for early-career strategy.

A few weeks ago, I shared a 42-page report from the World Economic Forum that included a framework to help leaders understand the impact of AI on entry-level roles and potential responses. One component was redesigning entry-level roles to fit an AI-enabled world. I am now sharing a recently released 30-page PwC paper with a section specifically on entry-level roles and AI, that can help inform where job redesign in entry-level roles could have the greatest ROI. Analyzing over 1 billion job postings globally, the analysis identifies a phenomenon it calls "seniorization," where entry-level roles in highly AI-exposed occupations are rewritten to require skills typically reserved for experienced workers, such as judgment and people management. Entry-level roles that had been "seniorized," meaning they had added 10 or more of these traditionally senior skills, grew 35% between 2019 and 2025, while non-seniorized roles in the same category fell 10%. This is an opportunity for organizations to be intentional about early-career reinvention, so they can build the talent pipeline for the future rather then simply eliminate or reduce early-career roles. Which early-career roles and paths need to be reinvented for an AI-enabled world in your organization, and how will that change how you recruit, hire, and develop early-career talent? This is a topic we will discuss in my private community for internal HR practitioners, Talent Edge Circle.

AI & RETURN-ON-INVESTMENT

A new report identifies seven levers companies use to create value with AI. I share a one-pager to map your own AI use cases against the framework.

As HR practitioners help their organizations implement AI across a growing number of use cases, clarity about the value each one is expected to create makes it easier to measure whether it delivered. This new report, based on interviews with 30 executives, speaks directly to this. While the report covers various aspects of AI, from the true pace of enterprise AI adoption to why survey-based ROI studies often contradict each other, one part to highlight is the section on the seven levers of how AI creates value, from reducing labor intensity to improving decision making. Interestingly, 91% of the AI use cases discussed centered on reducing labor intensity, suggesting opportunities to use AI to create value beyond any one lever. Also, although each of these seven levers is listed separately, they are not mutually exclusive (e.g., an application that reduces labor intensity may also reduce cycle time). To help put the framework into practice, I created a modified version, adding practical examples and space to list your own AI use cases and evaluate them against each lever. The resulting visual can help you spot whether your AI portfolio is spread broadly across the seven levers or leaning on just one, providing insight to evaluate and evolve your strategy. As a bonus, I’m resharing my slide, Framing Talent Initiatives Within the Business Context, which can be paired with the AI framework to articulate AI-based talent initiatives that can create stakeholder value.

TALENT MANAGEMENT & DEVELOPMENT

My slides to help evaluate if key development roles are used effectively to support talent growth and leadership pipeline flow.

In every organization, certain roles are accelerators of development, where the nature of the role and its challenges enable individuals to build critical skills and gain key experiences faster than in other roles. However, when an incumbent remains in one of these high-impact roles for too long, without the interest or potential to transition into larger, more complex roles, it can hinder both individual growth and organizational performance. To keep development and leadership pipelines flowing, it’s helpful to periodically assess whether these roles (often limited in supply) are being used to accelerate the development of others, including those on succession plans. To jumpstart your thinking, my attached slides provide some guiding questions for managers: Has the person been in the same development role for an extended period without progression? Are they open to new responsibilities or stretch opportunities? Is their continued presence in the role limiting access to valuable experiences for successors? While there are other ways to accelerate development, such as short-term assignments, roles remain a meaningful and powerful source of growth. This topic can also be integrated into talent review discussions to support more informed and deliberate talent planning and decisions. The slides are from a larger deck available in my private community, Talent Edge Circle.  

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.

As AI reshapes how organizations execute work, many HR practitioners are rethinking how performance management may need to evolve, including how performance is evaluated. This new HBR article notes that many organizations still evaluate employees with pre-AI metrics like productivity and goal completion, creating a performance paradox: employees who rely heavily on AI look highly productive, while those who slow down to verify or correct outputs can look less efficient, when they are adding the most value. For example, one field experiment (published in Organization Science) on 750 knowledge workers using GPT-4 found workers were 25% faster and 12% more likely to succeed on tasks within the AI's capability, with higher-quality output. But on a task just outside that capability, workers using AI were 19% less likely to produce a correct solution than those without it. The authors of the HBR article propose a three-layer measurement framework: 1) metrics for human contribution, 2) metrics for the AI system or AI agent, and 3) metrics for how well the two perform together, including a complementarity index measuring whether a person genuinely added value (e.g., catching an error or reframing a problem) beyond what AI produced. From my standpoint, the complementarity index is conceptually clear but would need to be operationalized, including how incremental value gets determined and defined, by whom, and at what standard. Is there a simplified version of this your organization could pilot? Regardless, the article offers various considerations for evolving performance management as AI itself continues to evolve.

ORGANIZATIONAL CAPACITY & CHANGE

A new article that views cognitive capacity as an organizational resource to manage strategically, outlining three research-backed practices to support it.

Organizations invest significant time and resources in attracting, hiring, and retaining top talent to enable business strategy execution. But two things can quietly work against that investment: 1) the sheer volume of change moving through the organization, which outstrips employees' capacity, and 2) additional work added throughout the year without considering capacity to deliver on it. Last year I shared my one-pager to help leaders better understand the full scope of changes happening simultaneously in their organizations, and more recently, my mid-year one-pager to address goal creep, where new goals get added without deciding what makes room for them. Both are meant to help leaders manage workforce capacity more deliberately. A new McKinsey article picks up where both leave off, treating cognitive capacity, the mental bandwidth people need for deep thinking and learning, as an organizational resource to manage strategically. Drawing on nine sources of research from publications such as Organization Science and Journal of Management Studies, the authors outline three practices for safeguarding cognitive capacity, including agreeing on what work stops before something new starts, a practice also shared in my mid-year one-pager. This article is an example of how HR practitioners can use scientific research to inform and strengthen their own recommendations.

MOST POPULAR FROM LAST WEEK

TALENT MANAGEMENT

A chapter from the eBook (The Age of HR) explores how organizations can apply the same ROI discipline to human capital that they apply to financial capital by mapping role criticality against talent caliber.

With many organizations getting ready to conduct talent reviews, of which critical roles and succession planning are part, I want to highlight chapter 25, beginning on page 120, by Chief People Officer, Holly Tyson, in the excellent, open access eBook, The Age of HR. Holly reinforces how organizations should manage human capital like financial capital, with targeted development, deployment, and measurement of ROI. Her 5i Model maps Role Criticality (core, critical, and differentiating) against Talent Caliber (core, key, and top talent), prescribing one of five actions (invest, improve, inspect, increase impact, or inject), based on where a role and its incumbent land on this matrix. For those in my private community for internal HR practitioners, Talent Edge Circle, I’m looking forward to our upcoming discussion on the strategic talent management of critical roles. And as a bonus, here is one of my cheat sheets on managing talent risks in critical roles.

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