SPONSORED BY

Welcome to this new issue of Talent Edge Weekly!

First, a shout out to Liz Dente, Chief People Officer at Priceline, for referring new subscribers to Talent Edge Weekly. Thank you, Liz, for your support of this newsletter!

 Not subscribed to Talent Edge Weekly? Sign up now and get 5 of my PDFs.

PRESENTED BY TechWolf

Does your AI actually understand work, or just sound like it does?

Most tools point a general-purpose model at HR data and call it intelligence. TechWolf made the opposite bet: work is its own domain, worth dedicated AI research. Co-Founder Mikaël Wornoo (Mik) writes it all up in his series, Computing the Labor Market:

• WorkRB: the first open-source benchmark for work: 14 tasks, 28 languages, built with six universities and public employment services across 74 countries.

• "Work IQ": a way to measure whether a model genuinely understands work, instead of trusting a slick result on one narrow task.

Mik and the team are on the road this conference season, and would love to meet Talent Edge Weekly readers in person. Come find TechWolf at:

• SAP SuccessConnect Happy Hour | Details 

• Workday Rising NAMER Happy Hour | Details 

• Workday Rising Pharma & Life Sciences Dinner | Details 

• Gartner HR Executive Dinner | Details 

P.S. Want the research first? Read the series: Computing the Labor Market.

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.

• The State of AI in 2026: On The Road to ROI | QuantumBlack AI by McKinsey | A new report examines several aspects of AI, from ROI on investments to the economics of scaling AI. I expand on the latter and why workforce plans need to account for the actual economics of AI capacity.

• Why C-Suite Leaders Need to Rethink Organization Design for The Agentic Era | Deloitte | A new article explores how AI is reshaping organization design, from spans of control and layers to decision rights. I tie in insights from a recent Talent Edge Circle discussion we had on the topic.

• The AI Literacy Development Canvas: Assessing and Building AI Literacy in Organizations | Business Horizons | A research paper introduces practical frameworks for assessing and building AI fluency and includes a real case study. I also share my bonus slides for connecting talent initiatives to business priorities.

• Succession Planning: 8 Scenarios to Help Inform Successor Readiness | Brian Heger | My one-pager outlines eight scenarios that successors could be moving into when taking on a new role, which should be factored into determining their readiness.

• Most Careers Stall at Mid-Level, No Matter How Long People Work | Harvard Business School Working Knowledge | A new analysis of 150 million resumes finds that most careers plateau well below senior leadership, with only 19% reaching top seniority after 20 years. I share why career growth needs to extend beyond promotion.

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.

THIS WEEK'S EDGE 

AI AND WORKFORCE PLANNING

The State of AI in 2026: On The Road to ROI | QuantumBlack AI by McKinsey

A new report examines several aspects of AI, from ROI on investments to the economics of scaling AI. I expand on the latter and why workforce plans need to account for the actual economics of AI capacity.

McKinsey’s new 31-page State of AI in 2026 report includes several useful findings from its global survey of 1,719 participants across 97 countries. One data point that caught my attention is the economics of scaling AI. About 20% of respondents say AI-related operating costs, including token costs (the units of data processed when using an AI model), have caused some organizations to limit how much they use AI. The issue becomes even more pronounced among AI high performers, which McKinsey defines as organizations that attribute at least 5% of EBIT to AI use and describe its impact as significant. This reinforces an important point: running AI at scale is not free or unlimited, and workforce plans need to account for the actual economics of scaling it. Another related data point: 39% of respondents expect AI to decrease their organization’s overall head count over the next year. From my standpoint, layering in the token and operating cost constraints noted above, the 39% headcount expectation raises an important second-order consideration: if headcount is reduced based partly on the assumption that AI will take on more of the workload, but AI use later becomes limited by cost or other constraints, workload demand could outpace the organization's capacity to deliver. AI’s capabilities are tremendous and will increasingly need to be part of workforce models. At the same time, we need to be intentional about these decisions so we can create ROI from AI’s benefits while reducing unintended consequences.

Access report

AI & ORGANIZATION DESIGN

Why C-Suite Leaders Need to Rethink Organization Design for The Agentic Era | Deloitte

A new article explores how AI is reshaping organization design, from spans of control and layers to decision rights. I tie in insights from a recent Talent Edge Circle discussion we had on the topic.

A few weeks ago, members of my private community for internal HR practitioners, Talent Edge Circle, came together to discuss AI’s impact on organization design. The discussion ranged from spans of control, organizational layers, and decision rights to reimagining early-career roles and how work may flow differently with AI. For example, one part of the discussion focused on span of control and led us to question whether it should shift from a standard benchmark to a more contextual design choice. That could mean considering factors such as work complexity, process standardization, team maturity, and how much routine coordination AI is absorbing. The result may be wider spans in some areas and tighter spans in others. Within the one-hour discussion, we not only highlighted key issues across these topics but also came away with frameworks and working principles that can help inform these decisions. That is one reason this new Deloitte article caught my attention. It expands on many of these organization design topics. For example, on decision rights, the article extends the traditional RACI framework by adding an “O” for override authority, clarifying who can challenge, modify, or stop an AI agent’s output. As AI takes on more tasks and decisions, organizations need to be clear about who remains accountable for the outcome and who can intervene when needed. If you are a Talent Edge Circle member, you can catch the full replay of our discussion, along with some of the resources we developed following it, in the resource library on our private platform.

Access article

AI FLUENCY

The AI Literacy Development Canvas: Assessing and Building AI Literacy in Organizations | Business Horizons

A research paper introduces practical frameworks for assessing and building AI fluency and includes a real case study. I also share my bonus slides for connecting talent initiatives to business priorities.

Many organizations are focusing on building AI fluency to tap the potential of AI investments in their workforce. To support this effort, I recently made a post about a report by the International Labour Organization that expanded on the topic, including framing AI fluency into three categories. To build on that resource, I wanted to share a paper offering two practical frameworks: the AI Literacy Assessment Matrix, which evaluates AI skills across job levels, and the AI Literacy Development Canvas, a strategic planning tool for investing in AI training. The paper's appendix also includes prompting questions to help walk through the Canvas. What I find particularly useful is that the paper also grounds these frameworks in a real case study. PharmaCo, a global pharmaceutical company, used both tools to identify literacy gaps across executives, middle managers, and frontline staff, then built a phased rollout from pilot to company-wide adoption, including clear metrics of success tied to business priorities. This reinforces something I often emphasize: talent initiatives resonate most when anchored in the real business problem being solved, with a clear and "good enough" plan to start and build momentum. With this as the backdrop, I am resharing my two-slide resource on framing a talent initiative around business needs while jumpstarting ideas for phased execution. As it relates to AI fluency, I am looking forward to having Tracy St. Dic, VP of Global Talent at Zapier, join Talent Edge Circle for an upcoming discussion on how Zapier is building AI fluency in its organization.

Access paper

SUCCESSION PLANNING

Succession Planning: 8 Scenarios to Help Inform Successor Readiness | Brian Heger

My one-pager outlines eight scenarios that successors could be moving into when taking on a new role, which should be factored into determining their readiness.

Last week, I made a post about a recent study published in the Journal of Applied Psychology that followed leadership transitions across 113 U.S. elementary schools. One finding caught my attention: hands-on coaching improved employee engagement and performance when employees believed change was needed, but produced declines when they did not. While the setting was education, I believe the broader implication extends well beyond it: certain leadership skills and behaviors can disproportionately influence success depending on the situation a leader is stepping into. This is especially relevant to succession planning. Successor assessment typically starts with a success profile, the skills and experiences required to perform a given role, and that remains important. But the scenario a successor is likely to step into can significantly influence who is best suited for the role, and that scenario can shift over time. This is why it helps to factor in the scenario as an additional layer in selection and development discussions, not just the general success profile. Building on that idea, I created a one-page resource covering 8 scenarios, such as turnaround, rapid growth, culture change, and major transformation. Some scenarios can look similar on the surface, but the distinctions can matter for how a successor is prepared. The scenarios are also not mutually exclusive, meaning a successor could be stepping into a situation that reflects more than one scenario at the same time, so use judgment to determine which scenario, or combination, is most relevant.

Access my one-pager

CAREER DEVELOPMENT

Most Careers Stall at Mid-Level, No Matter How Long People Work | Harvard Business School Working Knowledge

A new analysis of 150 million resumes finds that most careers plateau well below senior leadership, with only 19% reaching top seniority after 20 years. I share why career growth needs to extend beyond promotion.

As internal mobility and career development remain top priorities, I am always interested in data on how careers progress. A new Harvard Business School analysis looks at one dimension: upward advancement. Based on this working paper, Professor Paul Gompers and coauthors analyzed 150 million resumes to build a seniority measure, defined as the typical number of years it takes someone to reach a given job title within their industry and firm size. Using this measure, more than half of those with 10 years of experience had kept pace, reaching seniority level 10 or higher, but only 19% of those with 20 years had kept pace to reach level 20. What this reinforces for me is that career growth cannot be defined only by upward advancement. Deepening expertise, expanding scope, lateral moves into higher-value work, and broader business exposure can all be meaningful forms of progression. The challenge is making sure employees see them that way, a matter of positioning and communication. One tactic I like for creating these opportunities is project-based work, or short-term work tied to a real business need outside someone's regular responsibilities. It can give employees new skills, experiences, and connections while helping the organization move talent to priority work. Internal talent marketplaces, often enabled by technology, can make these opportunities more visible and accessible. With this in mind, I'm resharing my one-pager with eight questions to help identify potential projects for an organization's internal talent marketplace.

Access article

MOST POPULAR FROM LAST WEEK

AI & REDESIGNING WORK

AI Transformation Requires Redesigning Work, Not Cutting Roles | Harvard Business Review

A new article shares evidence that AI-driven layoffs are often falling short of expected results and offers tactics for making better workforce decisions. I also share one of my bonus cheat sheets related to the topic.

Access article

🔓️ There is more content in this issue, but you must be subscribed to view it. Subscribe Now (it’s free) or sign in if you are already a subscriber!