Talent Edge Weekly - Issue #334

2026 performance management report, unlocking M&A value through operating model design, untapped talent segments, podcast on C-Suite outlook for 2026 and their implications for human capital, and AI in the workplace.

Author

Brian Heger
February 15, 2026

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Welcome to this issue of Talent Edge Weekly!

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Boards are no longer asking if AI matters. They are asking which business units will feel the impact first and what it means for next quarter’s financials. Here is the operating reality:

  • Most enterprises are making billion-dollar AI infrastructure investments with limited insight into the human side of the equation.

  • They can tell you how many GPU clusters they are provisioning, but they cannot tell you which roles are most exposed to disruption or where the biggest productivity gains will come from.

At TechWolf, we believe the AI revolution is a people transformation, not just a technology deployment.

Read our latest Vision Paper to learn about three moves high-performing HR functions are making to lead this revolution.

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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 (subscription-based), where I track hires, promotions, and exits in the Chief HR Officer role.

 âŹ‡ď¸ Now let’s dive in.

Brian Heger
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THIS WEEK'S EDGE 

PERFORMANCE MANAGEMENT

Zac Upchurch shares findings from a new global survey on how companies design, manage, and execute performance management today.

A few weeks ago, Marc Effron, thought leader and President of The Talent Strategy Group (TSG), joined my private community for internal HR practitioners, The Talent Edge Circle, for a 90-minute discussion on enabling business strategy execution through performance management (PM). One point he led with that too many teams miss: clarify the purpose of PM before designing or redesigning it. PM can support multiple outcomes (development, engagement, pay decisions), but it usually does one thing well (and maybe a second “kind of well”). The primary purpose should be increasing performance, which is what CEOs care about. When PM tries to serve too many outcomes, it often fails at all of them. While there are many other insights from that discussion that I can’t do justice to in this short post, I’m glad to point you to TSG’s 2026 Performance Management Report, authored by Zac Upchurch (Partner/COO) and shared on LinkedIn. Based on 250+ organizations, it shows how companies design, manage, and execute PM today, from goals to feedback to evaluation. If PM is on your 2026 agenda, this report is a great reference point, not as a set of best practices, but as a way to spark ideas about potential design choices that support your PM purpose. If you’re an internal HR practitioner and want access to deeper, private discussions that help you advance your talent priorities faster and with more impact, alongside other practitioners and with me in The Talent Edge Circle—apply here.

HR-SUPPORTED M&A

A new article outlines 5 priorities that help avoid the common integration pitfalls, plus a companion 166-page 2026 M&A Trends report with practical tactics.

Many organizations use Mergers and Acquisitions (M&A) as a core lever in their growth strategy and broader business plans. But translating what looks like a strong deal on paper into real value requires thoughtful decisions about how the combined company will actually run—especially the operating model (structure, processes, talent, and behaviors). This McKinsey article argues that integration is a rare window to reset the operating model to match the deal rationale, and it highlights five priorities that separate value capture from value dilution: 1) Quickly define end-state and interim operating models (so planning and continuity stay on track), 2) Use the integration to selectively transform the organization (so the deal rationale becomes operating reality), 3) Announce leaders quickly (to lock accountability and reduce uncertainty), 4) Build an operating model that enables the aspired culture (so decision rights and governance reinforce the culture you want), and 5) Manage change so employees can do their jobs at every stage (so productivity and customer experience don’t suffer during transition). As a deeper-dive supplement, McKinsey’s 166-page 2026 M&A Trends report (which this article draws from) includes additional tactics and practices across the deal cycle, including M&A communications. The image in this post highlights one illustration from the report: a minute-by-minute plan for announcement-day communications.

TALENT ACQUISITION

My cheat sheet includes eight examples of untapped talent segments and the red flags that suggest you may be overlooking them in your hiring practices.

Talent acquisition teams are constantly seeking ways to identify new sources of talent. One underutilized strategy is tapping into ‘hidden workers,’ individuals with valuable skills who are often overlooked due to gaps in hiring practices, policies, or technology. Coined by researchers from Harvard Business School in their report Hidden Workers: Untapped Talent, the term includes talent segments ranging from caregivers to people with disabilities. While many worker segments can be categorized as hidden workers, my infographic highlights eight examples, each with a brief description. In addition to the descriptions, I include a “red flag” for each segment—signs that your hiring process might be excluding these candidates. For instance, the long-term unemployed (individuals out of work for an extended period) may be filtered out by algorithms that screen for employment gaps. Another group is career changers—professionals transitioning between industries or roles, who may be overlooked when hiring processes overemphasize industry-specific experience rather than transferable skills. This infographic can serve as a starting point to help organizations identify and address gaps in their talent acquisition strategies, enabling them to unlock opportunities to tap into overlooked talent pools and gain a talent advantage.

PODCAST: 2026 TALENT OUTLOOK

A 30-minute podcast exploring insights from the C-Suite Outlook survey for 2026 and their implications for human capital, including workforce planning.

In this recent 30-minute C-Suite Perspectives podcast conversation, Steve Odland and Diana Scott unpack The Conference Board’s C-Suite Outlook for 2026 survey and its implications for human capital—labor markets, skills, AI and productivity, and organizational transformation. As I listened to the episode, two points laddered up to the theme of workforce planning. First, regional labor dynamics continue to be a critical planning variable: North America and Europe face aging populations and tighter immigration pipelines; parts of Asia-Pacific are seeing skills gaps as AI and digital adoption accelerates; and in Japan, 36% of CEOs cite the aging population as a major concern. That variation makes it even more critical that workforce plans include location-specific assumptions and scenarios. Second, AI complicates workforce planning because it reshapes workflows and coordination, not just skill requirements. Said differently: it changes who does what, when, and how work moves from one person (or system) to the next. For example, in a contact center, the “before” role is handling routine questions and basic triage; the “after” role shifts reps toward exceptions, de-escalation, and complex problem-solving as AI handles repeatable work. The implication: plans can’t only focus on headcount and broad skill categories; they must anticipate role, task, and handoff changes and the pace of redeployment/upskilling. To help think through aspects of scenario planning in the context of workforce planning, I am resharing my one-page cheat sheet on the topic.

AI IN THE WORKPLACE

Shares study findings on how AI can speed work and expand task scope; authors caution that this benefit can come at a risk, such as burnout.

A new HBR article argues that AI does not reduce work and often intensifies it. The authors share findings from an eight-month study at a U.S.-based tech company with about 200 employees (a small sample, so not broadly generalizable, but still a data point to consider). Over the eight-month study, researchers observed employees in person two days a week, tracked internal work activity channels, and conducted 40+ interviews across engineering, product, design, research, and operations. AI use was not mandated, though the company provided enterprise subscriptions. The result: AI users worked faster, took on a broader range of tasks, and extended work into more hours of the day, often by choice. The upside was that work moved faster and felt easier to push forward. However, workload creep can look like productivity at first, and then gradually become the new baseline for speed and responsiveness. Over time, that intensity can contribute to burnout, cognitive strain, and decision fatigue, which can weaken judgment and decision quality. The authors suggest clear team norms for when to use AI, when to stop, and how to preserve recovery (for example, brief “decision pauses” before high-impact choices). For organizations already building strategies to reduce AI risk, such as privacy, bias, IP exposure, security, and compliance, this article offers a useful prompt to expand those efforts to include the human risks of AI-enabled work, including burnout and decision fatigue.

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