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Human Resources

Talent, pay, policy and culture, chosen for the HR leader who has to answer for them on Monday.

Human Resources at The First Click is written for the people who own the workforce question: talent and hiring, compensation and benefits, workplace policy, and culture and engagement. Three stories a weekday at 11, each summarised in our own words and linked to the publisher. We favour the story that changes a decision over the story that confirms one: a survey with a number a compensation head will be asked about, a policy experiment that will be copied badly, a departure that says something about retention at the top. Artificial intelligence runs through most of them now, as a tool the workforce already uses whether or not the policy has caught up. The editor’s note under the day’s lead says why we chose it, and the Friday Funny lane keeps the stories that prove the point by making you laugh.

A pile of money on floor being sucked into a vacuum cleanr

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Every story we have kept in Human Resources, newest first. Headlines link to the publisher; the tags below narrow the list.

7 stories in Learning & Development
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2026-09-30
Learning isn’t the constraint—capacity is

Writing for Chief Learning Officer, Sandra Mohr argues organizations face a capacity crisis rather than a learning-content shortage, citing Deloitte data showing workers now manage ten major enterprise changes yearly, up from two in 2016. She proposes a "Workforce Capacity Loop" prioritizing coaching and workflow conditions over course completion.

Editor's noteOrganizations' capacity to absorb change is the real constraint, not learning content. Watch the proportion of employees who report being overwhelmed by work changes, as that's the metric that will reveal whether the Workforce Capacity Loop can deliver sustained performance.

2026-09-15
The hidden cost of hybrid work: Rebuilding informal learning for early-career employees

Citing PwC's 2026 AI Jobs Barometer, OpenSesame chief executive Don Spear argues hybrid work has eroded informal learning for early-career staff as AI-exposed entry roles demand senior-level judgment.

2026-09-14
The Philippines to reskill 1.3 million IT-BPM employees under US$34.4 billion AI infrastructure plan

The Philippines launched a 34.4 billion dollar AI infrastructure masterplan through 2033, aiming to reskill 1.3 million IT-BPM workers and create over 500,000 AI-related jobs.

Editor's noteOne point three million workers is not a pilot. The Philippines is reskilling the workforce whose jobs automation threatens first, and doing it as national infrastructure policy rather than employer training, which makes this the clearest test yet of whether that approach can outrun displacement.

2026-09-09
AI is changing work. Is L&D changing fast enough?

L&D teams must move beyond basic AI training and redesign workforce capabilities around human judgment, validation, oversight, and real-world task augmentation as generative AI reshapes knowledge work.

2026-09-06
How To Design Better Branching Scenarios: Start With The Decision

Guidance on building branching scenarios that actually teach: start from a real decision, offer choices a learner might plausibly make, let consequences follow, and add no complexity the lesson does not need.

Editor's noteThe framework here shifts branching-scenario budgets away from narrative production toward locating genuine judgment calls first. For L&D teams burned by expensive multi-path builds that taught nothing new, the practical test becomes whether a decision point could genuinely divide competent staff, not whether it makes a better story.

2026-09-06
5 myths about being a genius

A neurologist argues that genius is trained rather than issued at birth, and picks apart five assumptions about talent that keep capable people from attempting difficult work.

2026-08-27
Abstinence is not an AI strategy

Banning or avoiding AI in the workplace is not a viable strategy. Learning leaders should focus on responsible experimentation, AI literacy, governance, and workforce adaptation rather than attempting to prevent employees from using AI.

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