The tectonic shift under our feet

We are living through a moment that will be recorded less for a single product or platform and more for a wholesale rearrangement of how work gets done. Artificial intelligence is no longer a specialist tool confined to research labs and Big Tech. It is being embedded into operations, customer interactions, design processes, supply chains, and hiring decisions. With that embedding comes new tasks, new hybrid roles, and new combinations of technical and human skills that do not map neatly to traditional degree lines.

LinkedIn’s Sue Duke has been clear: the AI‑driven economy is producing entirely new roles and skill sets. These are not simply upgraded versions of old jobs; they are new collared roles that sit between the conventional categories of blue collar and white collar. For workers and organizations that want to stay relevant, the imperative is to surface and celebrate this talent.

What ‘new‑collar’ really means

The term ‘new‑collar’ describes people who bring practical, job‑ready skills that may be acquired through nontraditional pathways: bootcamps, employer training, microcredentials, on‑the‑job development, or focused apprenticeships. Crucially, these workers are comfortable operating alongside AI systems. They know how to adapt model outputs, validate results, tune prompts, and integrate automated insights with human judgement.

New‑collar roles are hybrid by design. They blend domain knowledge, digital fluency, and an ability to communicate across teams. They are often defined by capability rather than credential. And as AI reshapes tasks, many legacy roles will be reconstituted around these new capabilities.

Why employers should lead the narrative

When employers spotlight new‑collar hires, they do more than fill positions: they send a signal to markets, investors, and talent pipelines. Highlighting these hires helps companies:

• Attract practical talent who can hit the ground running with AI‑augmented tools.
• Democratize access to career ladders by decoupling hiring from narrow credential gates.
• Reduce skill gaps by valuing demonstrable capability and continuous learning.
• Create internal visibility for hybrid pathways that can scale through apprenticeships and internal rotations.

Firms that continue to prioritize resumes over real capabilities risk losing agility. In a fast‑moving field, the person who can apply an LLM to real business problems or who can orchestrate human plus machine processes will be exponentially more valuable than a paper credential alone.

Practical moves for organizations

Shifting an organization toward a new‑collar mindset is not an ideological choice so much as an operational one. Here are concrete steps companies can take:

1. Audit roles and tasks.

   Map the work being done across teams and identify where AI changes the task mix. Ask which parts of a job require human empathy, complex judgment, or cross‑functional coordination, and which parts can be automated or supported by models.

2. Redefine hiring signals.

   Create job descriptions that emphasize demonstrated skills, project portfolios, and problem‑solving probes. Consider take‑home assignments, short work trials, and credential stacks that reflect the tools and workflows you use.

3. Invest in internal training and ladders.

   Rather than expecting all talent to arrive fully formed, build learning pathways that convert adjacent skills into role readiness. Sponsor bootcamps, micro‑credentials, and rotation programs that surface high‑potential workers from within.

4. Showcase new‑collar success stories.

   Publicize internal promotions, lateral moves, and project wins from new‑collar hires. Celebrate the mix of technical and social skills that produced impact, and use those stories to refine hiring pipelines.

5. Measure impact, not activity.

   Shift metrics toward outcomes that capture speed, quality, and learning velocity. Reward people who make teams more productive by pairing AI systems with human insight.

What workers should amplify

For professionals, the road ahead is not a choice between retrenchment and replacement; it is a path of continual reinvention. Workers can take strategic actions to become visible new‑collar candidates:

• Build a portfolio of AI‑augmented projects: show how you used models to generate insights, saved time, or improved outcomes.
• Learn complementary skills: combine domain knowledge with prompt design, data literacy, and systems thinking.
• Seek roles that offer learning velocity and exposure to cross‑functional problems rather than static job descriptions.
• Document learning pathways and microcredentials so employers understand the rigor behind nontraditional training.

Visibility matters. When you make the arc of your learning and impact clear, you create leverage for better roles and faster advancement.

Broader implications for equity and mobility

One of the most promising aspects of the new‑collar approach is its potential to broaden access. Traditional credential filters have long been gatekeepers that reinforced inequality. By centering demonstrable capability, organizations can open ladders to people who historically lacked access to formal degrees but who possess the practical skills to succeed in modern workplaces.

This is not automatic. Without intentional design, AI could amplify existing disparity by privileging those with resources to learn new tools. That is why employer commitment matters: hiring practices, training investments, and public recognition of nontraditional pathways can create durable mobility.

What success looks like

Companies that truly embrace new‑collar talent will look different in observable ways. They will have shorter onboarding cycles for AI‑augmented roles, more internal promotions from lateral training programs, and richer diversity of backgrounds in mission‑critical teams. They will measure learning velocity as a key performance indicator and invest in internal assessment tools that capture capability rather than credentials.

For workers, success will be defined by portfolio depth and adaptability. The most valuable professionals will be those who can combine human judgment, digital fluency, and collaborative instincts to amplify what machines do best with what humans do best.

Closing: a call to see differently

Sue Duke’s message is a call to action for every organization and worker navigating the AI transition: the future of work will be defined by people who can bridge the human and the algorithmic. To stay relevant, leaders must stop treating talent sourcing as a relic of credential signaling and start treating it as a capability supply chain.

Highlighting new‑collar hires is not an act of charity or convenience. It is a strategic necessity. The companies that win in the AI era will be those that can spot, cultivate, and celebrate the people who can make AI practical, reliable, and humane. The rest will be forced to play catch up in an economy where speed, adaptability, and demonstrable skill are the new currency.