AI broke hiring-can OpenAI fix it?

Applicants say AI is making the job market "hell." OpenAI wants to help.

AI is flooding hiring with noise. Candidates use chatbots to write applications. HR teams use AI to screen them. Fewer people make it through, and the market feels stuck.

Surveys show rising fear. One poll found 71% worry AI will put too many people out of work permanently. Media reports point to weak demand and rising long-term unemployment. For applicants and HR, the friction is real.

The market reality: friction on both sides

• Applicants lean on AI to mass-apply; employers deploy AI to scan at scale. Both sides automate; trust drops.
• Reports cite a weak market: long-term unemployment at a post-pandemic high and "near-zero job growth."
• Early research shows AI already reducing some openings (for example, software developer roles).

OpenAI's pitch: an AI-powered hiring platform

OpenAI plans to launch an AI-driven jobs platform in 2026, positioned as a competitor to LinkedIn. The promise: match employers with AI-savvy talent based on real job needs.

OpenAI says it's been working with large retailers, consulting firms, and state agencies to map what "AI-ready" work looks like. On the surface, it reads like an AI-focused LinkedIn-profiles, resumes, matching-similar to what Hiring.cafe and Sonara already do.

There's also a certification angle. OpenAI Academy will issue certificates for AI skills, visible to employers inside the platform. LinkedIn offers certificates too, but OpenAI is betting tighter alignment between training, proof, and placement will move the needle.

Why HR should care

• Faster signal from noise: If assessments and certifications map to actual tasks, you cut time-to-shortlist.
• Clearer skills taxonomy: Role profiles built around workflows and tools (prompts, automation, data analysis) clarify expectations.
• Portfolio-first hiring: Work samples and scenario tests matter more than keyword-stuffed resumes.
• Internal mobility: The same framework can guide reskilling and internal transfers into AI-augmented roles.

Where skepticism is warranted

There's a gap between better matching and actual job creation. Some leaders predict heavy losses in entry-level white-collar roles by 2030. And if LinkedIn's feature set hasn't been a silver bullet, a new platform won't fix hiring by itself.

The question for HR: Do these certifications and models predict on-the-job performance? If not, they're just new filters on the same stack of applications.

Practical steps HR can take now

• Define AI-augmented job families: List the top tasks, target tools, and expected outputs for each role.
• Add a clear AI skills rubric to requisitions: prompt quality, tool selection, data handling, QA, and documentation.
• Use scenario-based assessments: Give candidates real prompts, datasets, or process automations; score outputs, not buzzwords.
• Tighten your ATS flow: Short written responses, structured fields, and timed work samples reduce copy-paste spam.
• Be explicit about AI use: Tell candidates what's allowed in the process (and what's not); evaluate reasoning and results.
• Pilot small: Start with 1-2 roles, run controlled experiments, and track time-to-fill, quality-of-hire, and 90-day performance.
• Upskill your bench: Fund certificates and internal labs. Prioritize cross-functional skills (ops, data, compliance).

Training and certification options

If you're building an AI skills pathway, combine internal training with external credentials that map to real tasks. Two useful starting points:

• Popular AI certifications - a quick scan of credentials HR teams actually list in job posts.
• Courses by job function - curated options for HR, ops, marketing, support, and analytics.

What to watch through 2026

• Cert validity: Do OpenAI Academy certificates predict performance better than generic badges?
• ATS integration: Can the platform plug into your stack (Greenhouse, Workday, Lever) without extra overhead?
• Assessment quality: Are the built-in tests task-relevant, anti-cheat, and updated with new toolchains?
• Pricing and ROI: Compare platform costs against reduced time-to-fill and quality-of-hire gains.
• Candidate behavior: Does the spam flood shrink, or do applicants just shift tactics?

Bottom line

AI added noise to hiring. A smarter matching layer and verifiable skills could help, but they won't replace the essentials: clear role design, skills-based assessments, structured interviews, and a real plan to upskill current staff.

Disclosure: Ziff Davis, Mashable's parent company, in April filed a lawsuit against OpenAI, alleging it infringed Ziff Davis copyrights in training and operating its AI systems.