ChatGPT is stepping into a job market that has been struggling to find its footing. Millions of job seekers complain that sending out resumes feels like shouting into a void, while employers admit they cannot easily separate real skills from inflated buzzwords.

Per Resume Genius, as of July 2025, there were 7 million unemployed individuals competing for 7.7 million job openings, marking the first time since 2021 that job seekers outnumbered available positions. At the same time, workers worry about being displaced by the very technologies reshaping business, particularly artificial intelligence.

Into this environment comes OpenAI with a potentially disruptive concept: a jobs platform driven by ChatGPT. Reports from CNBC suggest the company is preparing to launch a hiring and certification ecosystem that could rival Microsoft’s LinkedIn. If successful, it could transform how the job market functions.

What ChatGPT May Bring to Hiring

Think of the vision as LinkedIn meets AI tutor meets recruiter—but powered by ChatGPT.

This isn’t a traditional job board. ChatGPT may integrate three core features.

First, skill certification: through ChatGPT’s study and learning modes, people could earn AI-validated micro-credentials, from AI fluency to prompt engineering, in days rather than years.

Second, AI-powered matching: instead of sifting through keyword-stuffed listings, ChatGPT might match users to roles based on demonstrated ability, not just past job titles.

Third, up-skilling: if candidates fall short of a requirement, the same AI could guide them through learning modules to get them up to speed.

Imagine logging into OpenAI’s platform and asking ChatGPT to show you open Web3 marketing roles. The AI identifies relevant openings and spots gaps in your skills—maybe in blockchain fundamentals, crypto ecosystems, or decentralized identity. It then suggests tailored training modules, and once completed, issues on-chain credentials that employers can verify. With these portable, tamper-proof certifications, ChatGPT may match you with hiring managers looking for precisely those skills—and might even facilitate scheduling interviews.

Pretty awesome promise for job seekers.

Why Timing May Be Critical for ChatGPT

Today’s labor market is fractured.

Applications stack up unanswered. Employers struggle to gauge real capability. Career shifters and those laid off can’t easily prove what they know. Meanwhile, workers feel vulnerable amid fast-moving AI disruption. OpenAI’s approach—with training and certification built into job matching—shifts ChatGPT from being seen as a threat to becoming a tool for empowerment.

The ambition is striking.

OpenAI is embedding certification directly into ChatGPT, allowing anyone to prepare and test within the app’s Study mode. The company has set a bold goal of certifying 10 million Americans by 2030, starting with launch partners like Walmart.

Walmart, the largest private employer in the world, announced it will provide the new no-cost OpenAI certification to its 2 million U.S. associates beginning next year as part of its up-skilling efforts. The program is designed to equip workers with essential AI skills and support their growth as technology becomes a larger part of daily work.

How ChatGPT Could Impact Job Seekers and Employers

For individuals, the implications could be life-changing. Many job seekers feel stuck without the right degree or with resumes filtered out by automated systems. Someone self-taught in generative AI may finally get credentials that employers trust. A mid-career worker facing layoffs could retrain quickly and prove new capabilities. International applicants might gain universally recognized credentials—all contributing to a fairer job market.

For employers, the promise is compelling. Hiring is expensive and uncertain. Resumes don’t always tell the truth, and turnover drains resources. If ChatGPT can certify skills and match candidates with greater precision, hiring could become faster, cheaper, and more confident—even introducing new pools of overlooked talent.

ChatGPT, Microsoft, and the Future of Work

The strategic dynamics are worth noting. Microsoft is OpenAI’s largest backer and also owns LinkedIn. On the one hand, OpenAI’s move may compete with its own investor’s platform. On the other, there may be collaboration—imagine ChatGPT-based certifications flowing into LinkedIn profiles. Regardless, wider AI literacy drives demand for Microsoft’s cloud and AI services, making this ecosystem too valuable to ignore.

Of course, there are risks.

Will employers accept AI-issued credentials on par with degrees? Could bias in the system reinforce inequalities? How will user data be protected? And will job seekers and employers be willing to adopt an entirely new platform? ChatGPT’s path to trust, adoption, and success depends not only on technology but on credibility. AI and education could help parents and children understand the path forward.

Still, the upside is significant. ChatGPT could recast AI from a job destroyer to a job enabler. Combining credentials, tutoring, and matching in one seamless experience may position OpenAI not just as LinkedIn’s competitor, but as the architect of a new category: the AI-driven opportunity engine.

The Future For Jobs MayBe ChatGPT

The traditional hiring playbook is outdated. Degrees are slow and often outdated, resumes are noisy, and job posts are overwhelming. Embedding seamless skills certification and learning into hiring may rewrite the hiring playbook. Will this help positively impact AI and Education?

If OpenAI succeeds, opportunities may shift from “where did you go to school?” to “what can you do?”

That paradigm shift could open doors for millions and help employers access untapped talent. We’re witnessing the early outlines of what may become one of the most significant AI applications of the next decade.

ChatGPT may not just challenge LinkedIn—it may fundamentally redefine how skills, work, and opportunity connect in a digital age.

Volkswagen will invest €1bn in AI by 2030 to transform vehicle development, production, and IT, targeting €4bn savings, faster innovation cycles, digital sovereignty in Europe, and “AI everywhere” across its industrial value chain.

In sum – what to know:

Billion-dollar AI drive – VW targets “no process without AI” to transform design, production, logistics, and IT.

Bigger industrial gains – 1,200+ AI production apps deployed; €4bn savings and 25% faster production targeted.

Sovereignty and support – push for digital sovereignty in Europe; request for AI-friendly support and regulation.

German automaker Volkswagen Group is to invest €1 billion ($1.17bn) by 2030 in AI-related industrial technologies to boost vehicle development, industrial applications, and IT infrastructure. It made the announcement at the IAA Mobility trade fair in Munich this week, with an AI-rules kind of message about its future Industry 4.0 strategy: “no process without AI”, it said. The firm reckons it will save €4 billion by 2035 from efficiency gains and cost avoidance through “consistent and scalable use of AI” across its entire “value chain”.

Hauke Stars, member of the management board for IT at Volkswagen Group, said: “Wherever we see potential, we utilize AI in a targeted manner. Scalable, responsible, and with clear industrial benefits. Our ambition: AI everywhere, in every process.” The group is working with unnamed technology and industry partners to develop a domain-specific Industry 4.0 language model, a so-called Large Industry Model (LIM), which uses design, production, and sundry automotive process data from participating companies. 

It stated: “Collective industrial process knowledge could be used to train an AI model that helps optimize internal workflows and enables more efficient logistics and process control across industries and for all participants.” An organizational blueprint for such an initiative, still in the “exploration” phase, might be the open Catena-X platform for the automotive sector and broader industrial value chain, it suggested. The Catena-X platform is designed to allow secure data exchange between manufacturers, suppliers, and other tech providers. 

Volkswagen is a founding member, alongside BMW, BASF, Mercedes-Benz, SAP, Siemens, ZF, and T-Systems. In the end, its total strategy is to make vehicles better, and faster, and AI looks like the answer. Volkswagen claims to have 1,200 AI applications in production already, and “several hundred more” in development or implementation. It has a proprietary “factory cloud”, connecting more than 40 production sites across the group. “Volkswagen is continuously introducing new AI applications into its manufacturing processes,” it said. 

Its centralised “factory cloud”, presented as a Digital Production Platform (DPP), is part of its group-wide private cloud infrastructure. This will be “significantly expanded” in the coming years, in line with its digital sovereignty play, and its hard line on resiliency “against external risks and influences”. It stated: “Technological independence and resilience begin with maintaining control over data – and that only works if data is stored, processed, and protected within Europe.” Sustainability, cybersecurity, and knowledge sharing are all part of its smarter production strategy.

In vehicle development, before its vehicles are connected to its “factory cloud” in its manufacturing sites, Volkswagen is working with Dassault Systèmes to build an “AI-powered engineering environment” to help engineers with virtual testing and component simulations across all its brands in all its markets. It wants to reduce its development cycle by around 12 months (25 percent) – to 36 months, “or less”. 

But there was a political message in its address at IAA Mobility, as well: it wants support, in exchange for support. It stated: “Volkswagen is committed to actively shaping the future of AI in Europe and supporting political and economic frameworks at both national and European levels. In an increasingly challenging environment – marked by high energy prices, elevated location costs, and administrative complexity – the company sees a clear need to advance technological innovation in AI in Germany and Europe through political support.” 

It wants “nnovation-friendly frameworks in the global AI race”, it said. Stars said: “We support the innovation-friendly evolution of European regulation. In addition, targeted incentives are needed: We must make more of what we’re capable of. This includes, above all, funding programs that strengthen spin-offs from universities and research institutions and accelerate the transfer of scientific knowledge into market-ready applications.”

The company has a large-scale internal AI training programme in place, since last year, which has already trained 130,000 staff across all levels, in all its markets. As a footnote, a blog post to go with the news of its AI investment makes AI need humans – in charge of it, and also accepting of it. Hence all the training. It stated: “AI needs rules… That is why we act on the basis of ethical standards and European regulation. When it comes to sensitive personnel issues, for example, a human being will make the final decision. Always. The key to the success of AI is acceptance.” 

Stars said: “With AI, we are igniting the next stage on our path to becoming the global automotive tech driver. AI is our key to greater speed, quality, and competitiveness – across the entire value chain, from vehicle development to production. Our ambition is to accelerate our development of attractive, innovative vehicles and bring them to our customers faster than ever before. To achieve this, we deploy AI with purpose: scalable, responsible, and with clear industrial benefits. Our ambition: no process without AI.”

University at Buffalo researchers and collaborators have completed a series of studies that reveal how much painful mouth sores known as oral mucositis increase infection risks in stem cell transplant patients and how artificial intelligence can be used to more accurately predict those risks.

Their paper, published Aug. 14 in the journal Cancers, revealed that patients undergoing hematopoietic stem cell transplants (HSCT) for blood cancers who develop oral mucositis are at nearly four times the risk of developing a severe infection compared to those without the condition. This is the first time that risk has been quantified.

The paper is the most comprehensive synthesis to date of recent findings on individual risk factors for oral mucositis, whether the transplant involves a patient’s own stem cells or donor cells. Risk factors are identified as specific drugs, such as methotrexate, high-dose chemotherapy, female gender, younger age, kidney issues, and reactivation of the herpes simplex virus.

A significant portal for infections

“Oral mucositis is not simply a source of discomfort; it serves as a significant portal for infections in immunocompromised patients,” says Satheeshkumar Poolakkad Sankaran, DDS, corresponding author on the paper and research scientist in the Division of Hematology/Oncology in the Department of Medicine at the Jacobs School of Medicine and Biomedical Sciences at UB. “All my patients with oral mucositis experience poorer outcomes, adversely impacting their quality of life.”

For this reason, he says, screening every cancer patient for oral mucositis risk ahead of time makes sense because the condition is so common — it occurs in up to 80% of HSCT patients. “Knowing risk factors can help doctors spot patients at high risk early,” he says. “This can allow for preventive steps, like oral hygiene or cryotherapy, where extremely cold temperatures are used to reduce inflammation, thus improving outcomes and quality of life.”

To better assess who is at risk, Poolakkad Sankaran and colleagues published a paper in July in Support Cancer Care describing a nomogram tool they developed to predict which patients are more likely to develop oral mucositis. A nomogram is a statistical instrument that is used to model relationships among variables. The researchers used age, gender, race, total body irradiation, and fluid/electrolyte disorders to estimate risks of developing ulcerative mucositis, a severe form of oral mucositis.

“This nomogram simplifies complex data for clinicians, enabling targeted oral care before HSCT,” explains Joel Epstein, DMD, co-author at the City of Hope Comprehensive Cancer Center.

Explainable AI better predicts adverse events

At the Multinational Association of Supportive Care in Cancer 2025 meeting in June, Poolakkad Sankaran presented additional related findings on a nomogram-based model that can better predict adverse events. He explains that this model was evaluated against a new framework that uses explainable AI, employing machine learning algorithms to assess intricate clinical and demographic facts. Explainable AI is designed to provide the rationale behind the output of an AI system.

“The AI model exhibited enhanced predictive accuracy, recognizing patterns linked to toxicities that conventional nomograms failed to detect,” he adds. “By synthesizing demographic and clinical data, the system can predict adverse events, facilitating individualized therapy modifications to reduce toxicities.”

Poolakkad Sankaran is validating the model with other cancer adverse events such as immune-related adverse events in a larger cohort, working with Roberto Pili, MD, a co-author and associate dean for cancer research and integrative oncology in the Jacobs School. Their ultimate goal is widespread clinical adoption of the model in assessing cancer patients.

“These interconnected studies underscore the oral-systemic connection in cancer therapy, urging multidisciplinary collaboration among oncologists, dentists, and AI specialists,” Poolakkad Sankaran says. “As cancer management such as HSCT and immunotherapy grows — particularly for older patients — these tools promise reduced complications, shorter hospitalizations, and lower costs.”

Reference: Eichhorn S, Rudin L, Ramasamy C, et al. Elevated likelihood of infectious complications related to oral mucositis after hematopoietic stem cell transplantation: A systematic review and meta-analysis of outcomes and risk factors. Cancers. 2025;17(16). doi: 10.3390/cancers17162657

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