AWS training exec: genAI isn’t killing entry-level jobs — it’s redefining them

Generative AI (genAI adoption is transforming entry-level roles in the tech industry, with more than half of workloads now augmented by AI, according to one study. Tasks such as drafting reports, synthesizing research, fixing simple code, and cleaning data, can already be executed by AI tools, according to the study by the World Economic Forum.

Early career professionals often struggle to identify which genAI skills are most valuable. The need for continuous learning, and changes in how educators and employers prepare students and entry-level workers to become “AI-native professionals,” is becoming an imperative for both organizations and employee careers.

Many companies aren’t hiring despite a clear AI skills gap as policymakers, educators, and industry leaders struggle to work together to future-proof the workforce.

“Fewer job openings, softer wage growth, and longer job searches are signs of a slowdown,” said Ger Doyle, North American regional president at global staffing firm ManpowerGroup. “The hiring momentum that kicked off the year has been tempered by uncertainty.”

Michelle Vaz, managing director at AWS Training and Certifications, believes genAI will create different demands for entry-level talent and AI literacy has already shifted from optional to essential. Continuous learning is now a necessity to keep up with the pace of change.

Vaz believes educators and employers can prepare tech workers for the “AI shift” through alternative training programs designed to enable “AI-native professionals” capable of contributing from day one on the job. In a written Q&A with Computerworld, Vaz discussed which specific AI competencies or certifications are emerging as essential across non-technical roles – and how education systems can integrate these into mainstream curricula early on.

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AWS

Even with an AI skills gap, organizations are still reluctant to hire. What’s happening? Why aren’t companies closing their AI skills gap? “We recently partnered with Draup, a data intelligence firm specializing in workforce planning and talent analytics, to conduct research on how early-career technical roles are evolving due to AI. Our findings revealed an interesting paradox: young adult unemployment is at 6.6% while simultaneously, AI is transforming technical roles and making them more accessible for early-career talent. What we are seeing is opportunity, not the disappearance of roles. Entry-level positions are being reshaped and made more accessible as traditional barriers like requiring extensive coding experience are removed through AI automation. This represents a transformation — companies aren’t just looking to fill skills gaps, they are seeking people who can leverage AI to make a greater impact earlier in their careers.

“This represents a fundamental shift in how we should think about entry-level work, reframing it as an opportunity multiplier — one that democratizes access to technical careers by removing traditional barriers and allowing talent from diverse backgrounds to make meaningful contributions from day one.

“Today’s companies are facing a skills mismatch where employer demands (AI literacy, cloud, ML engineering) are evolving faster than traditional education can adapt, while simultaneously many early career professionals are increasingly entering the workforce generative AI-enabled. Organizations now need people who can step into complex projects from day one — candidates with the right mix of AI and cloud skills who can contribute meaningfully. To address this skills gap, organizations must support practical, hands-on training programs that go beyond theory, giving students real-world AI and cloud experience before they enter the workforce and ultimately bridging the gap between classroom learning and industry needs.”

With AI rapidly evolving, how can policymakers, educators, and industry leaders collaborate to ensure that training programs remain relevant and adaptable across different professions and industries? “The ‘half-life of skills’ — the time it takes for a skill to lose half its market relevance -—has decreased from 10 to 15 years to about five years, and even shorter for technical skills. We are at a pivotal moment that requires organizations to fundamentally reimagine learning for the AI era. The traditional model simply can’t keep pace with today’s rate of technological change. Today’s AI-native workforce demands a different learning approach: modular, bite-sized learning with immediate application rather than traditional long-form courses. Organizations need to acknowledge this shift and create alternative pathways for quick application and credential-building. Organizations must prioritize hands-on practical opportunities that deliver real business impact.

“AWS Academy demonstrates this approach by providing free, ready-to-teach cloud and AI curricula to higher education institutions, partnering with over 6,600 institutions globally and offering free AI and cloud curricula that are continually updated to reflect industry needs.

“Amazon recently also announced its support for the White House Pledge to America’s Youth and the Presidential AI Challenge. As part of the White House’s Pledge to American Youth, Amazon will support AI skills training for four million US learners, enable AI curricula for 10,000 US educators, and provide up to $30 million in credits for eligible organizations to use cloud and AI technology to support students and educators in the US by 2028.”

Early-career professionals often struggle to identify which AI skills are most valuable. How can education systems and workforce development programs better guide young talent in choosing the right paths? “The key is having an open and curious mindset. For example, engineers today need to think less about writing every line of code themselves and more about how to orchestrate, validate, and scale solutions with AI. What is critical is the appetite to continually upskill through certifications, hands-on learning, and peer learning. It’s about being prepared and acknowledging that roles are transforming rapidly.

“One clear takeaway from our recent research is that AI is reshaping five high-growth roles — software development, data analysis, cloud engineering, cybersecurity, and data engineering. By pointing early professionals to these career paths and offering the specific AI-related skills that are needed, such as cloud computing or AI-driven data insights, educational systems and workforce development programs can help these early professionals navigate towards higher-value opportunities.

“At the same time, it’s important to keep in mind that AI literacy and foundational skills will soon be the table stakes across every entry-level role. There is an opportunity for the private and public sector to partner with education systems to develop more accessible training programs that offer hands-on practice in working with AI. These programs can be critical for helping students graduate into a workforce where they will be expected to use these tools in real-world situations.”

As AI transforms job roles, what balance should be struck between technical AI skills (like machine learning or prompt engineering) and human-centric skills (like ethics, creativity, and collaboration) in modern education? “AI is fundamentally changing the nature of work and career preparation. As automation handles more routine tasks, entry-level roles are becoming increasingly sophisticated. This evolution demands a thoughtful balance in how we prepare students for success.

“Technical AI literacy is certainly crucial — understanding machine learning concepts, working with cloud technologies, and effectively using AI tools are becoming foundational skills. However, human elements have also become more vital as AI handles the routine. Critical thinking, ethical judgment, creative problem-solving, and collaboration are skills that AI cannot replicate.

“The key is integrating both dimensions into education:

Build strong fundamentals first — just as we learn basic math before using calculators, students need core analytical and writing skills before leveraging AI tools.

Develop adaptability — while specific technologies will evolve, the ability to learn and grow remains constant.

Balance technical and human capabilities — as AI manages routine tasks, interpersonal skills and ethical judgment become increasingly valuable.

At AWS, we see this balanced approach as essential for developing well-rounded professionals who can not only implement AI solutions, but also understand their broader implications and applications. The goal isn’t just creating technical experts, but nurturing professionals who can think critically, solve problems creatively, and collaborate effectively while leveraging AI capabilities responsibly.  Available on AWS Skill Builder, AWS SimuLearn — powered by Amazon Bedrock — provides an immersive learning experience that pairs generative AI-powered simulations with hands-on training to help learners translate business problems into technical solutions.

“With AWS SimuLearn, leaners can develop soft skills, such as communication and problem-solving, in life-like conversations with AI-generated personas. An AI quiz agent evaluates conversation responses, and an AI helper agent is available when students get stuck. 

“The education system must evolve to develop both technical AI fluency and strengthen uniquely human capabilities. This balanced approach will best prepare students to thrive in an AI-transformed workplace.”Are genAI-fueled layoffs ever legit? Oracle may have found a way – ComputerworldRead More