Rethinking entry-level hiring in the age of AI: A conversation with Amazon’s Diana Godwin

With more than two decades in talent development, learning strategy and workforce transformation, Godwin guides AI skills initiatives at scale across AWS’s certification programs, including the new Certified Generative AI Developer certification, designed to help organizations identify and upskill tech talent capable of implementing enterprise-level gen AI solutions.

In a recent conversation, Godwin shared her views on what entry-level hiring looks like now, what she’s seeking in job candidates and the increasingly important role of certifications. Following is part of that one-on-one, edited for length and clarity.

The entry-level job market has shifted dramatically with AI. What’s changed about what candidates need to bring to the table?

The fundamental change is that AI is automating many of the routine tasks that entry-level positions traditionally relied on. Today’s entry-level jobs are no longer simply about following established processes; they require problem-solving skills right from day one. This means we need to look beyond traditional four-year degrees and focus on whether candidates have developed specific, demonstrable skills that set them apart. The question isn’t just “Did you graduate?” anymore; it’s “Can you actually do the work?”

You mentioned that entry-level jobs are changing. How should HR leaders think about this evolution?

We need to recognize that entry-level doesn’t mean what it used to. These roles increasingly require cloud foundations, data literacy and the ability to apply AI competencies across different functions. The candidates who will succeed are those who can show they’ve moved beyond theoretical knowledge to keep pace with rapidly evolving technology. For HR leaders, this means rethinking job descriptions and qualification requirements to focus on skills rather than pedigrees.

What role do certifications play in this new landscape?

Certifications have become essential differentiators, particularly for candidates without traditional technical backgrounds. At AWS, we’re seeing certifications become more accessible and practical. They provide verifiable proof that someone has developed specific competencies, whether that’s in cloud foundations, data analytics or AI application. What’s important is that certifications offer a way for students and career-changers to demonstrate their capabilities through hands-on projects and practical experience, not just test-taking.

You’ve emphasized making certifications more accessible. What does that mean in practice?

AWS is actively working to close the gap between where students are and where the industry needs them to be. This includes providing resources, training programs and clearer pathways to certification. The goal is to ensure that talent from all backgrounds — regardless of whether they have a four-year degree or came from a coding bootcamp — can compete for these opportunities. We’re focused on removing barriers so that practical skills and determination matter more than traditional credentials.

How is AI itself changing the certification and skills development landscape?

AI’s rapid evolution creates both challenges and opportunities. On one hand, it means the skills we’re certifying today need to stay current with technology that’s changing monthly, not yearly. On the other hand, AI makes it possible for students and early-career professionals to learn and apply advanced concepts without needing traditional technical backgrounds. They can use AI tools to build projects, solve problems and demonstrate competencies in ways that weren’t possible before. This levels the playing field significantly.

What advice would you give HR leaders who are rethinking their entry-level hiring strategies?

First, look at your job requirements critically. Are you asking for a four-year degree when what you really need is someone with specific cloud or AI competencies? Second, consider how candidates are demonstrating their skills. Certifications, portfolios and practical projects can be stronger indicators of capability than GPA or school name. Third, recognize that the most valuable candidates may be the ones who’ve shown initiative in upskilling themselves — those who’ve pursued certifications, built projects and stayed current with AI advancements. These are the problem-solvers and self-starters who will drive your organization forward.

Finally, what’s your perspective on where entry-level hiring is heading?

We’re moving toward a more skills-based, merit-driven hiring landscape, and AI is accelerating that transition. The organizations that adapt their hiring practices now — that look for demonstrated competencies rather than traditional credentials — will have access to a much broader, more diverse talent pool. And they’ll be better positioned to build teams that can actually navigate the AI-driven workplace. This isn’t just about being more inclusive; it’s about being more competitive.