There is a line in almost every graduation speech: The future is yours. This year, it lands differently. For many graduates, the future does not feel like a clear horizon. It feels unclear, unstable, and harder to predict than in years past.
That uncertainty surfaced at commencement ceremonies this spring where students had mixed and largely skeptical reactions to how AI opportunities were presented to them from their speakers.
Graduates are closely watching generative AI reshape writing, analysis, design, and other forms of early-career work in real time. So, when they hear broad promises about innovation and opportunity, many hear more personal questions underneath: Where do my skills fit now? Is the first rung of the career ladder still there for me?
Those questions matter because the path from college into work is being redrawn while students are still trying to step onto it. So, let’s be clear: Diplomas still matter a lot. Ambition is still important. But human judgment, practical AI skills, and the ability to adapt and learn matter more than ever.
Career readiness now depends on whether recent grads are prepared to use AI in practical and ethical ways that mirror the situations they’ll face on the job.
STUDENTS’ AI SKILLS
New Pearson and Amazon Web Services research, based on more than 2,700 learners, higher education leaders, and employers across six countries, highlights the AI readiness gap between higher education and the workforce. More than half of employers say their biggest challenge is finding graduates with the right AI skills, while only a small share of graduates say they feel highly proficient applying AI in a professional workflow.
Students may know how to open the tools, experiment with prompts, and generate answers quickly. But that is different than translating AI into a day-to-day workflow, where the harder questions are about applying practical AI-based skills that will add value to employers’ goals.
That is why this moment belongs to higher education and employers. Colleges cannot prepare students for this shift alone, and employers cannot expect new hires to arrive fully prepared.
THE PATH FORWARD
The path we need requires shared design: courses, projects, simulations, internships, and early-career experiences that reflect how AI is already changing the shape of work. Students need repeated chances to apply these tools in context, explain their choices, show where their human judgment influenced a positive outcome, and learn when not to rely on the technology at all.
Students, educators, and employers also need clearer norms. Expectations around AI use are still blurry, leaving students to guess what is acceptable while faculty worry about integrity, and managers consider workplace risk. Without clear standards, people default to their own judgment. When standards are explicit, practiced, and reinforced, trust has a chance to grow. Shared expectations around transparency, human review, and documentation can do more than reduce risk. They can help graduates carry better habits from the classroom into the workplace.
While the handoff from learning to work has rarely been easy, data shows us the growing challenges for graduates and employers are real. We’ve identified the gaps. Now it’s time for higher education, employers, and the learning community to collaborate and grab the generational opportunity to bring AI learning together with workforce needs.
Tom ap Simon is president of higher education and virtual learning at Pearson.