16 - 06 - 2026

Is AI is replacing ‘degrees’ with ‘proof of work’ in hiring?

LinkedIn Chief Economic Opportunity Officer Aneesh Raman on Tuesday said the global hiring system is undergoing a structural shift as artificial intelligence reshapes how organisations evaluate talent, moving away from traditional degree-based screening toward demonstrable skills and real-world work output.

Speaking at the “Level Up with LinkedIn” event, Raman said academic credentials, long used as convenient hiring shortcuts, are steadily losing strength as reliable indicators of job performance. He noted that degrees from elite institutions have historically functioned as proxies for capability, helping recruiters reduce uncertainty in selection processes.

However, he said this model is now evolving as companies seek more precise and performance-linked measures of talent. Raman said the most significant change in hiring will be the rise of “work product” as the dominant evaluation criterion.

Employers, he said, are increasingly prioritising tangible outputs such as projects, applications, writing, research, and other visible creations that demonstrate how candidates think, build, and solve problems in real-world conditions.

He added that artificial intelligence is accelerating this transition by enabling individuals to produce and showcase work more easily, while also helping organisations process large volumes of applications efficiently. This dual effect, he said, is pushing hiring systems toward more evidence-based evaluation frameworks.

On concerns that AI could deepen inequality, Raman said outcomes remain contingent on how the technology is adopted and governed. He noted that, unlike earlier technological shifts, AI is simultaneously accessible to workers, students and senior executives, which could help democratise opportunity.

However, he cautioned that the final impact will depend on access, adoption and responsible deployment.

He said resilience, adaptability and the ability to navigate failure are becoming increasingly important traits in the AI-driven economy, adding that individuals with non-linear career paths or experience of setbacks may be better equipped for uncertain work environments.

Raman also said organisations are increasingly valuing “failed founders” and candidates with unconventional trajectories, as such experiences often reflect an ability to operate under pressure, learn quickly and adapt continuously.

On recruitment practices, he noted that AI-led screening is likely to reduce administrative burden in early hiring stages, but said human judgement will remain central in interviews. He added that the interview process itself is becoming more important, as automation shifts focus away from filtering and toward deeper assessment of communication, storytelling and adaptability.

Addressing concerns around job displacement, Raman said entire job categories are not disappearing but evolving. He cited software engineering as an example, saying that while AI can now generate code, engineers are increasingly moving toward system design, architecture, customer engagement, cross-functional collaboration and ethical decision-making.

He compared the transition to the introduction of ATMs, which were expected to eliminate bank teller roles but initially expanded them as responsibilities shifted toward relationship management before declining with the rise of digital banking.

Raman concluded that it is too early to make definitive forecasts about AI’s long-term impact on employment, but said the direction of change is clear: more fluid job definitions, greater emphasis on adaptability, and a hiring ecosystem increasingly driven by demonstrable capability rather than static credentials.