The View
Digital Dilution
Are edtech credentials the new fast fashion of learning?
By Dr. Samir Kapur, Director, Adfactors PR
"The future demands learners who do not just use machines but think alongside them."
“Credentials must bridge education and employment, embedding practical experience through simulations, capstone projects, or internships.”
The education landscape is evolving at a blisering pace, driven by a digital revolution that mirrors the frenetic pace of fast fashion: ubiquitous, affordable and increasingly disposable. Nano-degrees, AI bootcamps and micro-credentials proliferate, offering instant access to learning with the click of a button.
From Lagos to London, learners can stack digital badges to signal expertise. Yet, this accessibility raises a critical question: are we equipping students to adapt and lead in an algorithm-driven world, or merely padding their résumés with credentials as disposable as last season’s trends?
As education merges with automation, we must scrutinise whether edtech’s promise of democratisation risks diluting quality, leaving learners unprepared for an AI-integrated future.
The "Fast Fashion" Problem
The edtech boom has flung open the doors of education. Several online edtech platforms have made credentials accessible to millions, empowering learners in regions like Sub-Saharan Africa and rural India, where traditional institutions are often out of reach. As per industry reports, the global edtech market is projected to hit $605 billion by 2027, a testament to its scale. But like fast fashion, this surge comes with trade-offs.
The market is flooded with certificates that lack rigor or recognition. A 2023 OECD report revealed that 60 percent of employers question the credibility of online credentials due to inconsistent standards. One platform’s “data science expert” might be another’s novice, with no global framework to harmonise skill verification.
Learners, often driven by ambition, accumulate badges that shine on LinkedIn but falter under scrutiny in real-world scenarios, creating a cycle of quantity over quality that undermines trust in digital credentials.

The Algorithm-Ready Learner
The future demands learners who do not just use machines but think alongside them. Employers, from tech giants in Silicon Valley to startups in Nairobi, seek workers who can navigate complex systems, make decisions in uncertain environments and collaborate with AI as partners, not tools. Digital literacy, once a benchmark, is no longer enough.
An algorithm-ready learner is a polymath: curious, adaptable and skilled in logic, ethics and systems thinking. For example, a software engineer in Bangalore might master Python but struggle to address an AI model’s ethical biases. Edtech’s focus on tutorials, coding bootcamps, and software certifications often neglects interdisciplinary problem-solving.
Initiatives like Singapore’s SkillsFuture show a better path, blending micro-credentials with industry projects that demand critical thinking. Globally, however, many platforms prioritise completion metrics over deep engagement, producing graduates who can navigate interfaces but not innovate in dynamic, AI-driven workplaces.
Feedback Deficiency in Edtech
Traditional education thrived on dialogue: professors challenged assumptions, peers sparked debate and learning was iterative. In contrast, many edtech courses are linear—watch a video, pass a quiz, earn a certificate—leaving little room for growth.
Many surveys suggest that online learners’ desire personalised feedback, but only a small portion receive it. Without robust feedback loops, students miss opportunities to revise, reflect or iterate, skills essential for resilience and adaptability. In an AI-driven world, where roles evolve rapidly, feedback is critical to align learning with reality.
Consider ETH Zurich’s “living labs”, where students refine AI prototypes with real-time industry input. Edtech must emulate such models, leveraging AI-driven analytics or mentorship to create dynamic feedback systems. Without them, credentials remain static, like last season’s clothing, failing to prepare learners for workplaces that demand constant evolution.

The Relevance Crisis
The job market evolves faster than most educational systems can keep up. AI breakthroughs redefine roles overnight, yet many edtech programmes lag behind. A 2024 World Economic Forum report highlighted that 65 percent of employers prioritise applied skills—communication, strategic thinking, contextual judgment—over badge counts.
In Brazil, where online learning has surged, platforms like Descomplica offer courses aligned with local industry needs, but globally, many credentials remain disconnected from real-world demands. For instance, a generic “AI fundamentals” course may teach TensorFlow but not how to apply it in healthcare or logistics.
Credentials must bridge education and employment, embedding practical experience through simulations, capstone projects, or internships. Without relevance, they risk becoming checklists—impressive on paper but ineffective in practice. Edtech must evolve in real time, aligning with industry shifts to ensure learners are job-ready.
Towards a Durable Learning Ecosystem
To transcend the fast fashion model, education must become modular, personalised, and lifelong. Micro-credentials offer flexibility, but they must be paired with depth. The European Union’s Digital Education Action Plan provides a blueprint, advocating for accredited micro-credentials that align with labour market needs.
In India, platforms like upGrad integrate mentorship and live projects, ensuring learners gain transferable skills. Globally, a durable learning ecosystem requires collaboration among universities, employers and regulators to set standards that prioritize quality. Peer learning, as seen in programs like Canada’s Mitacs, fosters collaboration, while AI-driven feedback can personalise growth. By designing for resilience—focusing on skills that endure across careers and industries—education can prepare learners for a world reshaped by AI, where adaptability is the new gold standard.
Education in the AI era must reject the allure of trends and embrace substance. Like couture, it should be thoughtful, intentional, and built to last. Edrech platforms have the potential to be more than credential mills—they can drive enduring transformation by prioritizing depth over dazzle, relevance over reach, and growth over gimmicks.
Credentials must signal capability, not just completion. By fostering algorithm-ready learners through rigorous standards, robust feedback, and industry alignment, we can build a learning ecosystem as dynamic and intelligent as the world it serves. The stakes are high: in a future shaped by AI, education must not just keep pace but lead, empowering students to shape tomorrow, not merely survive it.
Dr. Samir Kapur is a professional with over 29 years' experience in the field of corporate communications.