Michael Eraut argues that most workplace learning happens informally, through everyday tasks and interactions. This does not reduce the value of formal training. Instead, it highlights that deep competence—especially in today’s AI-driven environments—comes from real situations, teamwork, and problem-solving.
In Pakistan, where structured training is rare, employees develop digital and AI-related skills mainly on the job. This makes Eraut’s ideas even more relevant.
Informal Learning: A Hidden Process
Eraut explains that informal learning is often invisible. Workers do not recognize it as learning. They see it simply as part of their job.
In workplaces now integrating AI tools, this invisibility creates challenges. Employees constantly learn new technologies, interpret AI outputs, and adjust workflows. Yet without reflection or guidance, much of this learning remains unrecognized.
Organizations should create feedback opportunities, reflection sessions, and safe spaces to experiment with AI. This helps employees convert daily experiences into real skill growth.
Eraut’s Triangular Framework
Eraut identifies three key factors influencing informal learning:
1. The Work Environment
Tasks become more challenging as AI automates routine work. Employees must interpret, validate, and refine AI outputs.
2. Supportive Relationships
Colleagues, mentors, and team leaders shape learning through help, feedback, and collaboration.
3. Individual Capacity
A worker’s motivation, confidence, and digital literacy affect how well they learn informally.
These factors cannot be separated. Challenging AI tasks without support cause frustration. Support without challenge leads to stagnation. In Pakistan, where mentoring culture is weak, employees often struggle without proper guidance.
Managerial Role in AI-Enhanced Workplaces
Managers play a central role in distributing tasks. They choose between:
- Efficiency: Assign AI-heavy work to skilled staff.
- Development: Allow juniors to learn challenging AI tasks with supervision.
Most organizations choose efficiency, which widens skill gaps. Eraut suggests balanced task allocation. Managers must act as facilitators of learning, especially when AI tools evolve rapidly.
Policy vs Practice Gap
Many organizations still equate training with formal courses. But the most essential workplace skills—AI literacy, digital problem-solving, teamwork—are learned informally.
Informal learning is overlooked because it is hard to measure. Certificates are visible; tacit skills are not. HR policies should value mentoring, teamwork, adaptability, and effective use of AI tools.
