Learning moves up the ladder from the middle to the top

The learning landscape inside organisations is changing at a remarkable speed. Not long ago, most corporate training conversations were aimed squarely at new graduates and early-career employees.

The centre of gravity is shifting as companies invest more in the people who already carry the most operational weight—their mid-level and senior managers.

This is a strategic rebalancing of how firms build capability in an age defined by technological disruption.

Data from an enterprise study by Great Learning shows that demand for mid-level employee training jumped to 35% in FY25 from 15% in FY24, while senior-level training more than doubled over the same period.

These figures point to a deeper shift in mindset. Learning is no longer seen as a remedial exercise or a perk for new joiners. It is becoming a central mechanism for transformation and a safeguard against obsolescence.

In the face of continuous volatility driven by artificial intelligence (AI) and automation, the capability of a company’s existing leaders has become one of its most valuable forms of resilience.

Shift matters

The emphasis on mid- and senior-level development matters. Middle managers act as interpreters of strategy, turning organisational intent into operational reality. When they grasp new technologies and can judge where and how to apply them, innovation moves faster from concept to delivery.

“These employees sit at the intersection of technology, process and people. Their training should combine technical literacy with decision-making, stakeholder management and communication. When mid managers are confident in applying new tools, digital transformation gains real momentum,” said an industry expert.

Senior leaders, meanwhile, shape incentives and allocate resources. Without digital or AI fluency at the top, even the best investments in tools or people can fail to deliver returns. A leader’s understanding of technology increasingly determines the pace of its adoption.

“Executives must understand the implications of automation for workforce planning, ethics and governance. Board-level learning on AI, data and emerging technologies builds the competence required for safe and strategic adoption,” the expert added.

At the same time, AI is reshaping the economics of talent. As automation absorbs more routine tasks, the value of human work lies in judgement, creativity and cross-functional collaboration. This shift is prompting employers to redeploy and reskill existing staff rather than hire externally for every emerging capability.

Global context

This is not an isolated phenomenon. The World Economic Forum’s Future of Jobs Report 2025 identifies skills gaps as the single largest barrier to business transformation, with more than half of employers planning to prioritise upskilling in the coming years.

A LinkedIn Workplace Learning report describes the new era of learning as “central to the AI transformation”, noting that learning functions must shift from compliance-driven training to continuous capability building.

Similarly, McKinsey & Company argues that companies which fail to act decisively on large-scale workforce upskilling will fall behind competitors that do, adding that leadership, not technology, remains the main constraint to effective adoption of AI.

Gartner’s Future of Work Trends 2025 echoes these findings, calling for learning and development to evolve from a back-office support function into a strategic enabler of competitiveness.

These perspectives paint a consistent picture: the organisations most likely to thrive in a technology-driven economy are those that treat learning as a continuous investment in leadership capability.

Other changes

The data from Great Learning for Business, which works with more than 200 enterprises in training their workforce, highlights several operational changes happening alongside this rise in mid- and senior-level training.

Many firms are now using quarterly skills-gap assessments to direct budgets more precisely. Others are introducing role-specific curricula that link directly to performance outcomes. Around a quarter of surveyed organisations tailor training to particular job families, and another quarter refresh their content regularly to reflect market trends.

The types of skills being taught are also shifting. AI and Generative AI are priorities not only for IT and technology services but also for manufacturing, financial services and healthcare. Nearly half of the organisations prioritising AI training come from IT and IT-enabled sectors, yet a growing proportion belong to industries once considered less digital.