2026 Global Learning Transformation Benchmark

NIIT Learning Systems Limited (NIIT Managed Training Services – NIIT MTS), a global leader in managed learning services, in collaboration with St. Charles Consulting Group, its strategic advisory subsidiary serving Fortune 1000 organizations, has released the 2026 Global Learning Transformation Benchmark Survey — one of the most comprehensive global studies examining how enterprises are rebuilding Learning & Development (L&D) for an AI-driven world.

Titled “Rebuilding L&D for an AI-Driven World,” the report presents cross-industry insights from Chief Learning Officers, HR executives, and Talent leaders across Global 500 organizations. The research provides an in-depth view of how enterprises are modernizing L&D ecosystems, integrating artificial intelligence into learning strategies, and preparing for a skills-based future amid accelerating digital disruption.

Designed for senior executives who recognize the urgency of transformation, the benchmark addresses a critical question: Why do learning transformation initiatives stall despite high intent and significant investment?

A Strategic Blueprint for AI-Enabled Learning at Enterprise Scale

“As organizations navigate unprecedented disruption, learning is under pressure to move faster and closer to the work,” said Andrea Lipton, Senior Director, Consulting & Advisory at NIIT MTS and Lead Researcher of the study. “Our findings show that speed without sustainable infrastructure creates risk, not advantage. This report helps leaders articulate the urgency of the moment while building a compelling business case for strengthening systems, governance, and operating models required to scale transformation confidently.”

Five Core Domains Defining Enterprise Learning Transformation

The 2026 benchmark evaluates organizational maturity, progress, and risk across five critical transformation pillars:

1. Skills & Talent Architecture
Enterprise foundations — including governance models, skills frameworks, career pathways, and integrated data systems — that enable scalable talent decisions.

2. AI-Enabled Learning Readiness
Organizational capability to embed AI-driven learning into the flow of work, balancing ambition with enabling infrastructure.

3. Priority–Execution Alignment
Assessment of whether strategic transformation priorities outpace operational readiness, revealing sequencing and scaling risks.

4. Learning–Business Credibility
The degree to which learning measurement frameworks are trusted and actively inform executive decision-making.

5. Operating Model Evolution
Shifts in governance, decision rights, and the movement toward hybrid or federated operating models.

The study also incorporates executive interviews, offering qualitative insights and real-world examples of how organizations are implementing skills-based workforce transformation.

Key Findings from the 2026 Global Learning Transformation Survey

Alignment is High. Readiness is Not.
Senior leaders agree on strategic priorities, yet execution gaps are most pronounced in AI-enabled learning and skills-based workforce strategies.

System Readiness Remains Uneven.
While learning design and delivery advance rapidly, governance, measurement credibility, data integration, and career architecture lag behind.

AI Amplifies Existing Conditions.
Artificial intelligence accelerates strengths in mature systems — and magnifies risks in fragile ones.

Measurement Activity Has Increased — Influence Has Not.
Although organizations are measuring learning more frequently, the evidence often lacks credibility and executive influence.

Infrastructure Determines Sustainable Scale.
Enterprises that treat learning as critical infrastructure — supported by clear governance, shared standards, and trusted metrics — are better positioned to scale safely and sustainably.

“The research exposes a structural tension: organizations understand where they need to go, but their systems are not designed for the speed AI introduces,” said Jonathan Eighteen, Global Transformation Advisor to Boards and Executive Teams on Workforce and Capability Strategy at NIIT MTS. “As learning shifts into everyday work and individuals gain greater agency, AI reprices skills — elevating judgment and accountability while compressing routine expertise. Without redefining how capability is structured, governed, and measured, speed will increase, but competitive advantage will not.”

Larry Durham, President of St. Charles Consulting Group and co-author of The Talent-Fueled Enterprise, added: “This benchmark makes one point clear: leaders are aligned on what must change next, but most organizations lack the structural readiness to deliver at enterprise scale. The issue is not intent — it is infrastructure. Executive teams are making increasingly consequential AI and workforce decisions without reliable systems connecting skills, learning, and performance. This research provides leaders with a clear lens on structural risk — and what must be rebuilt to enable sustainable growth.”

To access the full 2026 Global Learning Transformation Benchmark Survey, visit:
https://www.niit.com/en/learning-outsourcing/learning-transformation-survey-report/