NIIT Learning Systems Limited [NIIT Managed Training Services (NIIT MTS)] (Ticker Symbol: NIITMTS), a global leader in managed learning services, along with St. Charles Consulting Group, a subsidiary of NIIT MTS and a leader in strategic consulting for Fortune 1000 organizations, announced today the release of the 2026 Global Learning Transformation Benchmark Survey. This comprehensive survey centers on the priorities and processes of senior leaders, offering critical guidance and insights for Chief Human Resources Officers, Chief Learning Officers, and other senior executives responsible for building a future-ready workforce amid the rapid rise of AI-enabled learning.
Rebuilding L&D for an AI-Driven World, the 2026 benchmark report, is a cross-sectional, global survey drawing on insights from Chief Learning Officers, Talent, and HR leaders across Global 500 industries and regions. The report offers one of the most detailed views to date of how organizations are modernizing L&D, deploying artificial intelligence, and preparing for a skills-based future. The research is designed for leaders who no longer question whether learning must change, but rather why transformation efforts so often stall despite high intent and investment.
“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 for this study. “Our research shows that moving fast without a sustainable foundation creates risk, not advantage. We hope the insights in this report help leaders clearly articulate the challenge of this moment and build a compelling business case for investing in the systems, operating models, and capabilities required to scale transformation with confidence.”
Five Core Domains of Transformation
The 2026 benchmark research evaluates maturity, progress, and challenges across five essential areas:
- Skills & Talent Architecture – The enterprise foundations – governance, skills frameworks, data and career pathways – required to scale learning and talent decisions consistently.
- AI-Enabled Learning Readiness – Readiness to deliver AI-enabled learning in the flow of work, combining ambition with enabling architecture.
- Priority–Execution Alignment – Where strategic priorities outpace current readiness, revealing sequencing and scaling risk.
- Learning–Business Credibility – Whether learning measurement is trusted and used in executive decision-making.
- Operating Model Evolution – How decision rights and governance are shifting toward more federated or hybrid models.
The study also incorporates executive interviews, adding qualitative insights and real-world context that illustrate how organizations are implementing skills-based transformation and underscore the practical relevance of the findings.
Key Findings
- Alignment is High. Readiness is Not – Leaders are aligned on priorities, but execution gaps are widest in the most strategically important areas, especially AI-enabled learning and skills-based strategies.
- System Readiness is Uneven – Most organizations exhibit uneven system readiness: design and delivery progress faster than governance, data integration, measurement credibility, and career architecture.
- AI Amplifies What Already Exists – AI amplifies existing strengths and weaknesses — scaling inconsistency and risk when systems are fragile, and accelerating impact when foundations are in place.
- Measurement has Increased, Influence has Not – Measurement activity has increased, but learning evidence often lacks credibility and influence in executive decision-making.
- Infrastructure Determines Scale – Organizations that treat learning as enterprise infrastructure — with clear governance, shared standards, and trusted measurement — are better positioned to scale safely and sustainably.
“The research exposes a structural tension: organizations know where they need to go, but their systems aren’t built for the speed AI introduces,” said Jonathan Eighteen, Global Transformation Advisor to Boards and Executive Teams on Workforce and Capability Strategy, NIIT MTS. “As learning shifts into everyday work — where individuals now have far greater agency — AI reprices skills, elevating judgment and accountability while compressing the value of routine expertise. Without redefining how capability is structured, governed, and evidenced, speed will increase, but advantage will not.”
“This benchmark makes one thing clear: leaders are aligned on what must change next but most organizations are not structurally prepared to deliver at enterprise scale,” said Larry Durham, President of St. Charles Consulting Group and Co-author of The Talent-Fueled Enterprise. “The gap is not intent, but infrastructure. Executive teams are making increasingly consequential workforce and AI decisions without systems that reliably connect skills, learning, and performance. This research gives leaders a clear view of where structural risk is accumulating—and what must be rebuilt to support sustainable growth.”
To access the full 2026 Global Learning Transformation Benchmark Survey, visit: https://www.niit.com/en/learning-outsourcing/learning-transformation-survey-report/
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