Executive summary. The article outlines the 2026 refresh of EFMD’s Corporate Learning Improvement Process (CLIP) accreditation framework to reflect emerging best practices in corporate learning. The update is built around four major trends: human-centred value creation, learning ecosystem orchestration, intelligent enterprise orientation, and AI-enabled learning acceleration. The revised framework evaluates how effectively learning contributes to organisational performance, agility, and strategic transformation. Through 60 updated criteria, CLIP positions corporate learning as a key driver of business value, capability development, workforce adaptability, and sustainable competitive advantage in an increasingly AI-driven world.
Key takeaways
- Corporate learning must be measured by the value it creates. Leading organisations increasingly evaluate learning through its contribution to performance, employability, capability deployment, and business outcomes.
- The role of corporate learning is shifting from provider to ecosystem orchestrator. Learning functions now curate and integrate internal and external knowledge sources, embedding learning, skills, and talent deployment directly into the workflow.
- AI is transforming both learning and the enterprise itself. Learning leaders must simultaneously use AI to accelerate the learning value chain, build AI literacy across the workforce, and help organisations manage the broader talent and cultural implications of AI adoption.
The Corporate Learning Improvement Process (CLIP) is EFMD’s accreditation scheme for corporate learning functions. Since 2002, CLIP has been the premier assessment and development system that more than 40 companies and public institutions in Europe, Asia, Latin America, and Africa have successfully implemented. It is based, like all EFMD quality management schemes, on a process of self-assessment followed by a peer review, and on a framework of excellence. The latter, in the form of the CLIP Standards & Criteria, was last revised in 20211. Given the rapid evolution of corporate learning, a 2026 refresh was undertaken and decided on by the CLIP Steering Committee in its recent spring meeting.
The framework’s overall structure of five chapters, each with three standards underpinned by four criteria, did not change; neither did the overall value chain logic. However, the chapter Resources was renamed Ecosystem, along with the renaming of several standards. The majority of the updating took place, however, at the level of the 60 criteria.
The review considered four major trends in corporate learning: (i) human-centred value creation, (ii) learning ecosystem orchestration, (iii) intelligent enterprise orientation, and (iv) AI-enabled learning acceleration. These are described in the following.
Human-centred Value Creation
Humans are not only learners but also agents of value creation. Value is only created when human capability translates into higher performance, better employability or measurable business outcomes. We have always known that human capability drives business value. Only now, given the availability of data on almost everything, are we able to measure and manage it properly.
Learning Ecosystem Orchestration
Corporate learning functions have evolved from learning providers to learning enablers, curating content from diverse internal and external sources, in addition to self-developed content, thus orchestrating a broad learning ecosystem.
The My Learning World app2 at Siemens personalises the learning offer for 240,000+ employees by selecting from a library of more than 180,000 digital learning assets that are continuously updated, originating from numerous sources.
Intelligent Enterprise Orientation
In the intelligent enterprise, learning is embedded in how work is executed, and value is created—it becomes part of the operating model rather than a separate activity. Skills and performance are made visible across the organisation, enabling capabilities to be developed and aligned more closely with strategic priorities. Talent can be dynamically matched to tasks, projects, and roles, ensuring that capabilities are applied where they create the most value. In this way, learning, skills, and talent deployment are integrated directly into the workflow, strengthening organisational agility and performance.
Several thousand field service agents at Deutsche Telekom3 are given a personalised learning offer based on their performance relative to their peer group and embedded in their schedule of field assignments resulting in first-time resolution rates increasing by 10%, and NPS by 14.
IBM is one of the most advanced examples of a skills-based organisation4. The skills of all 270,000 employees were made visible enterprise-wide. Business demand has driven skills building through a learning credentialing system that provides badges for newly acquired skills. By 2020, 1.3 million badges were issued, with an extra badge increasing a person’s promotion rate by 16%.
AI-enabled Learning Acceleration
AI turbocharges how the learning value chain operates — from identifying capability needs to design, delivery, and measurement of impact. Corporate learning functions are not only deploying AI in their own practices but are also building AI literacy across the workforce. This includes fostering an understanding of the limitations, risks and ethical implications of AI use. They provide a rich up- and reskilling offer, not as a one-off campaign but as a permanent operating model supporting ongoing workforce transformation. And they will monitor and manage the talent and culture ripple effects of AI deployment.
The refreshed CLIP Standards & Criteria mark an important step in repositioning corporate learning at the heart of organisational value creation. In the context of the intelligent enterprise, learning is no longer a supporting function but a critical enabler of strategic alignment, capability development, and continuous adaptation.
CLIP 2026 provides organisations with a rigorous framework to assess not only what their Corporate Learning Function delivers, but how effectively it contributes to organisational intelligence, agility, and performance. It challenges learning leaders to move beyond provision towards integration—embedding learning, skills, and talent into the workflow and aligning them closely with evolving business needs.
As organisations navigate a world of significant change and increasing complexity, those that can continuously learn and translate insight into action will thrive. CLIP offers both a benchmark and a roadmap for this ambition to become a reality.
Footnotes
1 See EFMD Global Focus Issue 3, Vol. 15
2 See EFMD Global Focus Issue 3, Vol. 15
3 Telecom AI Training Case Study | McKinsey
4 Free Skills-Based Learning From Technology Experts | IBM SkillsBuild
5 See EFMD Global Focus Issue 1, Vol. 20
Martin Moehrle is a management consultant and EFMD’s Director of Corporate Services and of CLIP. He was global head of recruiting, talent and learning at UBS and at Deutsche Bank.
Steven Smith is a management consultant, a Senior Advisor for EFMD’s Corporate Services and Director of LIFT. He was the head of the corporate learning function at Capgemini and Nordea.
