How Corporate Learning Is Being Transformed By AI
getty
As organizations accelerate their investments in artificial intelligence, many are realizing that corporate learning must be fundamentally reimagined. Traditional learning and development models are no longer sufficient. Instead, organizations need to embed AI into the career development experience so learning is personalized and relevant to each job role.
This shift is reflected in recent research. A 2026 University of Phoenix survey of 150 C-suite leaders found that nine out of ten executives identify learning and development as the top HR function where AI can create value and this is up from 74% in 2025.
Nine out of Ten C-Suite leaders identify learning & development as the top use case for AI in HR
Jeanne Meister LLC
While overall U.S. corporate training spending increased from $98.0 billion in 2024 to $102.8 billion in 2025, investment in external learning products and services grew at a much faster pace—29%, from $12.4 billion to $16 billion. This sharp increase reflects organizations’ growing demand for AI-powered learning platforms, personalized learning experiences, and specialized learning partners that can accelerate workforce upskilling.
Learning providers are responding to this shift. For example, the University of Phoenix recently announced a collaboration with OpenAI to integrate AI into the student learning experience, using AI to deliver more personalized, engaging, and effective learning at scale.
As organizations invest more in AI-enabled learning, the role of learning leaders is evolving from creating content to curating personalized learning experiences that deliver measurable business outcomes.
This transformation goes beyond adopting AI tools. It redefines the purpose of the learning function from designing courses to enabling personalized learning while working.
Mars University, GE Healthcare and McKinsey illustrate what this transformation looks like in practice for integrating AI into manager development, internship and new hire on-boarding programs.
Mars First Time Manager Program Embeds AI Powered Skill Practice
Mars University, the corporate learning and development function of Mars Incorporated, has been on a journey to re-invent the learning and development function from a traditional content-delivery model into an AI-enabled one. The learning team has re-designed their first time manager experience for nearly 1,500 managers. Traditionally, the learning experience was a blended experience combining self-directed online learning with instructor-led virtual and face to face session supported by on-the-job experiences. This learning experience took 16 months and required significant effort from a team of 20 instructional designers and subject matter experts at a cost of roughly $1 million to design, refresh, translate, and deploy learning content globally to these managers.
Today, the first-time manager program has been re-designed to be a hybrid experience combining instructor led sessions with AI coaching, AI enabled simulations, and role play exercises personalized to the role and function of the learner.
Corey Munoz, Vice President of Learning at Mars University and the architect of this new first time manager program, believes “practice and not content consumption is the real measure of learning. Deliberate practice uses application, reflection, and repetition to help first-time managers build new skills and confidence before applying them at work.”
The early signals from this re-invention show 100% of learners in the manufacturing population are participating in AI-enabled practice sessions and the learning teams are gaining visibility in how learners progress across the 9-week program. Importantly, this experience is personalized to each learner, with learners receiving different role play scenarios and coaching prompts depending on their function within the company. Says Munoz, “It’s almost like having your own AI tutor in your pocket.”
GE Healthcare Internship Program Uses AI to Close Skills Gap
Each year, the GE HealthCare Commercial Leadership Intern Program selects recent college graduates for a 12-week internship to work on such projects as product launches and sales campaigns. These interns are then evaluated for entry into GE HealthCare’s full-time Commercial Leadership Program (CLP) after their internship.
The goal of the GE Healthcare Learning & Development is to create a personalized learning experience that integrates AI into the content creation, delivery, administration and reinforcement of learning. This is accomplished by leveraging AI to help these interns practice and apply key skills in customer engagement and business communication.
According to Adam Roesner, Director of Learning Technology and AI at GE Healthcare, one of the program’s primary goals is to expose interns to real business challenges where they learn how to find solutions to problems, rather than simply get answers to their questions.
Roesner notes that one of the greatest benefits of having learners engage in AI role-plays is the psychological safety this provides so learners can practice having difficult conversations and learn new skills and repeat scenarios until they feel confident and competent in their new skills.
The results have been significant. GE HealthCare reports an increase in interns receiving full-time offers following the program. At the same time, the company saved money in traditional content development by allowing time for learners to engage in AI-powered role-play scenarios.
McKinsey Integrates AI into New Hire Orientation
New hire on-boarding remains a challenge for many companies. Despite significant investment, many on-boarding programs fail to engage employees, take advantage of emerging technologies, or demonstrate measurable business outcomes. McKinsey & Company set out to change that with Embark, its global on-boarding program supporting thousands of new hires each year. The program is designed to build skills faster while providing measurable evidence of skill development across the firm.
Lisa Christensen, Global Head of Learning Innovation at McKinsey, has redesigned Embark by combining instructor-led learning with AI-powered skills practice. This blended approach personalizes the on-boarding experience, giving new hires opportunities to practice key consulting skills, receive immediate feedback, and build proficiency in problem-solving and communications.
One of the core skills taught in Embark is storylining, a McKinsey communication methodology based on the MECE (Mutually Exclusive, Collectively Exhaustive) principle. Storylining helps consultants organize complex business issues into clear, logical, and comprehensive recommendations. Storylining helps newly hired consultants structure complex business ideas into clear, non-overlapping arguments that hopefully avoid a client asking, “Have you considered this?”
According to Christensen, “By leveraging AI-powered skills practice, we saw approximately a 20% improvement in new hires’ communication skills and a 10–20% increase in efficiency gains across program delivery, content development, and instructor time.”
The redesigned Embark program demonstrates that AI can enhance, not replace, the human connection of learning. By combining AI-driven practice with instructor-led sessions and peer interactions, McKinsey created a more personalized on-boarding experience that accelerates skill development while preserving the collaboration and coaching central to consulting.
The Transformation of Corporate Learning From Content Development to Curation of Learning
Reinventing corporate learning requires far more than deploying AI tools. It requires redesigning the learning experience around critical business and talent challenges and rethinking how working and learning happen seamlessly. The greatest opportunity for AI in corporate learning is not to create more content, but to personalize learning and provide employees with opportunities to practice and improve their skills.
The experiences of Mars, GE HealthCare, and McKinsey reveal an important lesson: the future of corporate learning will be shaped less by the organizations that adopt AI and more by those that redesign learning around AI.