Disrupting the Learning & Development (L&D) Industry: 2025–2035 Outlook

Learning and Development (L&D)
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Introduction:
The corporate Learning & Development (L&D) industry, a $350+ billion global market, is on the cusp of profound disruptionreworked.cojoshbersin.com. Over the next 5–10 years, advances in artificial intelligence, shifting workforce dynamics, and relentless pressure for business impact are set to reinvent how organizations educate and empower their people. No longer can L&D survive as a traditional support function delivering courses and tracking completions. Instead, it is evolving into a strategic engine deeply integrated with business operations and outcomeslepaya.com. This report explores what it would take to completely disrupt L&D across four dimensions – business models, delivery mechanisms, impact measurement, and role definitions – and highlights emerging examples, pioneers, and implications for the future.

1. Rethinking the L&D Business Model

For decades, corporate training was seen as a cost center – a necessary expense to be budgeted and sometimes cut. Disruption means turning this model on its head. L&D is shifting from a cost of doing business to an investment in competitive advantage. This involves changes in how L&D is funded, positioned, and staffed within organizations:

  • From Support Function to Strategic Driver: High-impact organizations are repositioning L&D as a core business partner rather than a back-office function. Learning initiatives are increasingly tied to strategic priorities and growth objectives, so funding is justified by direct business value. In practice, this means aligning learning investments with key business goals (e.g. linking a sales training budget to expected revenue uplift)elearningindustry.comelearningindustry.com. L&D leaders are crafting a richer narrative for the C-suite that combines hard ROI metrics with evidence of cultural and capability transformationlepaya.comlepaya.com. The message: learning is not just an expense but a catalyst for performance and innovation.
  • Outcome-Based Funding: We see early signals of budgets moving toward an outcome-based model. Instead of allocating L&D funds by habit or headcount, some companies now tie funding to results and skill needs. For example, if a program demonstrably improves customer satisfaction or productivity, it earns reinvestment. Leaders increasingly demand data that shows learning has improved on-the-job performance, not just training attendanceelearningindustry.comelearningindustry.com. In one striking case, IBM’s CEO announced that 94% of routine HR inquiries (including training and development questions) are now handled by an AI agent – allowing the company to reduce HR headcount and shift budget to higher-value functionsjoshbersin.com. This kind of reallocation sends a clear signal: if L&D cannot prove its impact, its resources may be redeployed elsewhere.
  • “Always-On” Learning Budgets & Learning as a Benefit: Disruptive models also treat learning as an employee-centric “benefit” or continuous investment. Some organizations have introduced learning stipends or internal marketplaces, giving employees an allotment of funds or credits to spend on courses, certifications, or personal development of their choice. This democratizes funding and encourages a self-driven learning culture. It also forces L&D to compete on value – offering learning options employees actually want to use. In parallel, a wave of content subscription services (e.g. LinkedIn Learning, Coursera for Business) shifted L&D spending from large one-time course development to on-demand access. Now, generative AI threatens even those providers: why pay for a static content library if AI can generate custom learning content on the fly? As analyst Josh Bersin notes, traditional content vendors (from Harvard Publishing to Skillsoft) are “on borrowed time” – an AI with the right skills can dynamically produce an entire training library, upending the publishing-based business model of corporate learningreworked.co. In short, the economics of build vs. buy vs. generate are changing fast.
  • Lean, Agile L&D Teams: The disrupted business model also affects L&D staffing. Many organizations are moving toward smaller, agile L&D teams that orchestrate learning rather than create everything from scratch. The emergence of AI content generation and curation tools is enabling L&D to do more with fewer peoplereworked.co. Large instructional design teams are no longer needed to build every course when AI can assemble content in real time. Instead, L&D departments are hiring data analysts, platform curators, and performance consultants – roles focused on aligning learning to business needs and managing the systems that deliver learningreworked.co. In some cases, companies augment a tiny internal L&D core with external experts or gig contractors on-demand (a “staff augmentation” approach) to stay flexible. The broader HR operating model is evolving too: L&D may be subsumed under Talent or People Analytics functions that take a holistic view of developing workforce capabilities. The common thread is that L&D headcount per employee is likely to shrink in coming years, while investment shifts to technology and just-in-time expertise. Bersin predicts a 20–30% reduction in HR/L&D staff in organizations embracing AI – with freed-up personnel moving into roles like learning experience design, change management, or AI platform administrationjoshbersin.com. The old hierarchy of trainers and coordinators is giving way to a leaner model that treats learning like a product to be continuously improved.

Pioneers & Examples: Some companies have already begun reinventing L&D’s business model. Unilever, for instance, elevated learning as a core pillar of its “future-fit” strategy, offering every employee an allowance for self-directed education and tying skill-building to career progression. At IBM, as noted, the HR function (including learning) underwent an AI-driven transformation – their virtual agent not only answers HR questions but also helps write employees’ development plans and coach managers, effectively automating many L&D advisory tasksjoshbersin.com. This allowed IBM to reduce costs while increasing personalized support. Deloitte and Mastercard have similarly positioned their L&D teams as “capability academies” woven into business units, where business leaders co-own the learning agenda and funding is allocated based on strategic capability gaps rather than an annual training calendar. The most radical experiments even question if a standalone L&D department is needed – or if it becomes a distributed responsibility of teams, enabled by enterprise learning platforms.

2. Disrupting Delivery: AI-Powered, Self-Serve, and Embedded Learning

Perhaps the most visible dimension of L&D disruption is how learning is delivered. Traditional instructor-led workshops and static e-learning modules are giving way to a fluid ecosystem of AI tutors, on-demand microlearning, peer-to-peer knowledge sharing, and learning embedded directly into the flow of work. The end goal is a model where employees get the skills and knowledge they need when and where they need them, with minimal friction. Key shifts in delivery include:

  • AI-Powered Personalized Learning: Advances in artificial intelligence are enabling truly personalized learning experiences at scale. Instead of one-size-fits-all courses, AI can generate content and recommendations tailored to each employee’s role, skill level, and real-time needs. Generative AI can instantly create training materials – from concise how-to guides to interactive simulations – based on an employee’s query or a new task at hand. This marks a shift from a “publishing” model of learning (pre-creating courses for future use) to a dynamic model of real-time content creationreworked.co. For example, if a salesperson needs to learn a new product feature, an AI system could assemble a mini-module or even a conversation role-play on the spot. Josh Bersin observes that AI is “eliminating the need for large ‘instructional design’ teams” because the system can auto-generate and curate content, while human staff refocus on curation and coachingreworked.co. In practice, this means an L&D platform might behave like Netflix or YouTube, but smarter – serving a unique learning feed to every employee based on their development goals, performance data, and even day-to-day work strugglesreworked.co.
  • Self-Service and On-Demand Learning: Disruptive L&D organizations empower employees to pull learning as needed rather than relying solely on push programs. A hallmark example is Rolls-Royce, which is integrating AI into its knowledge management systems so employees can access crucial information on-demand instead of waiting for formal coursesreworked.co. Need to troubleshoot a machine or learn a new compliance rule? The system serves up the answer or a quick training nugget in the moment. This “just-in-time” approach is often called learning in the flow of work. It is facilitated by tools like enterprise search engines, chatbots, and learning experience platforms (LXPs) that aggregate resources from many sources. Microsoft’s recent Copilot (an AI assistant across Office apps) hints at the future: imagine Copilot not only helps you write emails or code, but also becomes a “constant, smart workplace tutor” guiding you with tips and learning content as you workreworked.co. In such a world, the line between working and learning blurs – every work task can trigger a learning interaction, and learning is available 24/7 at one’s fingertips.
  • Peer-Driven and User-Generated Content: Another delivery disruption is the rise of social and peer-based learning models. Companies are tapping into their internal subject matter experts and high performers to create content and share knowledge, rather than relying only on formal trainers. Modern authoring tools and AI assistants make it easy for employees to document a best practice or record a quick tutorial, which can be shared across the organization. This employee-generated learning approach not only scales content faster, it keeps training hyper-relevant to the company’s context. As one example, Easygenerator (an e-learning software firm) enables SMEs to create digital learning content themselves; this is both “faster and cheaper” than a central L&D team doing it, and it’s the only way to keep content continuously up to date in a fast-changing environmenteasygenerator.com. By empowering experts to capture their knowledge (with AI smoothing the edges and suggesting improvements), organizations create a living, crowdsourced curriculum. We also see growth in mentoring and coaching networks where knowledge is transferred socially. Technology platforms (like Torch, Chronus, and others) are using AI to match mentors/experts to learners and even guide those conversations. This peer-driven delivery not only spreads know-how but also builds a culture of continuous learning and collaboration.
  • Embedded Learning in Workflow: The ultimate vision for disruptive L&D is learning embedded directly into work processes. Rather than separate “training times,” learning opportunities are woven into the software and tools employees use daily. Digital adoption platforms (such as Whatfix or WalkMe) are early examples – they overlay step-by-step guidance and tips on enterprise applications, so employees learn a new system as they use it. Going further, AI can monitor work outputs and proactively deliver micro-coaching. For instance, imagine a customer service rep who, after an AI analyzes a difficult call, is immediately guided through a short refresher on de-escalation techniques. In fact, Fortune 100 companies are already moving this direction: by 2024 many firms began embedding AI assistants into workflows, signaling they don’t want standalone training events but integrated supportreworked.coreworked.co. A tangible case is Bank of America’s “The Academy”, which uses AI-powered conversation simulators to let employees practice client interactions in a realistic but risk-free environmentcoursebox.ai. A banker can rehearse a tough customer scenario with an AI that responds like a real client, getting instant feedback and guidance. This kind of embedded simulation training, done as part of regular work routines, drastically improves confidence and consistency in servicecoursebox.ai. Other examples: DHL Express built an internal AI-driven career development portal that feels “like scrolling a social feed” – it suggests personalized training and job opportunities to employees based on their profile and goalscoursebox.ai. And ServiceNow created an AI mentor called “frED” (named after the founder) that helps employees set career goals, identifies skill gaps, and recommends learning resources to close those gapscoursebox.ai. These tools function as always-available career coaches, effectively embedding L&D into the day-to-day flow of employees’ career planning and project work.
  • Multi-Modal & Immersive Experiences: Disruption is also accelerating the use of new modalities like virtual reality (VR), augmented reality (AR), and gamification to deliver learning in more engaging ways. VR/AR can simulate hands-on scenarios that were previously hard to train for. Walmart, for instance, deployed VR headsets to all stores to train associates in customer service and store safety through immersive simulations. Research shows that such “hands-on” digital experiences can significantly enhance learning by making it active and realisticcoursebox.aicoursebox.ai. A new hire can learn to operate heavy machinery in VR before touching the real equipment, or a retail employee can use AR glasses that overlay product info in front of them while they practice a sales conversationcoursebox.ai. This converts passive learning into something memorable and practical. Meanwhile, gamified learning platforms turn training into a challenge or competition, rewarding learners with points or badges – a proven way to boost engagementcoursebox.aicoursebox.ai. The common theme is meeting learners where they are and capturing their attention through modern digital experiences, rather than dry slide decks or lectures.

Delivery Disruptors in Action: Numerous organizations across industries are pioneering these new delivery approaches:

  • In manufacturing/engineering, Rolls-Royce (noted above) is cutting back formal classes and instead arming engineers with an AI knowledge tool for on-demand learningreworked.co. Similarly, Siemens has implemented AR maintenance guides that train technicians on equipment repair in situ, and Boeing uses VR to train airplane assembly procedures – embedding learning into the actual work context.
  • In finance, Bank of America’s use of AI simulation (The Academy) is a leading example of scalable, AI-driven practice for soft skillscoursebox.ai. Meanwhile, Morgan Stanley deployed an AI-based tutoring system that listens to new call-center employees and gives real-time feedback on their customer interactions. Major banks also use digital nudges: after a learning module, employees might get automated text reminders or quizzes during the work week to reinforce new knowledge, effectively extending learning into the flow of work.
  • In tech and software, companies like Salesforce have leveraged AI personalization to deliver role-specific training at scale. Salesforce’s internal L&D programs dynamically customize learning pathways for sales vs. engineering vs. marketing roles, ensuring each employee only sees content aligned to their needseidesign.net. ServiceNow’s “frED” platform (noted above) is another tech-sector innovation, treating employees as customers of an AI-powered career/learning advisorcoursebox.ai. Microsoft and Google, of course, are infusing their productivity suites with “learning moments” – from Microsoft Viva Learning (integrated into Teams for one-click access to courses) to Google’s search-based learning recommendations for its developers.
  • In logistics and retail, DHL’s use of an AI-driven internal talent marketplace (suggesting courses and stretch assignments to employees) shows how frontline workforce development can become more personalizedcoursebox.ai. Walmart’s VR training and gamified mobile learning app (which turns real sales metrics into game scores) have been emulated by others like UPS (which uses VR for driver safety training).

Across these examples, the trend is clear: learning is becoming more continuous, personalized, and embedded in everyday activity. The traditional model of signing up for a course and hoping some of it sticks until you need it is being replaced by a model of pulling knowledge in real time, often with AI as the “mentor” or “guide” on-demand. As one L&D expert put it, learning is transitioning from something you go do outside of work to something that happens as part of work. This not only improves speed-to-competency but also helps keep pace with change – when new information or skills are required, AI can update or deliver them instantly, rather than waiting for the next scheduled training updatereworked.co.

3. Real-Time, Outcome-Based Impact Measurement

One of the most persistent challenges – and opportunities – for L&D is proving its impact. In a disrupted L&D industry, the days of measuring success by course completions or smile-sheet feedback are long gone. To truly tie learning to performance, organizations are shifting to real-time, outcome-based measurement that links L&D directly to business Key Performance Indicators (KPIs).

  • From Activity Metrics to Performance Metrics: Traditional L&D metrics (enrollments, completion rates, hours of training delivered) offer limited insight into whether learning improved anythingelearningindustry.comelearningindustry.com. High completion rates, for example, don’t guarantee employees actually apply new skills on the jobelearningindustry.com. Disruptive L&D teams are refocusing measurement on what happens after training – i.e. behavior change and business results. A common framework is moving up Kirkpatrick’s evaluation levels: after engagement and knowledge acquisition, the critical measures are behavior change (are employees doing something differently or better?) and business outcomes (did it impact key metrics?)elearningindustry.comelearningindustry.com. For instance, instead of reporting that 500 employees took a sales training, a modern L&D report would show that within 3 months post-training, average deal size increased 10% and win rates improved – concrete indicators that learning drove performanceelearningindustry.comelearningindustry.com. L&D initiatives today set clear success metrics tied to business goals from the start: if the business goal is to improve customer satisfaction, the training might target a certain lift in Net Promoter Score; if the goal is operational efficiency, the metric could be reduced error rates or faster cycle times linked to training on a new systemelearningindustry.comelearningindustry.com. By defining these outcomes up front, L&D can collect the right data to demonstrate value in terms executives care about.
  • Real-Time Data and Analytics: Disruption in measurement comes from leveraging data analytics and technology to track learning impact in real time, not in retrospective annual reviews. Modern learning platforms and Learning Record Stores (LRS) can stream data on who is learning what, and correlate it with performance dashboards. Live dashboards give L&D and business leaders up-to-the-minute visibility into learning participation and its effectselearningindustry.comelearningindustry.com. For example, a dashboard might show that in the last 30 days, the Sales team completed 120 hours of training on a new product, and concurrently, sales of that product rose 15%. Or it may highlight that a certain region has low uptake of a safety training and correspondingly higher incident rates, prompting an immediate intervention. Key elements on these dashboards include trends in learner progress by department, skills gaps mapped to job roles, behavior-change indicators (like scores from post-training assessments or on-the-job observations), and pre- vs. post-training business metrics for participantselearningindustry.comelearningindustry.com. With this data centralized, L&D can rapidly identify what’s working and what isn’t, and “course-correct in real time” to improve effectivenesselearningindustry.com. If a particular program isn’t moving the needle on its intended KPI, agile L&D teams will tweak the content or approach immediately rather than waiting months. The use of predictive analytics is also emerging – for example, analyzing learning engagement data to predict which employees might be at risk of low performance or attritionelearningindustry.com. If an algorithm flags that employees who skip certain trainings tend to miss targets, managers can be alerted to encourage those learning activities. All of this makes L&D more of a data-driven science than an administrative function.
  • Continuous Feedback and Iteration: Alongside quantitative metrics, disruptive L&D functions build continuous feedback loops with learners and managers to capture qualitative impact and suggestionselearningindustry.comelearningindustry.com. Instead of one-off post-course surveys that simply ask “Did you like the training?”, modern evaluations happen at multiple intervals (30-60-90 days after training) to ask “Are you using what you learned?” and “Have you seen improvement in XYZ outcomes?”elearningindustry.comelearningindustry.com. Managers are prompted to assess if their team members’ behavior changed after completing development programselearningindustry.comelearningindustry.com. Peer feedback and self-assessments are gathered to see if skills are sticking. These qualitative insights help validate whether knowledge has translated into action, and they often reveal barriers to application that L&D can address (perhaps with refresher modules or coaching). Importantly, this is a continuous cycle: data from outcomes and feedback is immediately fed back into program design. If, for instance, sales managers report that even after training, reps struggle with negotiation, L&D might add a simulation practice module on negotiation or arrange extra coaching sessions. In a disrupted L&D model, learning programs are never truly finished – they are iteratively improved like a software product, based on real-world performance data and user input. This echoes the agile concept of developing in “sprints” and continually refining, which some L&D teams have adopted to keep pace with business changeswhatfix.comwatershedlrs.com.
  • Outcome-Based Recognition: Another facet of impact measurement is how it influences recognition and rewards. Companies on the leading edge tie learning achievements to tangible career outcomes – promotions, certifications, or bonus incentives – which closes the loop between development and performance. For example, a company might declare that employees who attain certain skill benchmarks (verified by assessments and observed performance improvements) are eligible for fast-track promotion or special assignments. This creates a culture where learning is directly associated with career growth and business value, not just personal enrichment. Some organizations even experiment with skill-based “currencies” or internal talent marketplaces where demonstrated skills (earned through learning and proven via projects) qualify employees for new opportunities and compensation, effectively making the impact of learning very visible in one’s job trajectory.

Signs of Change: The push for outcome-based measurement is clearly underway. Surveys of L&D leaders show that aligning learning to business goals is now their top priority for the second year in a rowlearning.linkedin.com. Yet, many are still early in this transformation – one study noted that demand for proof of ROI in learning is rising, but only ~16% of organizations feel ready to effectively measure itreworked.co. This indicates a huge opportunity for disruption. The tools and data exist, but mindsets and skills are catching up. Encouragingly, L&D professionals themselves are evolving: on LinkedIn, there’s been a 54% uptick in L&D practitioners listing “analytical skills” on their profiles year-over-year, reflecting a new emphasis on data competencies in the fieldlearning.linkedin.com. We also see more Chief Learning Officers partnering with CFOs and business unit leaders to develop agreed-upon learning KPIs (e.g. impact on sales, quality, innovation rate). The “From Participation to Performance” mantra is taking hold. In practical terms, forward-looking companies are building integrated data systems – connecting Learning Management Systems (LMS) with performance management, sales dashboards, and other enterprise systems – to trace the threads between development activities and outcomeselearningindustry.com. Some have even employed AI to help make these connections (for example, using AI to analyze text from employee performance reviews to see if training is mentioned as contributing to improvement, or to correlate competency assessments with business metrics).

The endgame over the next decade is that L&D’s value will be continuously proven (or disproven) through data. Consider a future scenario: a real-time L&D “impact scorecard” is as commonplace as a financial report – at any given moment, an executive could see exactly how learning programs are influencing key business metrics, and even get AI-driven suggestions for where to invest next for maximum ROI. Learning investments might then flow more dynamically to where the data shows they drive results (akin to marketers adjusting spend to high-performing campaigns in real time). Organizations that crack this code will have a formidable advantage, as they can double down on development strategies that demonstrably boost productivity, innovation, and retention – and cut loose those that don’t. As one 2025 workplace learning report put it succinctly: “In the age of AI, senior leaders must put business impact at center stage. Success isn’t delivering training; it’s delivering results.”learning.linkedin.comlearning.linkedin.com.

4. Role Transformation: The New L&D (or Its Demise)

Perhaps the most profound disruption will be in the roles and structure of the L&D function itself. As technology and new models reshape L&D, the traditional roles – trainers standing in classrooms, instructional designers building slide decks, LMS administrators tracking completions – are being either radically redefined or gradually phased out. We are witnessing a transformation of the L&D profession and its place in the organization:

  • L&D Merges with Talent and HR: In many companies, L&D is no longer a siloed department. It’s increasingly integrated with Talent Management, HR, and Organizational Development functions to create a seamless strategy for upskilling, reskilling, and career growth. CHROs (Chief HR Officers) are taking a stronger hand in learning strategy, often co-owning or directly overseeing L&D initiativeslearning.linkedin.comlearning.linkedin.com. Nearly half of organizations now say the head of HR is also responsible for internal mobility and learning programslearning.linkedin.com, reflecting this absorption of L&D into the broader talent agenda. The rationale is clear: with skills and adaptability now critical to business survival, learning can’t be an adjunct – it must be embedded in how you manage talent overall. Some organizations have created new titles like Chief Talent & Learning Officer or Chief People Capability Officer, subsuming learning into a larger role focused on end-to-end talent development. In others, the Chief Learning Officer (CLO) role still exists but is evolving to focus on learning innovation and culture more than operations. McKinsey notes that future CLOs will “lead beyond the learning function,” acting as strategic partners to business leaders and orchestrating cross-functional teams (including data analysts, technologists, and business SMEs) to drive workforce transformationmckinsey.com. In short, L&D professionals are being called upon to contribute to topics like workforce planning, change management, and employee experience, not just training delivery.
  • Shrinking and Shifting of Traditional Roles: As discussed, AI and automation are poised to handle a lot of the routine work that junior L&D staff and support roles used to do. Everything from scheduling and enrolling learners to answering basic “how do I…?” queries can be automated by chatbots and self-service systems. IBM’s internal AI, for example, now answers the vast majority of HR questions (94%) that employees ask – eliminating much of the need for HR generalists to field FAQsjoshbersin.com. It even helps write performance reviews and development plans for employeesjoshbersin.com. Translated to L&D, this means an AI can push out learning recommendations, create draft training content, and monitor progress, activities that once required multiple coordinators and content developers. The result: L&D teams may significantly downsize. We already referenced Bersin’s estimate of a 20-30% headcount reduction with AI adoptionjoshbersin.com. Those that remain won’t be doing the same tasks – their jobs will evolve. The new L&D team might consist of a “learning technology architect” (to manage AI platforms and learning systems), a data analyst (to track impact and insights), a curation lead (to source and organize content from both AI and human experts), and a few performance consultants who work closely with business units to diagnose skill gaps and design solutions. Classic roles like instructional designer or facilitator will either disappear or be redefined. Instructional design in the AI era becomes more about configuring and coaching the AI (providing it with the right inputs, quality-checking outputs) and about designing the overall experience rather than manually writing each slide or modulereworked.co. Facilitators may still exist for high-touch leadership programs or live workshops, but even those might be augmented by virtual coaches and simulations.
  • AI as the New “Team Member”: In many cases, AI tools will effectively take on the role of an L&D team member – a tireless one that works 24/7. For instance, if an AI tutor is monitoring learners’ progress and automatically intervening when someone struggles (as in the example of an AI agent that can “alert the training manager and automatically generate remedial content or invite the learner to a chat”reworked.co), then the role of a human coach or instructor shifts from first-line support to second-line escalation. The AI handles routine coaching; the human focuses on complex mentoring and exceptions. We might see AI content creators that automatically produce first drafts of training materials, which human L&D staff then refine – analogous to how many marketing teams now use AI to draft copy that humans polish. In effect, L&D professionals will need to “manage” and collaborate with AI. New skills come into play, such as prompt engineering (to get the best output from generative AI), AI ethics and governance (ensuring the AI’s advice or content is accurate and fair), and training the AI itself (providing it with company-specific knowledge or style guidelines). Only a small minority of L&D leaders today feel expert in using AI tools – just 7% according to a 2025 studyjoshbersin.com – but this will change out of necessity. L&D roles that survive and thrive will be those that embrace AI as a partner and leverage it to amplify their impact, rather than those trying to compete with or ignore it.
  • New Focus on Human Uniqueness: Interestingly, as AI takes over routine tasks, the human side of L&D work becomes even more important. There will be an amplified focus on areas where humans excel and AI cannot fully replace us: empathy, creativity, complex problem-solving, and cultural leadership. L&D professionals might spend less time compiling PowerPoints and more time consulting with business leaders on change initiatives, coaching employees in soft skills, and architecting a culture of continuous learning. One emerging role is the “Learning Experience Designer,” who draws on design thinking and behavioral science to create engaging, learner-centric experiences (often working alongside AI that handles content generation)joshbersin.comjoshbersin.com. Another is the “Capability Architect” or “Skills Strategist,” who maps out what skills the organization will need in the future and aligns learning programs to build those – a big-picture role connecting learning with workforce strategy. We also see roles like “Community Manager” in L&D, where the job is to facilitate peer learning communities and knowledge sharing across the company (something an AI can aid but not do alone, since it involves social trust and motivation). Human leadership in L&D will shift to enabling and guiding, rather than delivering, learning. The mantra becomes “let the tech do the training, while humans do the empathizing and strategizing.” Indeed, as generative AI becomes ubiquitous, there’s a paradox: the more we automate content and knowledge transfer, the more critical human skills (like judgment, ethical decision-making, emotional intelligence) become for overall successhbr.org. L&D will play a key role in cultivating those human skills – something that requires human insight to model and nurture – ensuring that people can work effectively alongside AI.
  • Job Losses and New Opportunities: It would be remiss not to acknowledge that disruption can be painful. Certain traditional L&D job families may shrink dramatically. We’ve already seen some organizations freeze hiring for content developers or even let go of trainers where digital alternatives proved effective. However, new opportunities are emerging. Consider the explosion of HR and learning tech startups – they need people who understand both learning and AI. L&D professionals who upskill in data, AI, and agile methodologies are finding exciting roles in developing next-gen learning platforms (either internally or with vendors). Additionally, as every company becomes more knowledge-driven, the skills of L&D (instructional design, content creation, coaching) are finding their way into line roles. For example, product teams might have someone who specializes in “learning content” for customer training, or consulting firms might embed learning experts into project teams to ensure knowledge transfer to the client. Some futurists even envision a role of “Chief Knowledge Officer” regaining prominence – not in the old IT sense, but as someone who ensures the organization’s knowledge is effectively created and shared (a natural evolution for a senior L&D person). What is certain is that L&D professionals must evolve or risk obsolescence. Those who cling to delivering slide decks in isolation will struggle, whereas those who can interpret data, work with AI, and drive business-relevant solutions will become linchpins of the organization. As Bersin bluntly puts it, L&D (and HR) folks who resist the AI-driven changes “risk facing a steady decline into irrelevance, with shrinking budgets to match”reworked.co.

Conclusion – The Empowered L&D Leader: In a disrupted L&D industry, the function doesn’t disappear – it transforms. In fact, many predict an “L&D revolution” is underway, where L&D finally earns a seat at the strategic table by embracing technology and proving its direct impact on growthjoshbersin.comjoshbersin.com. Organizations that get this right will have L&D leaders acting as futurists and innovators, not just training administrators. The next 5–10 years will likely see L&D fully woven into the fabric of organizational strategy, culture, and operations. The function may be smaller in headcount, but far larger in influence. And in some cases, the terminology may change – we might speak less of “training” and more of “performance enablement” or “capability acceleration,” reflecting a broadened mandate. Regardless of naming, the underlying evolution is that learning is continuous, not occasional; it’s data-driven, not faith-based; it’s personalized, not one-size-fits-all; and it’s strategic, not peripherallct.edu.vnjoshbersin.com.

Signals of Disruption and Emerging Players to Watch

Disruption in L&D is not merely theoretical – it’s happening now. Here we highlight some practical signals and pioneers that suggest the industry’s transformation is underway, as well as notable vendors and startups driving change:

  • Skyrocketing Investment in AI for L&D: Investment in AI technologies related to HR and learning is booming. By 2025, annual investment in AI is projected to reach $200 billioniseazy.com, and a significant chunk of that is flowing into corporate education tools. Practically every major learning platform vendor is announcing AI features – from auto-generated content to AI coaching bots. For example, Cornerstone OnDemand (a leading LMS provider) launched an AI-powered skills engine after acquiring an adaptive learning startup, and Workday (an HR software giant) recently acquired Sana Labs, an AI-driven learning platform, to infuse personalization into its learning module (a clear sign that even enterprise HR systems must reinvent learning).
  • Employee Expectations & Skill Gaps: The workforce itself is expecting more modern learning experiences. Surveys show 96% of employees believe generative AI will play a key role in their jobs in the near futureiseazy.com. However, only ~37% say they’ve received training in AI tools so fariseazy.com – indicating a huge skill gap that L&D needs to address. When nearly every employee recognizes AI’s importance, they will demand L&D help them upskill quickly (or they’ll seek learning elsewhere). Furthermore, new generations (Gen Z and beyond) value learning as a key driver of career growth – in one LinkedIn survey, 73% of Gen Z said “through learning I can explore new career opportunities”learning.linkedin.com. These attitudes put pressure on employers to offer cutting-edge, self-directed development avenues or risk losing talent. High attrition rates in some industries are already linked to lack of growth opportunities; conversely, companies with strong learning cultures have significantly higher retention and internal mobilitylearning.linkedin.comlearning.linkedin.com.
  • Analytics and ROI Focus: We see signs of a measurement mindset taking root. The number of organizations that have matured to the stage of measuring learning’s success (not just delivering it) is slowly increasing, but it’s telling that each year only a small single-digit percentage reach that levellearning.linkedin.comlearning.linkedin.com. The positive spin: those who do are often highlighted as industry exemplars. For instance, AT&T’s reskilling program in the late 2010s (the well-known “Workforce 2020” initiative) has become a case study in quantifying ROI of learning – they publicly tracked how many employees moved into higher-skill jobs after training. Now in the mid-2020s, many more companies are following suit by publishing internal “skills dashboards” and impact reports. Vendors like Watershed (a learning analytics platform) and Degreed (which tracks skill development) are enabling this by aggregating data from various learning experiences and tying them to performance metrics. The prevalence of OKR (Objectives and Key Results) frameworks in companies means L&D is often asked to map its metrics to company OKRs – another sign that outcome alignment is becoming standard.
  • Top Companies Pioneering New Approaches: Across sectors, certain organizations stand out for their disruptive L&D practices:
    • IBM: Already discussed for its AI-driven HR transformation, IBM has also been a pioneer in “open badge” credentials and AI skills inference. It built an internal AI tool that scans employees’ projects, learning history, and even voluntary activities to infer their skills and suggest personalized learning or career moves. IBM’s embrace of AI in HR led to the elimination of thousands of hours of menial work and a new emphasis on strategic HR/L&D initiativesjoshbersin.comjoshbersin.com.
    • Accenture: The consulting giant implemented an enterprise-wide digital learning platform that uses AI to recommend learning content to its 500,000+ employees, and it heavily leverages learning in the flow of work. Accenture also dismantled its annual performance review in favor of continuous feedback, supported by coaching training for managers – showing a trend of blending learning with performance management.
    • DHL & Unilever: These are often cited in the context of becoming “skills-based organizations.” DHL’s career marketplace (with AI suggestions) is a model for logistics and frontline worker developmentcoursebox.ai. Unilever, meanwhile, developed an AI system to assess employees’ skills and potential, and then used gamified learning journeys to encourage employees to gain future skills – all tied to an internal certification system. Both companies have reported improvements in talent mobility and employee engagement as a result.
    • Mastercard: Known for its “Learning Network,” Mastercard emphasizes peer learning and knowledge sharing through an internal platform that lets experts run bite-sized courses for others. They’ve effectively crowdsourced learning and fostered a culture where every employee is a teacher and a learner. To ensure quality, they train internal experts in facilitation skills and use learner ratings to measure impact.
    • Walmart: As mentioned, Walmart’s use of VR for hourly associate training was groundbreaking, but additionally Walmart invested in an AI-powered learning system that delivers tailored content to store managers on their tablets. They’ve reported higher retention and faster onboarding as a result. Walmart also signaled that L&D is part of their digital transformation, not separate – a strong benchmark in retail.
    • Infosys and other IT firms: Indian IT services companies like Infosys, TCS, and Wipro faced massive reskilling needs as technology shifted (e.g. towards cloud and AI). They responded by building their own online learning universities with AI recommendation engines and adaptive assessments. Infosys’s platform, for example, uses AI to create personal learning paths for engineers and has an on-demand “brainstorm with an AI expert” feature. These efforts have been credited with avoiding widespread layoffs by reskilling tens of thousands of employees into new roles.
    • Airbus (Manufacturing): Airbus launched a digital academy for its employees that incorporates AR/VR for factory training and an AI tutor for engineering knowledge. They also established “Microlearning Mondays” – short, gamified quizzes each week that all staff take part in, creating a continuous learning habit. This is a small cultural practice that signals how learning is embedded regularly, not occasionally.
    • The U.S. Defense Department (Public Sector): Even large public institutions are innovating. The DoD created an AI-based platform called “ADL” (Advanced Distributed Learning) to deliver training to soldiers anywhere, anytime, and it’s experimenting with AI to tailor simulations for individual units. Such initiatives show that disruption isn’t limited to corporate settings – government and education sectors are also adopting similar paradigms.
  • Startups and Vendors Reshaping L&D: The L&D tech market is buzzing with innovation. A few categories and examples:
    • Learning Experience Platforms (LXP): Tools like Degreed, EdCast (now part of Cornerstone), and LinkedIn Learning Hub focus on aggregating content from multiple sources and using AI to recommend learning tailored to skills and career paths. They emphasize self-directed learning and skill tracking, moving away from top-down assigned training.
    • AI Content Creation and Curation: Startups like Easygenerator and isEazy have integrated AI to help even non-experts create quality e-learning rapidly (e.g. converting a document into an interactive course automatically)easygenerator.com. Another, Synthesia, uses AI avatars to create training videos without the need for cameras or actors – useful for quickly localizing content in multiple languages or updating a video when policies change. These tools drastically reduce the time and cost to produce learning materials, enabling continuous content refresh. As Training Industry’s 2024 awards highlighted, the top emerging companies offer “AI-powered content development, coaching and feedback tools, adaptive delivery, and localization support” among other capabilitieseasygenerator.com.
    • AI Coaching and Simulation: Beyond content, a crop of solutions are tackling the human side of development with AI. BetterUp, for instance, provides an AI-enhanced coaching platform (though still primarily human coaches, AI assists in tracking progress and nudging behaviors). Mursion and Talespin use AI-driven virtual humans to let employees practice difficult conversations (like giving feedback or sales pitches) in a safe environment. Similarly, Cogito uses AI to guide call center employees in real time by analyzing their tone and stress – effectively acting as a live coach during customer calls.
    • Talent Marketplaces and Skill Platforms: Gloat and Fuel50 are examples of internal talent marketplace platforms. They match employees to projects, gigs, or roles based on their skills and interests, and they integrate learning by recommending what skills an employee should build to reach their desired next role. This blurs the line between learning and career development – learning becomes a means to achieve an internal career move, and the platform facilitates both. Such marketplaces are quite disruptive because they empower employees to drive their growth (peer-driven) and make the organization’s skill supply and demand more transparent.
    • Learning Analytics and Impact Tools: Vendors like Watershed (which grew out of the xAPI learning data standard) and Learning Pool provide sophisticated analytics to connect learning to performance. Cultivate (acquired by Perceptyx) uses AI to analyze managers’ communication patterns and then coach the manager on better behaviors – a novel approach to leadership development measurement in vivo. Even traditional LMS players (Cornerstone, SumTotal, etc.) have added analytics dashboards that pull in business data.
    • Digital Adoption and Workflow Learning: Whatfix, WalkMe, and Spekit are leaders in the digital adoption platform space, embedding step-by-step guidance into software applications. As companies accelerate software implementation, these tools ensure employees learn within the tool (e.g., when using a new CRM system, the platform pops up tips and walkthroughs). They reduce the need for classroom training on software, and importantly they collect usage data that can inform L&D where users get stuck (triggering targeted training interventions). Microsoft’s Viva suite is also one to watch – Viva Learning brings learning into Teams, Viva Topics uses AI to generate wiki-like topic pages from enterprise content (auto-curated learning), and Viva Sales is starting to integrate coaching insights for sellers. All point to embedding learning in daily workflow.
    • Immersive Learning and Gamification: Strivr (VR training), Degreed (partnering with VR content providers), Motivation Science (gamified learning journeys) and others are bringing advanced engagement techniques. As hardware like AR glasses and VR become more affordable, we expect these to become mainstream in high-impact training (safety, manufacturing, customer service role-play, etc.). For example, Bank of America’s success with VR for branch employee training (which saw a measured improvement in customer satisfaction post-training) has prompted other banks and retailers to pilot similar approaches.
    • Knowledge Management meets L&D: Companies like Starmind or Squirro offer AI-powered Q&A platforms that route employee questions to the right experts internally and provide curated answers (sort of a “Watson for enterprise knowledge”). These can act as informal learning channels: instead of taking a course, an employee asks a question and learns from the best answer. Over time, these Q&A pairs build a knowledge base accessible to all. The convergence of knowledge management and L&D technology is a notable trend – the outcome is to make organizational knowledge accessible on demand, which is arguably the purest form of learning in the flow of work.

The vendor landscape is rich, and consolidation is likely (as we see big players acquiring innovative startups). For L&D leaders, the key is not to chase every shiny tool, but to grasp the underlying capabilities these tools provide and how they align to their strategy. The fact that TrainingIndustry created a “Top 20 AI in Training” list for the first time in 2024 is itself a signal – it formalizes that AI-driven solutions are now central to the L&D tech market, not peripheral.

Implications for L&D Leaders: Preparing for the Next Decade

With disruption clearly afoot, what should L&D leaders and professionals do to navigate – and indeed harness – these changes? Below are five key actions and watchpoints for those leading learning into the future:

1. Embrace AI and Build Tech Savvy: L&D leaders must become fluent in AI and data analytics. This doesn’t mean becoming a data scientist, but understanding how AI can automate content creation, personalize learning, and generate insights – and then piloting these tools in your organization. Only 7% of L&D leaders today feel they have expert-level skills in AI platformsjoshbersin.com, which shows a huge development need for the function. Start small: experiment with a generative AI tool (like using ChatGPT or an AI course builder) on a low-stakes project to see how it can augment your team. Encourage your staff to get training in data literacy, because the future L&D team will be analyzing dashboards and making data-driven decisions regularly. Additionally, partner closely with your IT or HRIS department – integrating systems (LMS, HR systems, performance systems) is crucial for things like real-time measurement. If your current LMS or LXP lacks AI capabilities, start exploring upgrades or add-ons. The goal is to gradually infuse AI into every aspect of L&D operations, from development to delivery to evaluation. Notably, L&D teams are already upskilling in analytics (54% increase as noted)learning.linkedin.com, and many CLOs are hiring roles like “Learning Data Analyst” or “Learning Technologist” – you might consider the same.

2. Pivot from Delivering Training to Enabling Performance: Shift your mindset and strategy to focus on performance and business outcomes first, training solutions second. In practice, this means when a business leader comes with a problem (“customer complaints are up” or “we need to improve innovation”), the L&D response is not immediately “let’s run a training course.” Instead, it’s to diagnose the issue, identify if it’s a skill/knowledge gap or something else, and then design a solution that may include learning as one component. It also means designing every learning initiative with clear metrics of success (behavioral and business) and tracking them diligentlyelearningindustry.comelearningindustry.com. L&D should market itself internally not as a “course factory” but as a performance consulting and capability-building partner. This shift in positioning will help ensure L&D is invited to strategic conversations, not just brought in after decisions are made. Also, advocate for and implement tools that connect learning to work: for example, performance support tools, embedded “quick help” resources, and richer on-the-job feedback processes. One practical step is to invest in a learning analytics capability (either via a platform or internal expertise) that can pull data from various sources – LMS, work KPIs, employee surveys – to tell a story of learning impact. When L&D can show a dashboard of how a program moved the needle on key metrics, it builds immense credibility. As a 2024 industry guide noted, “aligning learning to business goals” remains the top focus area for L&Dlearning.linkedin.com – make it your mantra. Remember, what gets measured gets done; by measuring what truly matters (outcomes), you’ll start designing learning that truly matters.

3. Champion a Culture of Continuous, Self-Directed Learning: Disruptive L&D is as much about culture as technology. Foster an environment where learning is not an event but a habit, woven into daily routines. Encourage and train managers to become learning champions who coach their teams and allocate time for development (for example, setting “learning hours” where teams collectively engage in learning, or simply normalizing that taking time for a course is acceptable). Promote shared ownership of learning: leadership must reinforce it as a priority, and employees should feel empowered (and expected) to drive their own growthlepaya.comlepaya.com. Tactics to consider: launch internal campaigns for new learning initiatives focusing on WIIFM (what’s in it for me) to spark intrinsic motivation; create internal communities or interest groups around skill areas (e.g. a data science learning circle); implement knowledge-sharing forums (like lunch-and-learns, or enterprise social Q&A as mentioned). Also, leverage peer learning – identify internal experts and reward them for contributing content or mentoring others. Perhaps start an internal “expert marketplace” where employees can sign up to teach short sessions on anything they’re skilled at. Peer-driven approaches both scale and increase engagement, because colleagues often learn better from each other’s real-world experience. Lastly, visibly align learning with career advancement. Ensure employees see the connection (via internal success stories or even policy) that those who learn and apply new skills get ahead. When learning is seen as one’s own responsibility and path to success, the culture is primed for all the new tools and methods to actually take root.

4. Redefine L&D Roles and Upskill Your Team: As roles shift, proactively reskill and reorganize your L&D team. Conduct a skills assessment for your L&D staff: do they have strengths in data analysis, digital content creation, AI tool use, consulting with stakeholders? Identify gaps and provide development (you might need to ironically “train the trainers” in these new areas, possibly using external courses or certifications in learning analytics, agile project management, etc.). Encourage your team to experiment with new technologies and to iterate solutions in shorter cycles rather than spending months on perfecting a single course. Consider new roles or role rotations: for example, appoint a “Learning Innovation Lead” who keeps abreast of emerging tech and runs pilots; designate a “Learning Impact Manager” who focuses on measurement strategies. Moreover, prepare the team (and yourself) for possible structural changes – e.g. embedding L&D business partners in different units, or merging the L&D team under a broader Talent or People organization. It could be worthwhile to cross-train with HR colleagues in talent management or workforce analytics, to build bridges and understand each other’s domains. On the staffing front, as AI handles more content development, you might repurpose some instructional designers into “learning curators” (their job becomes finding and organizing the best content from outside sources and AI outputs, rather than creating from scratch). You might also reduce pure delivery roles and increase roles that manage vendor platforms or that focus on coaching/mentoring (since experiential and personal development will still need a human touch). The key is to proactively drive the change rather than waiting for it. As Bersin advises HR/L&D folks: accept that AI “is going to disrupt our role” and lean into redesigning jobs to focus on higher-value work that AI can’t dojoshbersin.comjoshbersin.com. This ensures your team stays relevant and essential in the new L&D landscape.

5. Stay Informed and Experiment Boldly: Finally, keep a finger on the pulse of L&D innovations and be willing to try new approaches. The pace of change is rapid – “every week brings a new, mind-blowing development in AI’s capabilities,” as one expert notedreworked.co. Join professional networks, attend industry conferences (many now focus heavily on AI in learning), and follow thought leaders (e.g., Josh Bersin, Jane Hart, Dani Johnson) to learn from early successes and failures. It’s advisable to maintain a small experimental budget or sandbox for L&D. Pilot that VR module for leadership training, or try out an AI coaching app with a volunteer cohort of employees, or set up a demo of a new platform that claims to do real-time skill tracking. Measure the results, gather feedback, and scale up what shows promise. Also, watch the moves of big players – for instance, when Microsoft or Google embed learning features into popular workplace tools, plan how to leverage those rather than reinventing the wheel. Pay attention to your own industry’s disruptors: if you’re in retail, what are the learning tactics of the fastest-growing retailers? If in tech, how are leading tech firms keeping engineers skilled on new frameworks? These can offer inspiration and validation for your own initiatives. And don’t overlook the importance of user experience – as L&D becomes more productized, employee experience with learning tools matters. Keep an eye on adoption rates and user feedback for any new technology you deploy; iterate to improve the UX just as a software product team would (e.g., if employees aren’t engaging with an LXP, find out why – is content not relevant, is interface clunky? – and adjust accordingly). Essentially, treat innovation as a continuous process. The next decade may bring things like AI-driven adaptive learning paths that change daily or widespread use of “digital twin” employees for simulation-based training. Being curious and agile will let you ride these waves instead of being swamped by them.

6. (Bonus) Safeguard the Human Element: Amid all the tech excitement, L&D leaders should also be the guardians of the human element in learning. The future will demand uniquely human skills – creativity, critical thinking, leadership, empathy – in greater quantities, precisely because automation will handle the resthbr.org. L&D has a crucial role in developing these “soft” or “power” skills which are harder to measure but deeply vital. Ensure your strategy balances high-tech with high-touch. This might mean preserving certain in-person experiences (like leadership retreats or peer networking events) even as you digitize other aspects. It also means using AI ethically and transparently – for example, if you use AI to monitor performance for learning insights, be clear with employees about how it works and ensure data privacy. By championing a responsible, human-centered approach, L&D can build trust in the new tools. Employees will be more willing to engage with an AI coach if they know it’s there to help, not surveil, and if they feel their managers and L&D partners still genuinely care about their growth as individuals. Ultimately, learning is deeply personal – it changes who we are. The disrupted L&D industry should enhance that personal journey, not diminish it.

In conclusion, the Learning and Development field is poised for a comprehensive reboot. The coming disruptions – new business models focused on value, AI-augmented delivery systems, rigorous impact measurement, and transformed roles – will not be easy. But they promise a future where L&D is faster, smarter, and more relevant than ever before. In that future, learning is continuously woven into work, every employee has a personalized development path guided by intelligent systems, and every learning effort is tied to moving the needle for the business. Organizations that pioneer these changes (and the solution providers enabling them) are already reaping benefits: more agile workforces, higher engagement, and better performance. Those that lag may find their L&D efforts – and perhaps their entire talent strategies – outpaced by a rapidly changing world.

For L&D leaders, the mandate is clear: disrupt yourselves before you are disrupted. By adopting new technologies, new metrics, and new mindsets, you can position L&D as the linchpin of organizational success in the next decade. The time to act is now – as one report urged, “if you’re in L&D, 2025 is the year to wake up and realize the AI revolution is here.”reworked.co The L&D revolution isn’t coming; it has arrived. And it will utterly transform how we learn and grow at work – for the better, if we rise to the occasion.

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Ravinder Tulsiani

Dr. Ravinder Tulsiani

Dr. Ravinder Tulsiani is a renowned Leadership Expert, Author, and Speaker with 25+ years in the corporate sector. He brings a unique blend of academic insight and practical experience. His approach is data-driven, ensuring that every learning intervention is not only engaging but also delivers measurable ROI.
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