The future of learning isn’t arriving someday. It’s already here.

As organizations adapt to constant disruption, the learning function has never been more critical to business agility, innovation, and growth. But the way learning operates today often determines whether it can keep pace with what’s next.

That’s why we created the Learning Performance Index—an interactive assessment designed to help learning leaders understand how their organization operates today, where it’s strong, and where it can evolve to meet the demands of an AI-powered, rapidly changing world.

The assessment evaluates how learning functions across seven key domains and interprets results through four strategic dimensions: The Work, The Team, The Business Impact, and The Brand. Together, these insights reveal which of four operating models—Foundational, Developing, Advanced, or Transformative—best describes how learning currently drives value in the organization.

The content below serves as a companion guide to the assessment. It provides the definitions, context, and strategic thinking behind the Future-Ready Framework for L&D—to help you interpret your results, reflect on your organization’s current model, and chart a path toward a more adaptive, high-impact learning function.

The future of L&D is here

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Introduction to Docebo’s Future-Ready Framework

Docebo’s future-ready framework helps senior L&D leaders and their teams evaluate their current state, identify capability gaps, and define a clear path toward becoming an adaptive, modern learning organization. Built on evidence from real-world practice, the framework introduces four operating models that capture the business value L&D delivers today and the conditions needed for future readiness. Each model consists of four dimensions that influence the effectiveness and agility of L&D’s operational capabilities within the operating model.

At the intersection of these models and dimensions lies a comprehensive view of both operational readiness and measurable outcomes. This framework shows you how to use that view to guide investment decisions, prioritize actions, and build a strategy that can stand up to unpredictable change—and position L&D as a driver of enterprise performance in the AI era.

This is not a Maturity Model

Maturity models often try to simplify the complexity of organizations into neat, prescriptive stages. They tend to categorize clients into a box with a defined problem with a matching solution. While that may work for small or mid-sized organizations, it’s far too limiting for large, complex enterprises where context is everything

Docebo’s Future-Ready Framework addresses many of the same challenges that maturity models claim to solve. Organizations still want structure, guidance, and direction, but no two organizations are equally equipped to face these challenges. Personalized guidance is needed, yet it’s rarely scalable.

Our framework aims to close that gap. It gives learning leaders adaptable tools and mental models to interpret and act within their own context. The framework’s design is intentionally flexible, scalable, and equally relevant to enterprises across industry sectors.

The Future-Ready Dimensions

Although every organization faces its own challenges, our industry research and stakeholder conversations uncovered four core dimensions where leaders in learning organizations often focus their attention. These dimensions describe how L&D excels at delivering business value: L&D’s Work, Team, Business Impact, and The Brand.

We describe the importance of each dimension and how the Learning Performance Index connects the dimensions to L&D’s operating models below. But, before you unpack the four future-ready models, take a moment to review each dimension below to best align with the definitions, scope, and considerations that are relevant for your situation. Consider in what ways each dimension is applicable to, or different from your function’s current state, and be conscious of these agreements and disagreements.

While completing the diagnostic provided, leaders are encouraged to also consider dimensions outside of the four listed, as each organization and team faces its own unique challenges. Based on our experience, these four dimensions represent what’s most important to the majority of L&D teams. 

Dimension 1: The Work

How L&D designs, delivers, and automates learning operations

The Work dimension focuses on how your L&D function operates. It encompasses the:

• agile and accessible design and delivery of learning
• integration of learning moments into the flow of work
• presence of innovation and efficiency 
• use of technology 
• creation of measurable value

The strategic value of The Work dimension lies in determining L&D’s operational impact: How L&D drives business performance, how quickly it adapts to change, and how seamlessly it embeds learning into the employee and customer experience. This dimension also surfaces friction points that keep the function stuck in low-value tasks. 

The Learning Performance Index examines whether L&D is positioned to deliver timely, high-impact learning and what steps to take in order to ensure your learning operations connect to business value. 

Dimension 2: The Team

Capability, structure, and adaptive skills within the L&D function

The Team dimension focuses on the structure, skills, and adaptability of the L&D function. It includes the: 

• composition, capabilities, and mindsets of the team 
• alignment of roles to business needs
• presence of cross-functional expertise
• use of agile ways of working
• commitment to continuous improvement and learning 

The strategic value of The Team dimension lies in its ability to help leaders determine whether L&D’s impact is limited or enhanced by the quality of its supporting players. A strong Team dimension reflects a function equipped with business acumen, digital learning expertise, comfort with AI tools, and a mindset for iteration and innovation. It’s not just about designing great programs, it’s about ensuring learning operations advance performance. 

The Learning Performance Index explores whether L&D has the talent and structure to build credibility, partner effectively, and meet evolving enterprise demands. 

Dimension 3: The Business Impact

Evidence, analytics, and influence that proves the L&D’s value

The Business Impact dimension focuses on L&D’s ability to demonstrate measurable value to the organization. It includes the: 

• use of evidence and analytics to prove impact 
• maturity of learning measurement and reporting 
• influence of the function on business decisions 
• ability to link learning outcomes to performance, ROI, and talent metrics 
• effectiveness for using data to secure support for investment

The strategic value of The Business Impact dimension lies in its role as the proof point for L&D’s credibility and growth potential. This dimension is what moves L&D from an intuitive we believe it works function into a data-driven, accountable business partner. Without credible, verifiable impact data, the function risks being seen as expendable overhead. 

The Learning Performance Index looks at whether the function operates as a data-informed, accountable business partner or remains dependent on intuition and assumptions. 

Dimension 4: The Brand

Reputation, credibility, and strategic partnerships across the organization

The Brand dimension focuses on how L&D is perceived within the organization. It includes the: 

• reputation and credibility of the function 
• alignment with business priorities 
• influence on leadership decisions
• quality of relationships with executives, managers, and employees
• participation in strategic planning

The strategic value of The Brand dimension lies in how perception shapes reality for L&D’s impact. Even a highly capable function can struggle if its value is not recognized. When L&D is seen as a trusted advisor and strategic partner, it gains the support, influence, and resources it needs to drive change. Most importantly, it becomes acknowledged as critical infrastructure and not just a support function. 

The Learning Performance Index assesses whether L&D is positioned as a cost center or a strategic lever for the business, and what actions are needed to strengthen its standing. 

L&D’s Four Operating Models

The Framework outlines four operating models based on our research, interviews with industry leaders and practitioners, discussions with Docebo customers, and key partners, influencers, and stakeholders across HR and L&D.

The four operating models outlined in this framework are tools for insight—a way to see how your L&D function works today and where it can evolve, rather than a ladder towards maturity that you’re expected to climb. Leaders should view these operating models as distinct but interconnected. Most L&D functions will find elements of more than one operating model reflected in their operation at any given time, with natural interdependencies across them. Strategic priorities, organizational context, and emerging needs (including AI integration) will influence which aspects take precedence at different moments.

The intent is not to move from one model to another in a linear progression, but to use the models—and their related dimensions—to map your current landscape, surface strengths, and identify opportunities. This perspective enables leaders and teams to make informed choices that level-up operations and strategy in alignment with the demands of an AI-powered organization.

The Foundational Model

The Foundational Model describes a state where the Learning function is core and essential, but operating with constraints that limit its ability to create sustained business impact. Across the L&D landscape, it’s fairly common to find many teams operating within this model across a number of their dimensions. 

In this model: 

• learning operations often focus on meeting immediate business requests
• investments may be loosely tied to business priorities
• measurement tends to track activity over outcomes
• governance is applied inconsistently, if at all

While these capabilities provide a baseline for effective learning delivery, they restrict adaptability and scale. The purpose of the Foundational Model is to make these strengths visible, address structural gaps, and build the conditions for a deliberate shift towards more advanced, future-ready ways of operation. 

Next, let’s take a look at how the Foundational Model might look across the four dimensions of future readiness. Compare them to your current state.

The Work

This dimension is focused on how the L&D function operates. In the Foundational Model, we find that in many cases:

• manual processes drive most learning activity
• basic and legacy digital tools support learning design 
• learning is focused on compliance, or standardized training programs 
• learning experiences are minimally adaptable or personalized 

In this operating model, the conditions are not yet ripe for innovation. Members of the team are likely under-resourced or unable to find time and energy to redevelop or redesign workflows. 

Recommended Priorities and Actions

Although the work being done in the Foundational Model is core and essential, there are operational limitations that can be addressed to help teams establish more structured workflows and processes.

Actions to consider:

1. Focus on the initial stages of governance and risk management, particularly around emerging AI tools and outline where your processes are outdated or lagging.
2. Begin an exploration of foundational AI tools to help add capacity and automation, with a particular focus on those standardized training programs. 

A future-ready L&D function offers performance as a service, and reactive needs from the organization should be easily handled by automation, supported by AI technologies.  

How Might We…

As you develop an action plan, anticipate and reframe challenges into opportunities by answering these. How Might We (HMW) questions to help you through this process. For the Work dimension, consider: 

• HMW replace manual, repetitive learning processes with AI-driven automation, while preserving accuracy and learner experience? 
• HMW modernize our learning design tools and workflows, without disrupting compliance or standardized training delivery? 
• HMW use standardized programs as a sandbox for AI or process automation experiments that can later scale to more adaptive learning experiences? 

Areas of Caution

Change is often challenging and requires a mindset shift. Here are a few critical areas of caution to watch for as you formulate your strategy and introduce change to the broader ecosystem of stakeholders: 

• Automating a broken process only scales inefficiency; redesign workflows before integrating AI. 
• Focusing AI efforts on novelty features instead of fixing core pain points will drain time and budget without moving key metrics. 
• AI tools won’t deliver sustained benefits without rethinking the underlying processes and developing a plan to improve them.

The Team

The Team dimension is focused on the structure, skills, and adaptability of the L&D function. In a Foundational Model, we find that in many cases the team:

• manages essential operational tasks (i.e., compliance training)
• have not begun to explore or use AI tools
• are limited by budget or expertise 

In this operating model, the team is likely composed of generalists, who are core to keeping essential programs running. Where possible, the team works with subject matter experts (SMEs) to distribute learning across the organization, but minimal learning theory or design is integrated or added before distribution to learners. 

Recommended Priorities and Actions

Here, the team is essential to the presence of learning across the organization and has an opportunity to expand its reach to support capacity building and change management. Smart usage of AI can add leverage and expand the team’s ability to do more in restrictive budgeting scenarios. 

Actions to consider:

1. Develop or invest in foundational AI literacy training to build capability. A future-ready L&D function works across the organization to build capability where the business needs it.
2. Identify the appropriate AI tools to optimize your L&D team’s workflow so they can be adaptable to the needs of both the business and the workforce and move with agility and speed.

AI fluency is an essential underpinning in the future of learning, and Learning teams that understand the power of this technology will be best suited to guide transformation and change. 

How Might We…

• HMW build a baseline of AI literacy for all L&D team members, so they can confidently identify authentic opportunities to integrate AI?
• HMW expand the team’s capacity by pairing SMEs with AI tools to co-create learning content without compromising on established standards?
• HMW use budget constraints as a catalyst to prioritize AI solutions that deliver the greatest leverage per dollar invested? 

Areas of Caution

• Don’t assume that team members will adopt AI tools without structured upskilling. This can create uneven capability across the team. 
• Large language models are not built for developing learning content. Consider how to integrate best practices in learning design into AI workflows to preserve quality while adding velocity.
• As AI reshapes workflows, be aware that new roles and responsibilities will likely be needed. Think about your overall team structure as you drive transformation, otherwise you may cause confusion, overlap, or gaps in delivery. 

The Business Impact

The Business Impact dimension is focused on how L&D demonstrates measurable value to the organization. In a Foundational Model, we find that in many cases, L&D: 

• ensures compliance and meets regulatory requirements
• makes minimal impact on broader operational agility or strategy 
• has limited capacity to respond to evolving business needs
• does not typically support capability development 

In this operating model, L&D has a narrow impact on the business. Reporting is typically limited to completion data, and due to a limitation in resources, capacity, and capability, the team has difficulty responding to out-of-scope requests. 

Recommended Priorities and Actions

As it relates to making an impact on the business, teams in the Foundational Model are already delivering value. Stakeholders within the function are likely very aware of this value, but broader awareness across the organization may be missing. 

This presents an opportunity for L&D leaders to increase awareness of how L&D is driving outcomes, while they continue to secure investments into the team’s development that helps to expand the reach and capacity of what they deliver. 

How Might We…

• HMW move beyond compliance metrics to demonstrate the business value of learning in measurable, outcome-focused ways? 
• HMW capture and communicate the link between L&D initiatives and operational agility? 
• HMW expand the remit from meeting current requests to proactively shaping workforce capabilities for future needs? 

Areas of Caution

• Consider both leading and lagging indicators of performance and capability. Relying solely on completion data will limit leadership’s ability to see L&D as a driver of strategic value. 
• Working in a silo is a great way to keep value hidden. Socialize the work that L&D is focused on early and often to build momentum across the organization that helps secure investment and prioritization. 
• Don’t forget to align capability-building efforts to business priorities, wherever possible. Build strong relationships with leaders in other business units, or risk being seen as an optional or secondary function.
  

The Brand

The Brand dimension is focused on how L&D is perceived by stakeholders across the organization. In a Foundational Model, we find in many cases that: 

• the organization sees L&D as necessary, primarily for compliance purposes
• engagement with learning is reactive, driven by regulatory obligations or transactional business imperatives

In this operating model, compliance training is running the show and leaves no room for guest stars. If individual teams across the organization are coaching and developing their talent, L&D is not deeply involved or supporting in meaningful ways. 

Recommended Priorities and Actions

In order for the business to see L&D as a structured and reliable partner, L&D leadership should consider positioning learning as more than compliance-driven activity by demonstrating early value in enhancing capability, efficiency, and adaptability across the organization. 

Bring performance metrics and learning analytics together into a cohesive story to help stakeholders outside of the function understand how L&D brings value. If this data is unavailable, it may be a signal that how you measure and track the impact of the team needs to be revisited (see The Work dimension).  

How Might We…

• HMW shift the perception of L&D from compliance enforcer to capability accelerator?  
• HMW use early AI-powered success stories to reposition L&D as an indispensable partner in building organizational resilience?  
• HMW ensure that L&D has sufficient learning analytics to signal both leading and lagging indicators? 

Areas of Caution

Building L&D’s brand requires consistency and regular, intentional effort. Treating this dimension as a one-off awareness push, rather than an ongoing narrative will cause advocacy and attention to quickly fade. 

Generative AI is still an emerging technology. Over-promising on AI’s impact without evidence will add risk and could damage credibility with leadership. Underpromise and overdeliver (within reason). 

Nobody outside of L&D cares about learning the way you do. Communicate L&D wins without the jargon and leverage the language of the business. 

The Developing Model

The Developing Model describes a state where the Learning function is beginning to break free from the constraints of purely foundational work. There is growing alignment with business priorities, early governance structures are in place, and AI is starting to be explored in targeted ways.

Docebo’s research and insights into the L&D landscape show that most leaders and teams continue to work inside this model. 

In the Developing Model, expect to find that:

• processes are being redesigned for scalability, with some automation already in use
• digital tools are modernizing, though adoption may still be uneven
• L&D is moving beyond compliance to start addressing capability gaps and strategic needs
• governance exists or is forming, but isn’t yet fully embedded into everyday decision-making

While the Developing Model reflects a higher level of operational capability, it still requires deliberate focus to sustain momentum, deepen integration with the business, and build the trust needed to lead at a strategic level.

Next, let’s see how the Developing Model might look across the four dimensions of future readiness. Compare them to your current state and, as always, consider other dimensions that may be unique to your organization or industry.

The Work

The Work dimension is focused on how the L&D function operates. In a Developing Model, we find that in many cases:

• workflows have been revisited to reduce manual effort, with AI tools in early use
• learning design is starting to incorporate personalization and adaptability
• compliance remains important, but strategic programs are becoming more common
• some performance support is being integrated into learning delivery

In this operating model, teams have started to reengineer processes and use modern tools, but scale and consistency remain a challenge.

Recommended Priorities and Actions

The Work in the Developing Model is established and structured. Investments made in automation are giving the team time to consider broader priorities as part of their scope.

Consider these actions:

1. Invest in workflow modernization with a focus on repeatability and scalability.
2. As you gain small wins, expand automation and AI into areas beyond compliance to include capability development and targeted performance interventions.
3. Embed governance into day-to-day decision-making so it becomes second nature to how work gets done.

At this stage, be vigilant to avoid over-engineering, which might introduce bottlenecks. Simple is clear, and clear is kind. 

How Might We…

As you develop a strategic plan to achieve your goals, anticipating and reframing challenges into opportunities is vital. How Might We (HMW) questions are a design-thinking technique to help you through this process. For the Work dimension, consider: 

• HMW expand AI-enabled workflows from pilot programs into enterprise-scale delivery without creating bottlenecks?
• HMW ensure that process redesign prioritizes learner experience alongside efficiency gains?
• HMW develop capability academies that align with organizational priorities that deliver measurable outcomes?

Areas of Caution

Change is often challenging and requires a mindset shift. Here are a few areas to watch out for as you formulate your strategy and introduce change to the broader ecosystem of stakeholders: 

Change is often challenging and requires a mindset shift. Here are a few areas to watch out for as you formulate your strategy and introduce change to the broader ecosystem of stakeholders: 

• Pilots that don’t involve learners introduce change in disruptive ways. By incorporating a cross-section of your authentic learner groups in experiments, you gain buy-in and identify champions for a wider go-live strategy. 
• As workflows evolve and pilots expand, it’s tempting to skip or deprioritize documenting what went well and what missed the mark. Documentation and post-mortem analyses set your team up for success. 
• Edge cases and exceptions will emerge naturally as you roll out new automations and begin to scale. How you anticipate these, manage expectations, and make accommodations will have a significant impact on your next steps.

The Team

This dimension is focused on the structure, skills, and adaptability of the L&D function. In a Developing Model, we find that in many cases:

• AI literacy is emerging, with some team members actively experimenting and sharing best practices
• specialized skills are beginning to complement generalist roles
• collaboration with SMEs includes more co-creation, but quality control is still needed
• budgeting allows for limited experimentation with new tools and approaches

In this operating model, the team is capable of more ambitious work but still needs structure, consistency, and targeted skill development to bring the function into more strategic, capability-building activities. 

Recommended Priorities and Actions

In this operating model, the structure of the team may be shifting as specializations become more common. The team is beginning to establish trust with stakeholders outside of Learning and HR, and is actively building relationships and trust with stakeholders across the organization.

1. Continue to focus on and standardize AI literacy across the function to avoid capability gaps. Expect that your circle of collaboration now includes IT in new and interesting ways, as AI technologies emerge across the organization. This is an accelerator on the Learning function.
2. Formalize co-creation models with SMEs that preserve learning design quality. Identify where specialist roles or skills will accelerate transformation, and plan for gradual team restructuring to meet future demands.

How Might We…

• HMW maintain and scale AI literacy across the team while the technology is still emerging and evolving rapidly? 
• HMW continue to build trust and relationships across the organization to support capability building while avoiding the trap of becoming order-takers? 
• HMW define the desired team composition, mixing generalist and specialist roles to achieve strategic goals?

Areas of Caution

• Developing AI literacy can be unpredictable, hard to track and can increase risk of burnout. Failure to communicate this with the team, or forgetting to check-in can increase risk of negative outcomes while developing capabilities.
  
• Co-creation with SMEs can accelerate content production, but skipping instructional design rigor risks turning speed into a liability. Build a plan to embed quality checkpoints into SME–AI workflows preserving both velocity and learning impact.
  
• As new tools and workflows reshape how the team operates, role boundaries can blur. Without clear ownership, you risk overlaps, missed handoffs, and delivery gaps that undermine confidence in L&D’s ability to execute.

The Business Impact

The Business Impact dimension is focused on how L&D demonstrates measurable value to the organization. In a Developing Model, we find that in many cases:

• reporting includes both activity and how leading and lagging indicators have shifted
• L&D is seen as contributing to agility and capability development in targeted areas
• leadership engagement with L&D is improving, but still inconsistent 
• the function can respond to emerging business needs with growing levels of agility

In this operating model, the value story is clearer and more connected to business outcomes. Here, L&D is invited to strategize on programs to support big-picture strategy. This is an improvement, but there is still opportunity to collaborate on a deeper level. 

Recommended Priorities and Actions

In the Developing model, the value story is starting to land. Consider these actions:

1. Avoid dashboard fatigue by treating measurement as a narrative device. Pair leading indicators such as adoption rates, time to proficiency, and early performance signals with lagging results such as quality, revenue, cost, and risk so leaders can see cause and effect.
2. Based on how your organization manages goal planning (i.e., OKRs), look for opportunities to bring business partners into the fold by co-owning targets, baselines, and review cadences. As momentum builds, start shifting from quarterly reviews from training updates to capability outcomes. 

At this stage, some pilots may be coming to maturity and full adoption. Ensure that your success criteria for these have been well defined to assist in planning cycles so that future funding and prioritization are your rewards for demonstrated impact. 

How Might We…

• HMW capture and incorporate analytics early in the workflow to identify leading indicators before they become performance gaps?
• HMW standardize the way outcomes are reported and shared so learning’s business value is visible, trusted, and repeatable across the organization?
• HMW secure a seat for L&D in annual and quarterly planning so capability development shapes the strategy?

Areas of Caution

• Measurement bloat creeps in when every metric is tracked “just in case.” Focus sharpens when you choose the few metrics that decision-makers can’t ignore. Be prepared to explain why a metric matters to those who don’t share your day-to-day context. 
• Learning impact gets lost when outcomes are presented in L&D’s language instead of the metrics the business already lives by. Translation is your force multiplier; speak the language of your stakeholders while representing the values of your team. 
• Business partners drift away when engagement feels optional. Treat their involvement as a standing meeting in your operating rhythm, not a nice-to-have.

The Brand

The Brand dimension is focused on how L&D is perceived by stakeholders across the organization. In a Developing Model, we find in many cases that:

• the organization sees L&D as increasingly relevant beyond compliance
• pockets of strong advocacy exist, but perceptions vary across business units
• L&D is more visible in capability-building and change initiatives, but not yet seen as a default strategic partner

In this operating model, L&D’s brand is established, evolving from compliance-enforcer to capability-builder. Focus on structure and consistent organization-wide reinforcement to help this model stick, while laying the groundwork for future improvements.

Recommended Priorities and Actions

In the Developing model, your brand as a capability enabler is expanding and gaining traction across the organization. 

Consider these actions:

1. Treat communication as a continuous campaign rather than a periodic update. Build a steady rhythm of impact stories that connect directly to business priorities so stakeholders see L&D as a driver of measurable change.
2. Explore AI-driven analytics to tailor messages to the language and priorities of different audiences. Remember, what resonates with frontline managers may differ from what lands with the C-suite. 

Keep your function visible in moments of strategic change, while starting to position learning as infrastructure rather than a series of interventions. 

How Might We…

• Make L&D’s contributions to strategic initiatives visible across the enterprise by embedding updates into existing business forums and communications channels?
• Use AI analytics to map the interests and priorities of different stakeholder groups so our value story speaks directly to what matters to them?
• Establish L&D as the go-to partner for capability challenges by offering rapid, targeted solutions that address urgent business needs?

Areas of Caution

• Perception gaps can form when some departments see L&D as strategic while others still think “compliance only.” Consistent brand reinforcement ensures alignment. Consider a brand or style guide for the team to document and create this consistency. 
• Bringing data meets the basic expectation. Consider how the data tells a story that revolves around a problem that was solved. Advocacy stays strong when updates are part of an ongoing narrative.
• Over-relying on AI-generated insights to tell your story without grounding them in tangible, real-world results risks eroding credibility instead of building it. Artificial technology is an emerging technology, and AI literacy means understanding where the technology adds strength, and where it adds risk.

The Advanced Model

The Advanced Model describes a state where the Learning function is recognized as a trusted partner in organizational capability-building. Learning is embedded in strategic conversations, governance is well established, and AI-enabled tools and processes are delivering consistent results across multiple programs. 

Across the L&D landscape, older, more established teams are exploring this model or already operating within it across multiple dimensions. For newer teams however, it’s expected that there might be organizational blockers or resourcing constraints that inhibit the ability to fully realize the Advanced Model. In these cases, there may still be specific dimensions where leaders can see themselves and their functions represented well. 

In this model, you can expect to find that: 

• the function supports Capability Academies through a federated hub and spoke model that scales alongside complexity 
• effective, automation and AI are integrated into core workflows, enabling the Team to focus on developing capability in alignment with organizational strategy 
• digital learning experiences are personalized at scale by AI technologies, informed by data and research-backed approaches to learning sciences
• governance and quality standards are embedded in daily operations, reducing risk and increasing consistency

L&D operating in the Advanced Model is a key stakeholder in the development of change resilience in alignment with organizational priorities. In this model, improvement often stems from subtraction and removal of inefficiencies, rather than monumental new programs that have been added. Here, learning is becoming a core part of the business infrastructure, rather than a series of reactive interventions. As governance and automation take a larger role in day-to-day operations, a diligent leader must pay close attention to the evolution of systems and their architecture to maintain reliability and agility as the needs of the business evolve. 

The Work 

The Work dimension is focused on how the L&D function operates. In an Advanced Model, we find that in many cases:

• workflows are standardized and instrumented, with AI and automation embedded in core delivery
• learning experiences are modular and adaptive, driven by real performance, usage, and adoption data
• compliance programs are reliable and efficient, while Capability Academies ensure that the business has the skills to remain strategically viable 

In this operating model, operations are comprehensive, resilient, and flexible in times of change. The focus shifts to scaling and refining feedback loops, expanding adaptive capabilities, and keeping governance responsive as technology and business needs evolve.

Recommended Priorities and Actions

L&D operating in the Advanced Model has established learning as infrastructure, rather than intervention. Focus on transitioning the team’s work to the principle of just-in-time enablement, or performance-as-a-service. To accomplish this, conduct a deep review of your function’s technology, capabilities, and areas of opportunity. Performance-as-a-service requires a learning strategy that is grounded in real-time performance data and supported by human-designed, AI-developed learning that supports learners in the flow of work. 

To accomplish this, be prepared to adopt and experiment with emerging technology. In the Advanced Model, you’re maximizing what is possible with the technology available to you. However, this approach comes with these key considerations:

1. Perform a comprehensive technology audit to evaluate your current learning tech stack for integration, scalability, and the ability to deliver in the flow of work.
2. Use AI for content creation, curation, and personalization, while keeping human oversight for design quality and ethics. And most importantly, weigh innovation adoption against clear ROI and workforce impact.

How Might We…

As you develop a strategic plan to achieve your goals, anticipating and reframing challenges into opportunities is vital. How Might We (HMW) questions are a design-thinking technique to help you through this process. For the Work dimension, consider: 

• HMW explore the jagged frontier of artificial intelligence technologies while preserving governance and standards? 
• HMW work collaboratively with vendors to inform the roadmaps of product development to drive innovation for our needs? 
• HMW connect real‑time performance signals to automatic pathway adjustments that are simple to audit?

Areas of Caution

• Mature workflows can look permanent, which slows improvement. Set review cadences that trigger even when nothing feels urgent, then refresh standards before drift accumulates.
• High levels of automation can hide exceptions until they become expensive. Use early‑warning/leading indicators and track exceptions so gaps surface early while they are still easy to manage. 
• Personalization at scale can dilute trust if impact and acceptance is untested. Validate recommendations with authentic pilots and learner validation before broad rollout.

The Team 

The Team dimension is focused on the structure, capabilities, and mindset of the Learning function. In an Advanced Model, we find that in many cases:

• the day-to-day learning needs of the business are managed through a hub-and-spoke federated model
• AI literacy is baseline across all roles, and advanced use cases are owned by cross‑functional groups that have rich context about individual team needs 
• specialist capabilities exist in areas like data, learning science, and AI orchestration, supported by shared bodies of knowledge accessible through AI knowledge management and information retrieval systems 

In this operating model, learning is managed through a federated hub-and-spoke model, where the Learning Center of Excellence (CoE) acts as the central hub providing freedom within a framework for the spokes of the system. This enables distributed learning teams to deliver complex, high-context programs with consistency and speed. 

Recommended Priorities and Actions

To enable a shift to performance-as-a-service, consider the design and development of a technology-enabled performance engine maintained by the CoE in partnership with the enterprise technology organization. The performance engine leverages AI to better understand the context of the work, helps improve and highlight the skills of each individual worker, and enhances the ability of work teams to dynamically distribute expert performance more effectively. Transformative L&D teams govern the performance engine and provide its capabilities to business functions in a hub-and-spoke model where the business functions (spokes) retain safe harbor to innovate and pilot new learning for specific needs. This drives agility, speed, and context-rich solutions within a governed (hub) performance engine. The performance engine is central to delivering capability-building to the workforce as a single, consistent performance “sidekick” for both individuals and teams.

How Might We…

• HMW design and operate a federated hub-and-spoke learning model that balances Learning CoE standards with local agility?
• HMW ensure advanced AI capabilities, such as orchestration and analytics, are seamlessly integrated into cross-functional workflows?
• HMW build and maintain an AI-enabled performance engine to make expertise and best practices instantly accessible across the federated hub-and-spoke model?

Areas of Caution

• If governance in the central Learning hub grows too heavy-handed, spokes lose the freedom to respond quickly to local needs. Maintain freedom within a framework through guardrails, not gates.
  
• Specialized expertise in areas like AI orchestration or data analytics will atrophy without sustained investment. Keep these roles funded, supported, and connected to a shared body of knowledge that raises quality across the network.
  
• Technology alone won’t make a federated model succeed. Without deliberate trust-building, shared rituals, and collaborative behaviors, the hub-and-spoke structure risks becoming transactional instead of transformational. Consider formalized rules of engagement co-authored by all relevant stakeholders in the hub-and-spoke model that is revised yearly as the needs of the organizations transform with unpredictable change. 

The Business Impact 

The Business Impact dimension is focused on how the function demonstrates measurable value to the organization. In an Advanced Model, we find that in many cases:

• reporting blends activity, leading indicators, and lagging outcomes that are aligned to the goals of adjacent business leaders 
• L&D and business leaders co-plan capability building up to a year in advance, guided by predictive analytics that align talent readiness with workforce needs
• time-to-value through learning is clearly understood by stakeholders across the organization and a driving factor in the trust and confidence in the L&D function 

In this operating model, L&D’s value story is visible and trusted. The focus now is to support innovation across the organization, stewarding change and developing change resilience. If the Team and the Work are also functioning within this operating model, expect to triage and mitigate challenges that emerge across the organization as integration challenges emerge with new tool implementations as the organization advances during times of change. 

Recommended Priorities and Actions

In this model, the Work and the Team are in solid shape and operating well across the majority of the function’s scope. Leverage this healthy performance to position L&D as a key stakeholder in developing change resilience through cultural alignment. Learning infrastructure must be flexible enough to adapt to the problem space and its solutions as the future of work evolves.

Consider these actions:

1. Integrate skill forecasting with enterprise planning and validate predictions against performance data.
2. Co‑own outcome frameworks and review cadences with business leaders.
3. Measure speed‑to‑impact and sustained results over time, then refine interventions based on evidence.
4. Keep a clear line of sight from learning investments to priority business metrics so capability becomes a competitive asset.

How Might We…

• HMW leverage predictive analytics and skill forecasting to close capability gaps in step with the business’s strategic priorities?
• HMW co-create a performance framework that balances activity with leading and lagging indicators, making time-to-value clear and credible across the enterprise?
• HMW position the Learning function as a driver of change resilience, ensuring capability-building initiatives actively support cultural alignment during times of transformation?

Areas of Caution

• Predictive analytics can erode trust if forecasts aren’t consistently validated against performance data. Close the loop quickly and in public forums so leaders see accuracy improving over time.
• Reporting that shows metrics without connecting them to time-to-value risks losing executive interest. Always tie capability gains back to measurable business acceleration.
• Strong performance on the Work and Team dimensions can mask fragility during rapid change. If possible, keep contingency plans and resource buffers ready for when new tools or processes trigger unplanned skill gaps.

The Brand 

The Brand dimension is focused on how the function is perceived by stakeholders across the organization. In an Advanced Model, we find that in many cases:

• L&D is seen as a default partner for capability-building and a competitive advantage – not just an optional contributor
• advocacy exists at multiple levels, bolstered by the strong relationships and trust developed through a federated hub-and-spoke model
• impact stories travel organically across the enterprise tied directly to strategic priorities and cultural goals

In this operating model, L&D’s reputation is well established, with influence and trust that extend across the business. The work now is to ensure that visibility, advocacy, and credibility are maintained during times of rapid change, and that the brand evolves to reflect L&D’s role as a driver of organizational adaptability.

Recommended Priorities and Actions

Sustain and grow your influence by maintaining a constant presence in strategic decision-making forums. Where possible, build a library of data-backed, context-rich narratives that speak to both the head (metrics) and the heart (stories), tuned to the needs of different audiences. Proactively cultivate advocates across every major function and level, equipping them with concise, repeatable proof points that extend your reach and reinforce the brand without your direct involvement.

How Might We…

• HMW secure a consistent presence in all internal forums and surfaces where strategy and capability decisions intersect, ensuring L&D’s role is visible and influential?
• HMW tailor the L&D value story to the priorities and language of different stakeholder groups while keeping the core message consistent?
• HMW grow a network of advocates who can carry and amplify L&D’s impact story across the organization without losing accuracy or intent?

Areas of Caution

• Strong brands fade when they aren’t actively maintained. If L&D’s voice disappears from key conversations, perception can shift quickly from strategic partner to service provider. Keep a visible role in decision-making spaces.
• Over-reliance on a handful of high-profile champions makes the function’s brand fragile. Deliberately diversify your advocate network across functions, levels, and geographies. You can’t afford to have your only champion exit the business and leave you without advocacy.
• AI-personalized messaging that gets ahead of actual performance outcomes risks undermining trust. Test messages against your authentic understanding of the stakeholders you support before allowing AI to speak on behalf of you and your function. 

The Transformative Model

The Transformative Model represents the most advanced and future-ready state for the Learning function, one that is aspirational that only a small number of organizations are positioned to realize today. This model relies on a combination of visionary strategy, highly evolved operating models, and technology that is either in the earliest stages of adoption, still in development, or has not yet been created. 

In this model, learning is fully embedded into the business’s operating system, seamlessly integrated into workflows, and constantly adapting to real-time performance signals. L&D serves not only as a strategic partner, but as a core driver of adaptability, competitive advantage, and innovation through technology. 

The Work

In a Transformative Model, we anticipate that in many cases:

• Performance-as-a-Service is fully realized, powered by advanced, modular AI systems capable of delivering adaptive, personalized learning directly into the flow of work
• Advanced LLMs and AI agents co-orchestrate design, delivery, and evaluation of learning in real time, integrated with business intelligence systems and decision-making tools
• Learning infrastructure remains under the expert management of Learning CoE, leveraging predictive models to adjust pathways under human oversight, while maintaining governance and compliance by design

Recommended Priorities and Actions

Lead on the frontier of AI-human collaboration, continuously experimenting with emerging technologies to refine performance-as-a-service. Maintain human oversight that ensures ethics, inclusivity, and alignment with cultural and business priorities. Work closely with vendors to influence the roadmap of AI systems that can integrate across the organization’s full tech ecosystem to keep learning frictionless and embedded. Dedicate monitoring capacity to workflows so the function can adapt in real-time to market or organizational shifts without sacrificing quality or trust.

How Might We…

As you develop a strategic plan to achieve your goals, anticipating and reframing challenges into opportunities is vital. How Might We (HMW) questions are a design-thinking technique to help you through this process. For the Work dimension, consider: 

• HMW create a fully integrated performance ecosystem where AI and human expertise work in constant feedback loops to anticipate and address learning needs?
  
• HMW design AI-driven experiences that can adapt in real time without compromising efficacy, compliance, equity, or learner trust?
  
• HMW leverage self-optimizing systems to free human talent for innovation, creative problem solving, and high-value strategic work?
  

Areas of Caution

• Fully autonomous AI learning systems can drift from intended business goals without human oversight. Maintain periodic human sense-checks to ensure optimization remains aligned with strategy and values.
  
• Deploying untested frontier technology directly into live workflows risks eroding trust if failures are visible to learners or leaders. Contain early deployments within controlled pilots until reliability is proven.
  
• Over-reliance on predictive AI can create complacency, leaving blind spots for novel situations.  Build in “red team” reviews to challenge assumptions and test system adaptability.

The Team

In a Transformative Model, we anticipate that in many cases:

• The federated hub-and-spoke model has matured into a seamless network with spokes operating as autonomous learning labs feeding innovation into the central learning performance engine. L&D acts as the primary learning ecosystem orchestrator over the entire system. 
• AI fluency is universal, with team members skilled in AI orchestration, advanced analytics, and human-AI collaborative design.
• Knowledge flows are instant and AI-curated, with reusable assets and playbooks available enterprise-wide at the point of need.
  

Recommended Priorities and Actions

In this model, the function is highly agile and responsive. Institutionalize the processes that allow innovation from any spoke to be evaluated, scaled, and shared. At this operating level, the business has likely invited L&D to support strategic planning in line with the executive level of planning. Where effective and relevant, use AI-enabled talent mapping to anticipate and build future capabilities before they’re needed. Build resilience into the culture by rewarding experimentation and adaptation alongside delivery.

How Might We…

• HMW maintain a culture of innovation in a mature, federated hub-and-spoke model without compromising operational stability?
  
• HMW design hybrid role profiles that future-proof the team against emerging needs and technologies?
  
• HMW create AI-enabled feedback loops that identify and replicate high-impact practices across the enterprise instantly?

Areas of Caution

• Autonomy across spokes without shared principles can fragment the function’s identity. Reaffirm core standards regularly and tie them back to the business impact required for the business units that each spoke is accountable for.
  
• Innovation pipelines from spokes can stall when evaluation criteria are unclear. Make the approval and scaling process transparent so promising proposals don’t get lost in the system.
  
• An ecosystem orchestrator role without clear decision rights (even in the CoE), risks becoming symbolic. Define authority boundaries and escalation paths with executive leadership so that orchestration translates into action.

The Business Impact

In a Transformative Model, we anticipate that in many cases:

• L&D is a co-architect of organizational strategy, with learning intelligence informing decisions in real time.
• Capability-building is proactive, predictive, and tied directly to business outcomes that are continuously monitored and adjusted.
• Learning drives cultural adaptability, creating a competitive advantage for the organization and enabling teams to thrive amid constant disruption.

Recommended Priorities and Actions

In this operating model, L&D has moved from contributing to enterprise strategy to actively shaping it. The performance engine, under L&D’s remit, should be accessible to all relevant management and executive stakeholders, integrating learning analytics into the same decision-making frameworks used for financial and operational planning. Functions operating within the Transformative Model build resilience into capability planning, ensuring the organization can pivot at speed without losing momentum. 

How Might We…

• HMW embed learning intelligence directly into executive decision-making processes so it shapes strategy in real time?
  
• HMW design predictive capability systems that combine internal data with external market signals to anticipate disruptive shifts before they impact performance?
  
• HMW design human-AI collaboration models and methodologies that evolve as new, unforeseen technologies and work patterns emerge?

Areas of Caution

• Predictive capability systems trained only on internal history can miss disruptive shifts from outside the organization. Blend internal trends with external market, technology, and societal signals to maintain foresight.
  
• Rapid pivots without a resilience plan can cause burnout and capability whiplash. Build buffer capacity and develop change-ready talent pools to absorb shocks without derailing momentum.
  
• Cultural adaptability efforts stall when they aren’t reinforced through leadership behavior. Ensure executives consistently model and communicate the adaptability mindset the organization is aiming to scale.

The Brand

In a Transformative Model,  we anticipate that in many cases:

• L&D is synonymous with organizational adaptability and innovation and seen as indispensable to the company’s ability to compete.
• Advocacy is embedded into the culture, with every leader able to work directly with their local learning resources in the hub-and-spoke model.
• The function’s reputation attracts top talent and strengthens the organization’s employer brand. 

Recommended Priorities and Actions

In this operating model, the Learning function is indispensable. Use your influence to shape both internal culture and external perception. Tell the L&D story in ways that inspire confidence in the organization’s future-readiness. Wherever possible, equip advocates with messaging that reinforces L&D’s strategic importance. 

How Might We…

• HMW position L&D as the visible engine of adaptability and innovation in both internal culture and the external market?
• HMW sustain an advocacy network that remains vibrant and accurate even as the business, technology, and workforce evolve?
• HMW leverage the employer brand impact of L&D’s reputation to attract high-caliber talent aligned with the organization’s culture and future direction?

Areas of Caution

• When brand storytelling gets ahead of delivery capability, credibility erodes quickly. Anchor every external claim in verifiable impact.
• Advocacy networks can decay without deliberate renewal. Rotate voices, refresh messaging, and celebrate contributions so advocacy remains active and authentic.
• A strong reputation can breed complacency. Keep measuring sentiment and adjusting the narrative so the brand stays relevant during shifts in market, tech, or strategy.

The organizations thriving in the AI era aren’t just reacting to change. They’re anticipating it. Understanding your current operating model gives you the foundation to adapt faster, lead smarter, and build resilience into your learning strategy.

If you haven’t already, take the Learning Performance Index assessment to see where your organization stands today and how to move confidently into the future.

By Brandon Carson

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