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Comparing the Top Change Management Models

Jay Perlman, Copywriter

Jay Perlman

Người sáng tạo nội dung quảng cáo tại Udemy

Comparing the Top Change Management Models

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Tóm tắt nội dung

Change management models help organizations move people from old ways of working to new ones. Use ADKAR for individual tech adoption and skills training, Kotter’s 8-Step for enterprise-wide cultural shifts, and Lewin’s 3-Step for bounded changes. Whatever the framework, put training at the center and measure success by behavior change, sustained adoption, and business outcomes.

Most change initiatives don’t fail because leaders picked the wrong strategy. They fail because the framework didn’t match the actual problem. A model built for senior leadership alignment won’t help when the real barrier is individual skill gaps. One designed for a one-time change won’t hold up under continuous AI adoption.

This guide covers the five most widely used change management models: when to use each, how they compare, and how to connect them to a training approach that makes adoption stick.

What are change management models?

Change management models are structured frameworks that guide organizations from current ways of working to new ones. Each model emphasizes a different lever for making that shift happen.

Five models appear most often in enterprise settings:

  1. Lewin’s Change Model
  2. Kotter’s 8-Step Model
  3. The ADKAR Model
  4. Bridges’ Transition Model
  5. The McKinsey 7-S Framework

Each answers a slightly different question. Lewin asks whether the organization is psychologically ready to change. ADKAR zeros in on the individual: can each person actually make this change? Kotter asks whether leadership has a plan to build and sustain momentum. Bridges addresses the emotional loss people feel during transitions.

For an L&D leader structuring an AI training program for 500 employees, or a department head rolling out a new workflow across multiple teams, model selection determines where to focus time, budget, and leadership attention.

How the top frameworks compare

No single change management framework fits every situation. Understanding the trade-offs helps L&D leaders avoid mismatches that slow adoption and waste resources.

1. Lewin’s 3-Step Model

Lewin’s Change Model asks the core question of whether an organization psychologically ready to change. It moves through three stages: unfreeze, change, and refreeze. The model works well for bounded, discrete changes with a clear start and end point, like a policy update or a single-system migration.

Its main limitation is that it offers no detailed implementation steps, and the “refreeze” concept doesn’t hold up well under continuous change environments like ongoing AI adoption, where the goal is sustained adaptation rather than a return to stability.

2. Kotter’s 8-Step Model

Kotter’s 8-Step Model asks whether leadership has a plan to build urgency and sustain momentum. It’s best suited for large-scale cultural shifts and enterprise-wide initiatives where top-down alignment is the primary driver. The eight steps move from creating a sense of urgency through anchoring change in culture.

The limitation is that the model is sequential and time-intensive, with a strong emphasis on leadership over individual adoption. It works well for setting direction but needs pairing with an individual-focused model like ADKAR when behavior change at the team level is the real goal.

3. ADKAR Model

ADKAR asks whether each individual can move through five stages: awareness, desire, knowledge, ability, and reinforcement. It’s the most direct fit for technology rollouts, skills training, and any initiative where behavior change at the individual level is the primary barrier. Unlike leadership-focused frameworks, ADKAR treats adoption as a personal progression and identifies exactly where someone is getting stuck.

Its limitation is scope. It doesn’t address broader organizational planning, structural alignment, or the leadership momentum needed to sustain a large-scale initiative.

4. Bridges’ Transition Model

Bridges’ Transition Model asks whether people are processing the emotional loss that comes with change. It distinguishes between the external event (the change) and the internal experience (the transition), arguing that most initiatives fail because leaders manage the change but ignore the transition. It’s best suited for restructuring, mergers, and role redefinitions where identity shifts are involved.

The limitation is that it provides psychological insight without much operational guidance, making it most useful as a complement to a more execution-focused framework like Kotter or ADKAR rather than as a standalone model.

5. McKinsey 7-S Framework

McKinsey’s 7-S Framework asks whether seven organizational elements, including strategy, structure, systems, shared values, skills, style, and staff, are aligned. It’s best suited for cross-functional realignment when multiple systems are changing simultaneously, such as a merger integration or a full operating model redesign. Unlike the other four models, it doesn’t focus on guiding people through change. It diagnoses whether the organization’s structure supports it.

The limitation here is complexity. It requires deep analysis across all seven dimensions and is better used as a diagnostic tool alongside an execution-focused model than as a standalone change playbook.

The framework matters, but execution fundamentals matter more. Understanding teams’ resistance to AI adoption makes model selection far more effective.

Matching the right model to your initiative

Model selection gets easier when you start with three questions: what’s changing, who needs to change, and how long the change will take.

Drive technology and AI adoption

When the goal is getting employees to use a new AI tool or platform, the barrier is usually employee resistance. People need to understand why the tool matters, want to use it, know how to use it, and be capable of applying it in their actual work. That’s ADKAR’s territory. An AI upskilling roadmap connects directly to ADKAR’s Knowledge and Ability stages, translating business goals into role-specific learning paths rather than generic course catalogs.

Framing AI as skill-enhancement drives greater employee engagement, while framing it as a productivity boost creates job insecurity. These framing effects align with ADKAR’s sequential logic of how change is communicated during the Awareness stage shapes whether employees develop the Desire to engage before any Knowledge transfer can succeed.

Lead enterprise-wide cultural shifts

When change affects the entire organization, Kotter’s 8-Step Model provides the leadership playbook. Creating urgency, forming a guiding coalition, and generating short-term wins are designed to build momentum across a large workforce.

A VP of Product moving 45 people from traditional product development into AI-augmented workflows isn’t facing a training problem alone. It requires leadership alignment, a clear vision employees can rally around, and visible early wins that prove the new approach works. Pairing Kotter with Bridges’ Transition Model adds the emotional layer, helping employees process anxiety about new ways of working before expecting them to adopt new behaviors.

Build skills-focused initiatives

An L&D director rolling out a prompt engineering program for 200 customer support agents needs more than a course catalog. ADKAR’s five sequential stages map to how learning professionals actually build competency by creating awareness of the skill gap and motivation to close it, delivering targeted training, following with hands-on practice, and then reinforcing new habits so they stick. This mirrors how adults actually learn. Readiness comes before knowledge, and knowledge needs practice to translate into behavior.

A practical AI change management guide helps L&D teams align communication plans, training sequences, and reinforcement systems to the same model logic rather than treating each as a separate workstream.

How to measure whether a model is working

Measurement should connect behavior change to business outcomes. Course completions and attendance don’t prove adoption. What matters is whether teams use the new process or tool in real work.

A practical approach maps measurement to ADKAR’s stages. Use these as a simple scorecard to identify where adoption is breaking down and which intervention to run next:

  • Awareness and Desire: Survey data, town hall attendance, and voluntary enrollment rates show whether people understand and care about the change.
  • Knowledge and Ability: Skills assessments, manager observations, and workflow performance data show whether people can do the new work.
  • Reinforcement: Sustained adoption rates, reduced support tickets, and productivity results three to six months after training show whether the change stuck.

Organizations looking to measure digital skills gaps as part of this scorecard can connect platform metrics to role-level proficiency targets, making it easier to explain learning ROI to managers and finance teams in the same conversation.

When measurement follows the same sequence as adoption, results become easier to explain to both managers and finance.

Support organizational change with Udemy Business

Selecting the right change management model is the starting point. Executing it well requires role-specific training that builds competency and psychological readiness across every level of the organization, from leadership to individual contributors.

Udemy Business gives L&D leaders and department heads the learning infrastructure to support every stage of a change initiative, from building initial awareness with curated AI learning paths to developing real ability through practitioner-led courses. With AI-powered Skills Mapping, teams reduce hours of manual learning path curation to minutes.

Schedule a Udemy Business demo to see how structured training supports change adoption across every team.

FAQs

What is the difference between ADKAR and Kotter’s 8-Step Model?

ADKAR focuses on the individual: it asks whether each person can move through awareness, desire, knowledge, ability, and reinforcement in sequence. Kotter’s model focuses on leadership: it asks whether the organization has a plan to build urgency and sustain momentum from the top down. For AI rollouts, teams often use Kotter to align leadership and ADKAR to drive individual adoption simultaneously, since both barriers tend to appear at once.

Which change management model works best for AI adoption?

ADKAR is the most direct fit for technology and AI adoption because its five stages map to how individuals actually change behavior: understanding why the tool matters, wanting to use it, learning how, practicing until capable, and reinforcing the habit. That said, large-scale AI initiatives often benefit from pairing ADKAR with Kotter, using Kotter to build executive sponsorship and visible urgency while ADKAR handles the skill-building at the team level.

How do you measure change management success?

Measure at each adoption stage rather than tracking completions alone. Awareness and Desire are measured through survey data and voluntary enrollment rates. Knowledge and Ability show up in skills assessments and manager observations. Reinforcement appears in sustained adoption rates and productivity results three to six months post-training. When measurement follows the same sequence as adoption, it becomes much easier to explain learning ROI to leadership and finance.

What causes change initiatives to fail?

Most change initiatives fail at the individual level, not the strategy level. Leadership announces a change, communications go out, training is treated as optional, and employees never develop the confidence or capability to work differently. The frameworks that succeed treat AI upskilling roadmap development as core infrastructure and build reinforcement loops that sustain new behaviors after the initial rollout ends.

Jay Perlman, Copywriter

Jay Perlman

Người sáng tạo nội dung quảng cáo tại Udemy

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Jay Perlman là người sáng tạo nội dung quảng cáo và chuyên gia tiếp thị giàu kinh nghiệm với hơn một thập kỷ kinh nghiệm hỗ trợ các công ty khởi nghiệp và các tổ chức đã thành lập. Chuyên môn của anh trải rộng trên các lĩnh vực văn hóa, thiết kế, tiếp thị, công nghệ và trí tuệ nhân tạo, tập trung vào việc phát triển thông điệp rõ ràng, chiến lược nhằm củng cố nhận diện thương hiệu và thúc đẩy sự tương tác của khán giả.