AI is eating change management  

Change management is a multibillion-dollar industry built on the fundamental claim that most people dislike change, and that someone needs to manage that resistance. 

But after decades of organizational theories and billions in consulting fees, the industry does not work as promised: change management projects have a failure rate of around 70%. There’s a reason no one asked McKinsey or any other leading consulting firm to run DOGE.  

As enterprises large and small grapple with the wholesale transformation that will be wrought by the rise of artificial intelligence, it’s time to face an uncomfortable truth: Change, especially today, doesn’t happen in neat phases. It’s cyclical, unpredictable, and requires constant adaptation.  

The Old Model Never Worked–But It Especially Doesn’t Now  

Traditional change management follows a predictable model. Under investor scrutiny—or to avoid it—the CEO announces a transformation is coming. Consultants conduct surveys, present slides at workshops, and create communication plans to deal with signs of revolt. Success gets measured by stakeholder-focused metrics like “adoption rates,” and KPIs like “number of training programs deployed.” It’s an industry that prioritizes rationality at the expense of inspiration and serendipity. 

AI will be the force that kills this episodic approach. First, the tech is already moving too quickly for rigid approaches to be relevant. Second, AI requires significant amounts of training and customization to be effective in most organizations, rendering a “one-size-fits-most” approach obsolete. And finally, the human side of AI-driven change is more complicated than a standard reorganization—because AI anxiety strikes at the heart of what is human, and what sort of careers we and our children will have.  

A Tale of Two Companies 

In our recent work inside companies that are adopting new AI tools and workflows, we’ve seen the potential for a new way of working. Instead of a traditional change management approach, smart leaders today are understanding—and embracing—that change in the era of AI is often organically driven by shifts brought about by AI eureka moments. Competitive advantage is built not by how quickly you move humans through a change program, but how seamlessly your organization’s source code—the unique combination of people, process, and technology—rewrites itself in real time.

A Tale of Two Companies

Consider a recent tale of two companies.  

First, fintech company Klarna’s recent initiative to automate its customer service operations using generative AI. The company publicly claimed that its AI tools were performing the work of 700 full-time agents, leading to a dramatic reduction in hiring and headcount. The rollout was managed through a centralized, top-down approach: executive-led messaging, internal dashboards to track AI performance, and a focus on cost savings and productivity metrics. But the transition sparked internal unease and external criticism, and Klarna quietly began rehiring human agents within the year. The AI may have delivered efficiency on paper, but the rigid implementation and lack of human-centered change management eroded trust, both inside and outside the company. 

Contrast that with one of our clients—a multinational pharmaceutical organization that took a radically different approach. Rather than relying on static KPIs and sequential rollouts, they used using AI to surface real-time insights from employee sentiment, social media behavior, and internal feedback loops. These insights continue to inform tailored interventions across roles and geographies. AI-powered chatbots enable employees to access personalized resources on demand, while leaders use behavioral analytics to trigger timely nudges and adapt strategies instantly. The result has been a more agile, inclusive transformation—where change has been continuously shaped by how employees are actually working.  

How Organizations Can Stay Ahead 

In this new world, “best practice” changes from week to week. But the most important trends we see in recent, successful transformations are:  

First, build a nonlinear approach. When it comes to generative and agentic AI, you often don’t know your best use cases until you experiment. Embrace the 3-D problem solving that comes with transformation by moving to organized but flexible processes that account for two-way feedback.  

Second, create pilots. Understand that new processes, technologies, and workflows will work differently for each organization and team. Select specific organizational areas for focused experimentation and training. Give them deadlines and establish feedback loops between pilot participants and the transformation team. Then, scale successful approaches across the organization using champions as advocates for the technology and its impact.  

Third, work to understand and activate teams with precision. Identify specific employee categories to play a role in championing change. Every organization has a group of early adopters—the “weekend warriors” who explore AI on their own time. And every organization also has laggards—those who will require structured protocols and personalized training plans to implement new systems. Focus your communications—and your expectations—by identifying each group and understanding the different needs it requires.  

Finally, empower leaders. Measure success not by who attended the meeting or did the training, but by who’s actually creating new pathways in process or technology. Encourage those leaders, from the CEO down, to show how they use AI tools, and arm with appropriate nudges for staff.  

According to the Boston Consulting Group, the small minority of companies already operating at this level are realizing 1.5× revenue growth, 1.6× shareholder returns, and 1.4× ROI. 

The goal is improving organizational metabolism so your organization stays healthy, instead of contracting a disease that needs treatment. The business model for change management consulting may shift to something far more organic: Enabling leaders to role model and guide, designing teams built for experimentation and imbuing organizational culture with a growth mindset. 

Adaptability counts most

Corporate America rewards risk-taking and stories about explosive growth, rapid innovation, and bottom-line-enhancing layoffs. But it’s adaptability that will count most in the AI era, and continuous improvement is what will deliver it. 

Organizations that continue to rely on traditional change management consultancies are not just wasting money—they’re actively handicapping their ability to compete in an increasingly dynamic business environment. Consultants can either change— the irony!— or go down with their ship.