Why Change is the Transformation, Not Just Part of it
Based on the podcast conversation, featuring David Gumley and Poppy Lucas.
Listen to the full episode on The Backlog Podcast.
TL;DR
Organizations are investing heavily in transformation but still failing to land the change. The reason, according to change specialist Poppy Lucas of ADAPTOVATE, is that change management is treated as a bolt-on rather than a foundation.
True change is about behavior and capability, takes longer than most leaders budget for, and must be built as a continuous organizational muscle rather than a start-and-stop program. AI is accelerating both the problem and the solution.
"People aren't resisting the change. They're just overwhelmed by it. There's huge change saturation. Multiple initiatives happening at the same time without really understanding what that looks like and what that means for them."
Most organizations running transformation programs today would say they take change seriously. They commission communication plans, arrange training sessions, and assign change leads. Then the program ends, and two years later the ways of working look remarkably similar to what came before. The investment has been made. The outcomes have not arrived.
This gap between transformation ambition and transformation reality is the subject of a recent conversation on The Backlog Podcast, hosted by David Gumley, managing director at ADAPTOVATE, with his colleague Poppy Lucas, a specialist who works directly with leaders navigating large-scale organizational change. Their exchange is a useful corrective to a persistent and expensive misconception about what change management actually is.
The saturation problem nobody is measuring
The starting point of the conversation is diagnosis. What is actually going wrong right now, at this particular moment in the business cycle? Lucas is direct: the issue is not resistance. People are not digging their heels in. They are simply overwhelmed.
"People aren't resisting the change. They're just overwhelmed by it. There's huge change saturation. Multiple initiatives happening at the same time without really understanding what that looks like and what that means for them."
The distinction matters. A resistant workforce is a workforce you can engage and persuade. A saturated workforce has lost the cognitive and emotional bandwidth to take anything new on board, regardless of how well it is presented. The result is change fatigue, which is not apathy but exhaustion, and it produces the same outcome: nothing sticks.
Organizations compound this by treating simultaneous programs in isolation, each with its own stakeholder map, its own communications, and its own definition of success. The compounding effect of all those initiatives landing on the same people at the same time is rarely modeled and rarely managed. What Lucas and her team now do with clients is map the full picture first, building what she describes as impact matrices across programs, so that the experience of change from the employee's perspective becomes visible before anyone starts communicating or training.
Sixty-six days and the habit gap
There is a number that sits at the centre of this conversation and deserves wider circulation in boardrooms. Research from Philippe Lally at University College London suggests that it takes approximately 66 days for a new behavior to become habitual. That is for a simple behavior. For complex shifts in ways of working, or the adoption of new technology platforms, the timeline is longer.
Most transformation programs do not run on that timescale. They run on project timescales, with defined start dates and end dates and delivery milestones that have nothing to do with the neuroscience of habit formation. The program closes, the change team disbands, and the organization declares success at exactly the moment the behavioral shift is only partway embedded.
Lucas frames this not as a criticism of any individual program but as a structural problem with how organizations conceptualize change. The framing of transformation as something that begins and ends, rather than as an ongoing capability, is itself the root cause.
"Change should be embedded as part of a long-term inbuilt capability, not just an add-on to a program."
This requires a different kind of investment. Not more communications or more training events, but the development of change capability inside the organization itself, in leaders, in managers, and in the broader workforce. The goal is for the organization to own its own change, with external specialists playing more of a coaching and diagnostic role than a delivery role.
Leadership alignment as a prerequisite, not a formality
When the conversation turns to what good change management looks like in practice, Lucas describes a first step that many programs skip or rush: genuine alignment at the leadership level. Not alignment in the sense of having signed off on a business case, but alignment on the narrative, on the success measures, and on the honest answer to the question of why this change is happening at all.
The approach ADAPTOVATE takes with clients begins with executive-level interviews, synthesizing those conversations into a case for change, and then bringing leaders together to resolve the gaps before that narrative reaches the wider organization. If the people at the top are operating from different assumptions about why the transformation is happening, those contradictions travel downward and undermine everything that follows.
From there, the work becomes one of synthesis. Rather than managing the change for a single program, the focus shifts to building a coherent picture of everything that is in flight, and making that visible to the people being impacted. As Lucas puts it, the question that every employee needs answered is not "what is the transformation?" but "what does this mean for me?" Getting that question answered at scale, and in a way that feels human rather than corporate, is where AI is beginning to play a meaningful role.
AI as accelerant and diagnostic tool
The emergence of AI in change management is, in Lucas's view, genuinely positive, though it requires care. The most immediate application is in accelerating the production of change communications, using AI to create videos, personalized messaging, and materials that make the experience of change more tangible and relatable to daily working life. The aim is to move away from a broadcast model, where information is sent and received, toward something closer to a lived experience of the change in progress.
There is also a more diagnostic application that may prove more significant over time. One of the hardest problems in change management is knowing where adoption is genuinely not happening, before it is too late to intervene. AI-enabled analysis of ways of working, and of behavioral signals within the organization, is beginning to make that kind of early warning possible. Gumley notes the compounding dynamic: the more technology is introduced into ways of working, the more behavior needs to shift, and therefore the greater the risk that the technology itself becomes an obstacle if the change is not managed well.
"Strategy and the technology and tools behind it are all enabling us to drive change faster. But it's also one of those inhibitors to actually accelerating change if you're not understanding how it can benefit you."
The implication is that organizations introducing AI-driven transformation are doing so into an environment that is already change-saturated, and that the two dynamics interact. The answer is not to slow down the technology adoption, but to treat the change management that surrounds it with far greater rigor than has been typical.
A note for leaders
The organizations that will navigate the current pace of change most successfully are not necessarily those with the largest transformation budgets or the most sophisticated technology. They are the ones that have built change capability as a genuine organizational muscle, one that does not require an external team to activate each time the environment shifts. The question worth asking is not "do we have a change management workstream?" but "do we have the internal capability to absorb and embed continuous change?" For most organizations, the honest answer is still no.
FAQ
Why do most transformation programs fail to deliver lasting change?
The most common reason is that change management is treated as a late-stage add-on rather than a foundational discipline built in from the start. Programs tend to focus on design and delivery, with communications and training applied at the end, rather than addressing the behavioral and capability shifts that determine whether change actually sticks. Leadership misalignment and failure to account for the compounding effect of simultaneous initiatives also play a significant role.
What does "change saturation" mean, and how does it affect organizations?
Change saturation occurs when employees are subject to multiple simultaneous initiatives without a clear, unified narrative about what those changes mean for them personally. The result is not resistance but overwhelm, leading to change fatigue. People lose the capacity to prioritize and adopt new behaviors, so even well-designed programs fail to land. Organizations that map the full landscape of in-flight initiatives and manage their cumulative impact are better placed to avoid this.
How long does behavioral change actually take in an organizational context?
Research from UCL indicates that a simple new behavior takes around 66 days to become habitual. For complex organizational behaviors, technology adoption, and new ways of working, the timeline is considerably longer. Most transformation programs close before behavioral change is fully embedded, which is why so many revert. Building change as a continuous internal capability, rather than a project with a defined endpoint, is the structural response to this reality.
What role can AI play in making change management more effective?
AI can support change management in two distinct ways. First, it can accelerate and personalize the creation of communications and engagement materials, helping employees experience what the change looks like in their day-to-day reality rather than receiving generic broadcast messages. Second, it can act as a diagnostic tool, analyzing behavioral signals and adoption patterns to surface where change is not landing before it becomes entrenched. As organizations introduce more AI-driven ways of working, the discipline of change management becomes more important, not less.
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