Why Executives Overestimate Technology and Underestimate People

One of the things I spoke about in my previous podcast, The Illusion of Adoption Metrics, was how organisations often convince themselves that activity equals adoption. If users are logging in, completing fields, attending training sessions, and generating reports, leadership naturally assumes the transformation is working. But underneath those metrics, there is often a much deeper issue hiding in plain sight — and that issue is the relationship businesses have with people during change. Because if you spend enough time around large transformation programmes, especially in the Salesforce world, you start noticing a pattern. Organisations are incredibly willing to invest in technology. They will invest in platforms, integrations, automation, AI functionality, consultants, architects, and redesign projects without hesitation. Yet the moment the conversation turns toward training, enablement, behavioural support, reinforcement, or long-term adoption, the energy in the room changes completely. Suddenly budgets become tighter. Questions become sharper. Leaders start asking whether all of this support is really necessary. And I think that tells us something very important. Most organisations still fundamentally believe that technology is the primary driver of transformation, while people are treated as secondary considerations that simply need to “catch up” once the system is live. The assumption is often that if the platform is good enough, modern enough, or intuitive enough, then users will naturally adapt themselves around it. But human beings simply do not work that way. Technology is predictable. Human behaviour is not. That is why executives so often overestimate technology and underestimate people. Technology feels measurable. It feels controllable. You can see it being built. You can demonstrate features in a boardroom. You can show implementation milestones, delivery plans, and architecture diagrams. You can physically point to progress. Human adoption, on the other hand, is far more difficult to measure because it is emotional, behavioural, and deeply connected to confidence, habits, trust, and workplace psychology. The irony is that the human side of transformation is usually more important than the technology itself, yet it receives a fraction of the attention. I have seen organisations spend months designing technically impressive Salesforce environments. Endless workshops take place around future-state processes, automation opportunities, reporting structures, AI roadmaps, integrations, page layouts, and governance models. Huge amounts of intellectual effort go into building something strategically powerful. But then, somewhere near the end of the project, there is almost a sudden realisation that users will need training. As though adoption is simply the final task before go-live rather than one of the central pillars holding the entire transformation together. And this is where so many businesses misunderstand the role of training. Good training is not simply about showing users where buttons live or explaining which fields need to be completed. Real enablement is far more complex than that. A good trainer is helping people rebuild confidence inside a completely new operational environment. They are helping users navigate uncertainty. They are helping experienced employees adapt long-established habits. They are helping individuals move through the uncomfortable feeling of no longer being experts in their own daily work. That emotional dimension is almost always underestimated by leadership teams. When executives look at transformation, they often see opportunity, efficiency, innovation, and strategic improvement. But users frequently experience something very different. They experience disruption. They experience pressure. They experience the fear of making mistakes publicly. They worry about performance targets. They worry about looking slow or incompetent in front of colleagues. In some cases, they worry about whether the technology is quietly preparing to replace parts of their role altogether. These concerns are rarely spoken about openly during projects, but they exist underneath the surface of almost every major transformation programme. You can often feel it during training sessions. Some users become quiet and withdrawn. Others become defensive or overly critical. Some disengage entirely, while others appear frustrated by seemingly small details. Leadership teams sometimes label these individuals as resistant or difficult, but many of them are simply trying to protect their confidence and stability inside an environment that suddenly feels unfamiliar. Interestingly, the most experienced employees can sometimes struggle the most during large system changes. That sounds counterintuitive because we naturally assume experienced staff will adapt quickly, but experience is often built on years of operational muscle memory. Confidence comes from repetition. Speed comes from familiarity. Reputation comes from expertise. When a business introduces an entirely new system, especially one with redesigned processes, it can temporarily destabilise the very people the organisation depends on most heavily. And this is where the gap between leadership perception and operational reality starts becoming dangerous. Executives usually experience technology through dashboards, demonstrations, strategy meetings, and implementation updates. Users experience technology through friction. They experience it through additional clicks during busy days, confusing processes under pressure, unclear workflows, and systems that may technically make sense but operationally feel unnatural. Leadership sees transformation; users often feel interruption. That disconnect matters enormously because once leadership becomes detached from the day-to-day operational experience of users, organisations begin making very flawed assumptions about adoption. Silence becomes mistaken for success. Attendance becomes mistaken for engagement. System access becomes mistaken for confidence. Completion rates become mistaken for capability. But users are remarkably good at surviving systems they do not truly believe in. That is one of the hidden truths of enterprise technology. Employees adapt just enough to function. They learn enough to avoid problems. They complete the minimum required processes. They attend the sessions. They log into the platform. They follow enough rules to appear compliant. From a reporting perspective, everything can look perfectly healthy while frustration quietly builds underneath. This is exactly why metrics alone are so dangerous, and why the previous podcast about adoption metrics connects so closely to this conversation. Metrics can show activity, but they cannot fully show confidence. They cannot fully show trust, usability, emotional buy-in, or long-term behavioural commitment. Those things are much harder to measure, yet they are often the true indicators of whether a transformation will succeed over time. What makes this even more interesting is that organisations frequently interpret technological complexity as maturity. The more automation, customisation, and functionality added into a platform, the more impressive the system appears at leadership level. But users experience that complexity very differently. Every additional process, every extra screen, every mandatory field, every layered workflow adds cognitive weight to somebody’s day. Over time, that creates what I often describe as cognitive debt — not technical debt, but human mental overload created by increasingly complex operational environments. And the dangerous thing about cognitive debt is that it accumulates quietly. Leadership teams may celebrate sophisticated functionality while users slowly become exhausted by the sheer effort required to navigate the platform efficiently. In those moments, people naturally begin creating workarounds. They revert to spreadsheets. They avoid fields that feel unnecessary. They bypass processes they do not fully understand. None of this happens because users are lazy or unwilling. It happens because human beings naturally move toward reducing friction in their working environment. This is precisely why good enablement professionals are so important. The best trainers sit between two worlds. They understand the technology, but they also understand human behaviour. They recognise where processes feel unnatural. They notice where terminology becomes confusing. They identify where workflows clash with real operational reality. Often, they are spotting problems long before leadership teams become aware of them. More importantly, good trainers create psychological safety. That is something businesses massively underestimate. People learn differently when they feel safe to ask questions. They absorb information differently when they are not worried about judgement or embarrassment. Confidence changes learning outcomes dramatically. A stressed or overwhelmed user processes information very differently to somebody who feels supported and psychologically secure. Yet many training plans are still designed almost entirely around content delivery rather than behavioural readiness. Organisations proudly announce that training has been delivered because sessions took place, recordings were uploaded, and documentation exists. But none of those things automatically mean people feel capable, supported, or confident in their new environment. And honestly, this is why I believe training should never be viewed as the final phase of a project. Good trainers influence projects long before delivery begins. They challenge process design. They identify operational risks. They ask whether workflows actually make sense for real people under real pressure. They bring a perspective that technical teams sometimes overlook because they are constantly thinking about the day-to-day human experience behind the system. Questions such as, “Will users realistically understand why this matters?” or “Does this process align with how people actually work?” are often just as important as technical design decisions themselves. Because ultimately, implementation and integration are not the same thing. Implementation is deploying technology. Integration is embedding behaviour. One is technical; the other is human. And human integration takes significantly longer than most businesses expect. It requires reinforcement, communication, leadership visibility, coaching, patience, and operational honesty. It also requires organisations to accept that when users struggle, the problem is not automatically the users themselves. Sometimes the process is flawed. Sometimes communication was poor. Sometimes the rollout was rushed. Sometimes the design ignored operational reality. And sometimes businesses simply underestimate how exhausting behavioural change can be for large groups of people trying to maintain performance while simultaneously relearning how they work. I think this conversation becomes even more important now that AI is being attached to almost every business strategy discussion. Once again, organisations are becoming fascinated by technological capability. AI copilots, automated summaries, predictive recommendations, and intelligent workflows all sound incredibly attractive. Some of them genuinely are valuable. But underneath the excitement, the same foundational issue still exists. If users already struggle with trust, confidence, usability, process understanding, or platform engagement, layering AI on top does not automatically solve those problems. In many cases, it amplifies them. Businesses cannot automate their way out of weak adoption foundations. And perhaps that is the uncomfortable question many organisations now need to ask themselves. Are they investing in technology because it genuinely helps people work better, or because technology feels easier to buy than behavioural change? Because behavioural transformation is difficult. It requires leadership maturity. It requires consistency. It requires humility. It forces organisations to acknowledge that successful transformation has never really been about systems alone. It has always been about people. Technology is simply the tool. The organisations that truly understand this usually behave very differently during projects. They do not treat enablement as a side activity. They do not see training as a support function that happens near go-live. They recognise that confidence, clarity, usability, communication, and reinforcement are strategic business priorities because they understand something many businesses still overlook: People are not the barrier to transformation. People are the transformation. And interestingly, when organisations genuinely invest in people properly, the technology suddenly starts performing better as well. Adoption improves. Data quality improves. Process consistency improves. Reporting improves. User confidence improves. Return on investment improves. Not because the technology changed, but because the relationship between the people and the technology changed. That may actually be the most important lesson in all of this. Executives often believe transformation is primarily about systems, platforms, and innovation. But the longer you work around large implementations, the more you realise successful transformation is really about understanding human beings — how they think, how they learn, how they react to pressure, and how they adapt to change. Technology simply exposes how well an organisation understands its people. And perhaps that is the real continuation of the conversation from the previous podcast. Adoption metrics can only ever show visible activity. They cannot fully show confidence, trust, emotional engagement, or belief in the system itself. Yet those human factors are often the true foundation of long-term success. So maybe the better question for leadership teams is no longer, “Did we implement the platform successfully?” Maybe the real question is this: “Did our people genuinely become stronger because of it?” Because if the answer to that question is no, then eventually even the best technology in the world will begin struggling under the weight of human disengagement.