Scaling Technology Without Losing the Human Side

Every transformation plan assumes it knows where the resistance will come from. It budgets for training, communications, a champion network, a change lead. All of it points downward, toward the employees who will be asked to work differently. Dr. Lindsey Ruiz has spent her career watching those plans get built, and she says the resistance that actually sinks them is sitting somewhere else entirely.

Ruiz is direct about where she stands in the current argument over what leads, the technology or the people. She describes herself as unequivocally and unapologetically pro-human, and she means it as a design order, something firmer than a soft preference.

Part of her work rests on a reframe that inverts the usual hierarchy between people and the tools they are handed. She argues the sophistication we are marvelling at is largely borrowed.

If an organization is a human system first, then a transformation is a change to that system, and the technical implementation is only one part of it. Ruiz makes a point of saying she is not against the capability. She calls her current position one of selective refusal, meaning she is interested in what the technology can do and more focused on what she does not want to lose because of it.

For executives who have attributed workforce reductions to AI, Ruiz separates her answer into the professional view, the moral one, and something closer to a personal challenge. She starts with the challenge. Leaders, she says, need to remember why they became leaders in the first place, before the conversation was corrupted into a contest between profits and people. Her point is grounded in history. The companies that became reference points for good practice got there by making people successful inside the organization so that those people would take care of the financials.

Host Mariam Ammar put the measurement problem alongside it. A large majority of organizations are funding AI initiatives, very few can point to a measurable return, and yet the cost-cutting arrives well ahead of the evidence. Ammar also named what is hardest to replace, the compounding domain knowledge a long-tenured employee holds, and the adaptability of a junior one who learns the operation by watching how people work together.

Professionally, Ruiz wants executives to return to the basics of technology adoption, and she reaches for the philosophy she associates with Steve Jobs: design the human experience first, then work backwards to the capability and the requirements. Current deployments, she says, run that sequence in reverse, and the reversal is what produces resistance.

When that happens, she says, the problem stops being tool adoption and becomes something people experience as an intrusion on their capacity to exist inside the organization authentically. At the center of her method is a distinction between two timelines. Organizations plan against one and then behave as though it is the only one that exists.

Treating change as a project is what breaks this. A technical group is brought in to orchestrate delivery, and the human element arrives later in the curve as training, with the hope that up-skilling is all anyone needed. Ruiz cites the familiar figure that seventy to eighty percent of these transformations fail, and says the failures are built into the structure. Emotional transition is not the same activity as executing a capability, so a plan that only schedules the second one will keep missing.

Traditional transformations have always had to manage what Ruiz calls the single point of failure, the individual who has accumulated institutional knowledge about how things are really done, the culture, the relationships, the politics. Organizations fear losing those people, and on large technology programs they get placed in key positions precisely because they can see gaps and frictions a regular employee cannot. They carry the risk and the gift at once.

Ruiz argues the same dynamic now runs between that person and an AI system, and that it explains the resistance among people who understand the tools well enough to think it through. The question underneath is whether to hand over what took years of meetings, emails and solved problems to acquire, knowing it may reduce their own value to the organization once it lives inside the tool.

The difference with AI, in her reading, is scale and asymmetry. Knowledge shared with a colleague stays in the human system. Knowledge absorbed by a tool does not, and the sense of lost meaning is correspondingly larger. Her recommendation is not to argue people out of that feeling but to use it. Reaction and opposition are data about where the organization actually is, and discarding them removes the only reliable signal a program has.

This is the part of the conversation that departs most sharply from standard change practice. Resistance is normally addressed at the employee level, on the assumption that this is where fear concentrates, and the response is pragmatic work to get people on board. Ruiz says the assumption is wrong, and that an organization has to be segmented so that fear can be addressed as it actually appears at each layer.

At the leadership layer the fear takes different forms. Losing control. Losing power. Being seen not to know where the organization needs to go. Holding a conflict of interest between departments that are not aligned, or between leaders who do not like each other, which then ripples downstream into the cultures they each run. Across her projects, Ruiz names this as the single factor that determines whether a large transformation succeeds or fails.

She describes the mechanism in detail, and she expects it to be the least popular thing she said. Leaders are appointed to these programs with incentives attached, whether status, more leadership, bonuses or survival, and the pressure on them to deliver is considerable. Unless the individual has enough self-awareness and foundation to carry that weight, the initiative gets eaten by the egos that show up in moments of fear and uncertainty. The result she has seen is an inversion nobody plans for, where the employee base turns out to be more mature than the leadership, and the program ends up leaning on employees because the leaders cannot absorb the complexity along with the daily pressure to spend less and finish sooner.

Asked how she finds the real friction points in a company she has not spent a decade inside, Ruiz offers no proprietary instrument. She asks for a cross-section of the organization to talk to, so she can hear how the employee, the middle manager and the executive are each thinking about the same transition, and she puts effort into that early. Interpretation, as she sees it, is the whole job. A second-hand account of how people feel has already been translated by someone else, and she needs it firsthand in order to convert it into a roadmap and a credible forecast of where the program will hit trouble.

Uncertainty does not disappear under this approach. Some of it, she says, can be anticipated and removed, and the rest is the surprises that arrive anyway, which is a different thing from being unprepared. What the method depends on entirely is trust, and when Ammar asked how she builds it, her answer was two words. Integrity and agency.

She distinguishes that from a strong first impression, which she thinks anyone can produce. Trust is what accumulates when someone opens up to you and you are consistent afterwards, including when the news is bad. Leaders often ask her how to phrase a difficult message, or which parts to leave out of a communication. She tells them the editing is transparent to everyone receiving it.

The alternative she recommends is plainer than most communication plans allow. Tell people there is a situation. In her experience they respond by wanting to be part of the solution, where being managed around produces the opposite reaction. The same test applies to executive sponsorship, which she says is not a leader saying yes to AI in a meeting and then behaving differently in the office. It is congruence, and her phrase for what it requires is putting skin in the game.

Ruiz cautions against reading a list like this as a checklist. In her framing the elements are real, but they operate in a context that is more organic and unexpected than most executives would like, and a roadmap has to leave room for adapting itself along the way.

If the resistance that matters sits at the leadership layer, then the work is not primarily technical, and it cannot be delegated to whoever holds the transformation title. Ruiz puts the obligation back where the fear is.

Asked for one thing listeners should keep, Ruiz did not name a practice or a framework. She wants people to remember who they are, as a daily exercise of reconnecting with the parts of themselves that make showing up to work, and to a life, mean something. She is skeptical of how the pro-human conversation currently sounds, calling a lot of it marketing-ish, and she treats the real version as closer to survival than to positioning.

A transformation that protects the financials and damages the human system has not delivered anything durable, because the human system is what executes every quarter after this one.