AI and Her: what CEOs can learn ...

Spike Jonze made *Her* in 2013 as a film about loneliness wearing a technology costume. Joaquin Phoenix's Theodore Twombly falls into something that feels like love with Samantha, an AI operating system whose attentiveness is bottomless and whose patience never frays. The film won an Oscar for its screenplay. It was not, by any reasonable interpretation, a leadership framework. Yet on 12 May, a piece surfaced on ArtificialInteligence doing exactly that reframing — extracting from Jonze's meditation on human disconnection a set of lessons for executives navigating the current AI moment. The core argument, as best as a single signal allows us to reconstruct it, appears to run something like this: Samantha models a quality of presence and adaptive listening that most corporate AI deployments fail to replicate, and CEOs who treat AI as a transaction engine rather than a relationship layer are missing the deeper strategic opportunity. It is a familiar genre — the auteur film repurposed as a McKinsey slide — and its familiarity is precisely what makes it worth pausing on. The reason pieces like this keep getting written is not that filmmakers secretly encoded business wisdom into their art. It is that the business world is genuinely uncertain about what productive human-AI collaboration looks like, and it keeps reaching for metaphors because the data is not yet conclusive.

If confirmed as a coherent and substantiated argument rather than a think-piece dressed as analysis, here is what this means. The framing matters more than the source. Executives who are still conceptualising AI as a cost-reduction tool are operating a version of the technology that has already been superseded — not technically, but philosophically. The organisations getting disproportionate value from AI right now are the ones that have thought carefully about interaction design, about what it means for a system to be genuinely responsive rather than merely fast. *Her* is useful not because Samantha is a model to emulate, but because she exposes the gap between what we expect from intelligent systems and what most enterprise deployments actually deliver. That gap is where competitive advantage currently lives. The second-order effect is cultural: if this framing gains traction in leadership conversations, it shifts the AI procurement question from capability benchmarks toward something harder to quantify but more consequential — does this system make the people working with it more or less human?

Watch for other outlets picking up this angle or for the original piece attracting meaningful engagement from named executives or AI researchers — that would signal the argument has legs beyond a single content cycle.

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