Analyzing Trends

In creative work today the question has shifted. It is no longer “Do we have enough ideas?” but “What are humans for, now that ideas are cheap?” AI can draft credible copy, sketch campaign concepts, and outline product features in seconds. In response, organisations are doubling down on visible rituals of creativity: workshops, “human-only” ideation sprints, and whiteboards thick with words like “delight” and “joy.” The point is to prove something uniquely human is still happening in the room. Too often, though, these sessions reward performance over judgement and slogans over the one thing that might actually help, the worry someone hesitates to say out loud.That tension sits at the heart of Story Systems and Cultural Research. We treat brainstorming not as the main event but as the opening move. Generating options only matters if you put them under pressure, through mapping, scenario testing, and deliberately designed dissent, to see how they hold up against incentives and constraints. The work is not producing more “territories” but finding which stories are actually shaping what happens and which are mere decoration. That demands conditions where dissent can survive and where discomfort counts as data. In a world where AI supplies endless surface variation, Story Systems focuses on what is harder to automate, designing conversations and research practices that change what a group can see and what it will do next.

On the photobooth’s 100th anniversary, its compact grammar of a fixed frame and timed shutter within a curtained chamber still teaches how machines choreograph behavior. Narrative intelligence decodes that language, turning affordances into hypotheses designers can test in the wild. If we want identity systems that permit verification without erasing improvisation, we must read these grammars and prototype the social scripts they encourage. What machine language are you listening to?

Younger generations find rites of passage unfulfilling because public life has thinned, connection is often performed, and identity work has shifted into private rehearsal that turns anxiety into a shared code. By framing culture as a living story system, we can see where meaning is forming and design credible thresholds for belonging and responsibility. The result is clearer direction in ambiguous times. Solutions to these complex challenges require an open and layered approach to analyzing how culture is changing. Sensemaking that resists conclusions and opens up more questions and connections between points within the cultural system.

We are revisiting the 2025 Trend Themes with a clearer lens. Flexibility became a perk for the few, not a standard for all. Big donors shaped politics while calling it populism. AI fakes moved from novelty to everyday content. Living alone became something cities must plan for. Cities focused on what was easy to count, while people demanded proof for every claim. October made this obvious: donors pushed court outcomes, newsrooms argued over how to label AI content, housing costs dominated local elections, and outside audits found emissions that city dashboards missed. These are not separate stories. They are parts of one system that now runs on constant pressure, not on quick recoveries.The intersections are plain. Hybrid work helped women where it lasted, while return to office policies hurt caregivers. Class decided who got paid leave and who kept real flexibility. Race and immigration status concentrated risk in frontline jobs. Age and access decided who smart tools helped and who got left out.This needs a different kind of foresight. Treat trust like infrastructure. Attach proof to every claim. Make governance opt in with clear consent, short data windows, and real ways to appeal. Design for belonging so solos, older adults, and young people in fractured media worlds can meet the rest of the city. Pair story with statistic. Set early warning signals. State what is known and what is not so choices in 2026 are clear and defensible.

When Amazon announced plans to replace more than half a million jobs with robots, most reactions focused on automation and job loss. The deeper story is about how such decisions reshape the systems that define work itself. Automation changes not only what people do but how they relate to space, technology, and one another. Every change in workplace design, from surveillance dashboards to wellness pods, carries an underlying logic about trust, power, and purpose. To understand these changes, it helps to look beyond the headlines and ask what stories, assumptions, and structures are shaping them.
A causal layered approach makes this possible. It starts with visible trends like return-to-office mandates and AI monitoring, then moves down through the systems that sustain them, the worldviews that justify them, and the deeper myths that give them meaning. This layered way of seeing shows how automation mirrors broader cultural choices about fairness, belonging, and control. It invites us to imagine multiple futures for work, some built around compliance and measurement, others around collaboration and care. Seeing these layers together gives a fuller picture of what is really being designed when machines and people share the same space.