Every altitude is now instantly available, and what arrives at each one is the median view. The frameworks in this territory were written for a world where reaching another level took effort, so they diagnose a failure that is no longer the one people have.
The answer, in one line
Two things. Reaching any level is now effortless, which removes the constraint that used to force a choice between them, so the failure moves from being unable to reach a level to committing to none.
The standard account, stated fairly#
Big picture thinking is described in the management literature as the capacity to move between levels of detail: zoom in and zoom out, fifty feet and fifty thousand, the dance floor and the balcony. The failure named in every version is fixity. A leader gets stuck at one level, usually the operational one, and cannot see the pattern. The remedy follows from the diagnosis and is always the same: exposure, rotation, deliberate practice at the level being avoided. Woodward puts the incidence of it at around 70 per cent of senior executives, without a study behind the figure. The frameworks are set out and graded at models of big picture thinking.
None of them mentions artificial intelligence, because all of them predate it. The recent work that does address AI and strategy, in turn, never mentions altitude, zoom, balcony or levels. The two literatures do not touch, and the join is where the argument is.
What changed, first: the constraint has gone#
Reaching another altitude used to cost something. Getting to the pattern meant analysis and time. Getting to the twenty-year view meant a scenario exercise with a budget and a sponsor. That cost is what forced a choice, and the choice is what people experienced as strategic thinking.
Dashboards now render the detail continuously, forecasts produce the horizon on request, and a model will generate the pattern in seconds. Nobody is prevented from reaching any level. What has disappeared is anything that makes them settle on one, and the resulting failure is not fixity. It is altitude lock: thorough at every level, committed to none, the level of the work set by whatever output arrived last. It reads as rigour, so it is not caught.
What changed, second: the view converges#
This is the part the abundance argument misses. Romasanta, Thomas and Levina reported in March 2026 that leading models consistently recommend strategies that match current managerial trends and vocabulary rather than with the logic of the situation put to them. They named it trendslop, and their recommendation is to use these systems to expand options rather than to make choices. The wider pattern of homogenised reasoning and perspective is treated at does AI make everyone think alike.
Put the two together and the conclusion is sharper than information abundance. What is instantly available at every altitude is the median view rather than the view: the same fashionable answer at every level, and produced for your competitors at the same moment it is produced for you. A strategy any competitor's model would also have generated is not a strategy; it is a position everybody is about to hold.
Where this disagrees with the current management literature#
The 2026 work from business schools and consultancies converges on a reasonable position: analysis has become abundant, so the bottleneck moves to selection and commitment. That is correct and it is incomplete, because it treats the abundant analysis as neutral raw material. If the material converges, selection is not merely the scarce step in a familiar process. It is the only remaining source of a position that is not generic, and choosing well from a homogenised option set is a different problem from choosing well from a varied one.
It also disagrees with the altitude tradition, more politely. Exposure and rotation are the right remedy for a leader who cannot reach the other level. They are no remedy at all for a leader who reaches all three every morning before the first meeting.
What follows in practice#
- Choose the altitude before the work, in writing. One line naming the level and why. The three filters of the Altitude Lens each carry a test that can be answered in a sentence, and the instruction is to pick one and ignore the rest.
- Use the machine to widen options, not to choose. That is the recommendation of the people who found the convergence, and the same division of labour as the three terrains.
- Record what was rejected. If the distinctive part of a strategy is the part a person overrode, then it exists only where somebody wrote down what the model proposed and why it was not taken. That is the Head entry in Hand, Head, Hours, Heart applied to strategy.
- Subtract. Abundance at every level makes the discipline of removing what you track more valuable rather than less, which is the first of the three drills in the altitude toolkit.
What would change my mind#
Evidence that model-generated strategic advice diverges rather than converges once the situation is described in enough detail, which would make the trendslop finding an artefact of thin prompting rather than a property of the systems. Or a measured finding that leaders working with instant access to every level do in fact settle on one, which would make altitude lock a worry rather than a pattern. Neither exists at the moment in either direction, and this page is an argument rather than a finding.
What this does not establish#
No study has measured altitude lock, and no instrument distinguishes it from thoroughness. The trendslop article discloses no sample, measures or figures on the page read, so nothing here rests on a rate. The claim that convergence removes competitive advantage is an inference from what strategy is for rather than a measured effect.
Key sources
- Romasanta, A., Thomas, L. D. W. and Levina, N. (2026). Researchers asked LLMs for strategic advice. They got trendslop in return. Harvard Business Review.
- Woodward, I. C. with Charan, R. (2017). The three altitudes of leadership. INSEAD Knowledge.
- Kanter, R. M. (2011). Managing yourself: zoom in, zoom out. Harvard Business Review.
- Meadows, D. H. (1999). Leverage points: places to intervene in a system.
Related SuperSkills research#
- What is altitude lock
- Models of big picture thinking
- Does AI make strategy generic
- Big Picture Thinking
Evidence review · SS-2026-354 · Graded against the published rubric
Hirji, R. (2026). Big picture thinking in the age of AI. The SuperSkills evidence base, SS-2026-354. https://thesuperskills.com/research/big-picture-thinking-in-the-age-of-ai. Last reviewed 26 September 2026.
An evidence review by Rahim Hirji, not peer-reviewed research. For a material claim, cite the underlying study as well; every study here carries its own permanent link.
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