AI is rapidly compressing coordination and decision — making inside companies, shortening product cycles and enabling strategy decks that once took weeks to be produced in hours. That speed matters because it can erase the productive disagreement — competing interpretations and unresolved trade — offs—that historically drives breakthrough ideas and long-term competitive advantage. Builders, product teams and decision designers are the most immediately affected: they gain execution speed but face a growing risk of premature consensus.
Boards and product teams are increasingly favoring speed. Cross — functional alignment, long a bottleneck for execution, is becoming easier as tools and workflows accelerate communication and reduce gatekeeping. The author notes a concrete change in how decisions are produced: AI now compresses interpretation, synthesis and decision into a single step. When disagreements arise about product direction, market entry or resource allocation, AI can rapidly summarize competing views, integrate data and generate a balanced recommendation that previously took days to produce.
For decades firms invested in eliminating operational and coordination friction because inefficiency is costly. Those investments have been accelerated by AI capabilities — matching, summarization and recommendation — that make previously slow alignment processes occur in minutes rather than days. The result is cognitive: not all friction is waste. Productive tension — heterodox perspectives, incompatible framings and unresolved arguments — helps surface original ideas and unconventional approaches that pure efficiency can obscure.
The trade — off has real consequences for innovation and competitive position. Julio Mario Ottino argues that while speed and smoother alignment improve execution, they can erode the cognitive friction that produces breakthrough thinking. Organizations that agree too quickly risk converging on conventional logic and becoming fast followers of yesterday’s ideas instead of creators of what comes next.
That tension points to practical steps for teams using AI. When systems produce instant, consensus — seeking recommendations, they can inadvertently short — circuit deliberation on trade — offs and novel angles. Treat AI-generated syntheses as inputs, not endpoints — especially for high-leverage choices about product strategy and market positioning. Organizations should balance efficiency gains with explicit processes that preserve dissent, surface heterodox perspectives and allocate time for creative debate to ensure rapid execution does not come at the cost of future innovation.
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