AI workflow redesign drives 1.9x revenue growth for startups, ETCIO

Startups that integrated AI into core workflows to tackle the “mapping problem” – identifying AI potential within workflows – saw nearly 1.9 times higher revenue generation compared to those that did not adopt such strategies, according to research by INSEAD and Harvard Business School.
The “mapping problem” refers to firms’ difficulty in pinpointing AI’s value in workflows and restructuring processes to achieve greater business outcomes.
The study aimed at going beyond basic AI use cases, encouraging firms to rethink workflows, products, and business models through the emerging best practices.
The field experiment involved 515 high-growth startups, half of whom were shown examples of firms that successfully reorganized with AI.
Firms exposed to real-world examples were more likely to try diverse activities, suggesting the challenge is discovery rather than access.
Reorganized firms significantly increased AI use by 44%, broadened identified use cases, completed 12% more tasks, and were 18% more likely to acquire paying customers.
Restructured startups required 39.5% less external capital, about $220,000 less on average, while maintaining employment levels, indicating efficiency gains from AI adoption.
The findings argue that focusing only on access to AI may not be sufficient; exploring use cases and rethinking workflows are essential for realizing AI’s economic potential.

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