The rapid speed of change in generative AI (GenAI), where significant advances can happen even month-to-month, means that executives must avoid obsessing over perfecting near-term use cases. Instead, they need to focus on formulating lasting guiding principles for how their company uses the technology, as it evolves, in order to meet the ultimate goal of creating a competitive advantage.

But how does a company truly generate competitive advantage when adopting rapidly changing GenAI? To answer that, BCG conducted a first-of-its-kind scientific experiment, with 750 BCG consultants using GPT-4 for a series of tasks that reflect part of what employees do day-to-day. With support from scholars at Harvard Business School, MIT Sloan, the Wharton School, and University of Warwick, the experiment looked to answer two fundamental questions business leaders face when determining their AI strategy: How should GenAI be used in high-skilled, white-collar work? And how should companies organize themselves to extract the most value from the partnership of humans and this technology?

Exploring generative AI’s ‘capability frontier’

The experiment’s results showed that when and how GenAI should be used in white-collar work depends largely on where a given task lies in relation to the technology’s “capability frontier”—either within a particular model’s competence, or beyond it. The capability frontier is largely expanding, increasing the range of competencies, but with bumps along the way where GenAI models unexpectedly fail. These fluctuations create a “jagged” capability frontier that makes it complex and confusing for generative AI users to identify whether a given task falls within or beyond the frontier, and make strategic decisions accordingly.