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A new exploration by the Financial Times and MIT Technology Review delves into the complex relationship between generative AI and global economic productivity, questioning whether the technology can deliver on its promise of significant gains.

Richard Waters (FT) and David Rotman (MIT Technology Review) highlight the inconsistent application of AI across industries, noting that while some sectors, like software development via AI coding assistants, have experienced rapid transformation, many organizations are struggling to realize a return on their AI investments. Some studies indicate a significant percentage of generative AI initiatives yield no measurable benefit.

The discussion echoes the ‘productivity paradox of IT’ from the 1990s, suggesting that realizing the full potential of AI requires significant organizational adaptation, including infrastructure upgrades, process redesign, and workforce retraining.

While recent productivity figures are promising, attributing these gains directly to AI remains challenging. MIT economist Daron Acemoglu suggests that the productivity increases may be more modest and take longer to materialize, citing a focus on AI applications irrelevant to key business sectors.

The report emphasizes that realizing AI’s potential to boost productivity relies on using the technology to enhance human capabilities and create novel job roles, rather than solely focusing on cost reduction. The long-term economic impact of AI hinges on its capacity to fundamentally reshape work and drive new value creation.