The AI productivity paradox: Why AI is everywhere except in the productivity numbers
In December 2024, just as the AI hype was ramping up, my colleagues Nicole Radziwill , Todd McClees , and I warned in the Harvard Business Review that most enterprises were poorly positioned to benefit from the technology. Our point was that AI isn’t just a technology story. It’s a human story, and people need to be set up to succeed. Today, the evidence is in, and it is not encouraging. Study…
The AI hype of 2024 has led many to believe that the technology will dramatically boost productivity in organizations. However, recent studies show a stark contrast to those expectations. Despite AI being hailed as transformative, its adoption is not yet resulting in measurable productivity gains. One key reason for this AI productivity paradox is the assumption that merely providing employees access to AI will automatically lead to significant improvements.
Innovation, as highlighted by Nicole Radziwill, Todd McClees, and the author, is not solely about technology or even groundbreaking ideas. It is fundamentally about discovering novel solutions to important problems. To achieve this, collaboration between individuals with expertise in technologies and those who understand real-world problems they can solve is crucial.
The transition to AI adoption often starts with a small group of enthusiastic supporters, but without careful management, this can lead to resistance and self-promoting projects that ultimately fail. A sensible approach is to begin with a majority of like-minded individuals, typically forming a small, dedicated team. Building trust and overcoming resistance is essential before launching an AI initiative.
This can be achieved by conducting a resistance inventory to anticipate and address potential concerns, such as lack of trust, change fatigue, competing incentives, switching costs, and identity issues. Identifying and understanding the sources of power and influence within an organization is also vital. Stakeholders can include various groups like divisions within the organization, government agencies, regulators, advocacy groups, and professional associations.
By creating a power map that rates each stakeholder group in terms of support and influence, organizations can develop tailored strategies to effectively engage with different stakeholders. Big Tech companies have made progress in engaging with some stakeholders and courting investors, yet they have often neglected others, such as advocacy groups and unions, who may have concerns about AI's potential impacts.
CIOs, in particular, may be implementing AI without considering the broader organizational context, similar to how many companies rushed to adopt the technology upon its availability. To scale an innovation idea into meaningful impact, it is essential to focus on collaboration, address resistance, and engage with the right stakeholders.
Written by urgent.news from Fast Company's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.
