Performance-Based Pay Increases Managerial Use of AI in Decision-Making

Linking managerial pay to performance increases AI use in decisions. Framing AI as a collaboration of data and human expertise boosts trust and adoption.

Linking Pay to Performance Increases AI Usage in Managerial Decisions

Artificial intelligence has advanced significantly and is transforming business decision-making. However, not all managers use AI tools consistently. Recent research identifies two key factors that encourage greater AI adoption in decision-making: the structure of managerial pay and how AI is presented.

Contrary to older studies suggesting that performance-based incentives reduce reliance on algorithmic advice, new findings show the opposite. Managers who receive performance-linked pay are more likely to use AI in their decisions compared to those on fixed salaries. Additionally, AI framed as combining data with human expertise gains more trust and usage than AI presented as purely algorithmic.

Revisiting Old Assumptions

Earlier research from the 1980s and 1990s introduced the idea of "algorithm aversion," where incentivized managers preferred relying on their own judgment over algorithmic recommendations. These studies concluded that performance incentives could backfire by discouraging AI use.

Given the evolution of AI tools, this assumption warranted reevaluation. Recent experiments led by researchers at the Vienna University of Economics and Business, including Martin Wiernsperger, assistant professor at Cornell's SC Johnson College of Business, challenged this view.

Designing the Experiment

The study involved about 1,500 participants from Austrian universities. Subjects were randomly assigned to one of nine groups based on two factors: pay structure (fixed, performance-based, or tournament-style) and AI framing (no AI advice, AI advice, or human-AI combined advice).

Participants estimated nightly rental prices for 10 Airbnb listings in Vienna. Those in AI groups made two estimates: one without and one with AI input. This setup measured how much participants weighted the AI advice in their final decisions.

Key Findings

Participants with performance or tournament incentives relied significantly more on AI advice than those with fixed pay.

Trust in AI increased when it was described as integrating human expert knowledge alongside algorithms.

Using AI advice improved estimation accuracy across the board compared to no AI assistance.

These results suggest that linking compensation to performance encourages managers to lean on AI tools rather than reject them. The framing of AI also plays a crucial role in building trust and increasing usage.

Implications for Business

Companies aiming to boost AI adoption in their decision-making processes should consider how they structure incentives and communicate about AI. Performance-based rewards can motivate managers to use AI effectively. Meanwhile, presenting AI as a collaborative tool that blends data and expert insight can reduce resistance.

For managers and organizations looking to improve their AI skills, exploring training options can be beneficial. Platforms like Complete AI Training offer courses tailored to different skill levels and roles.

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