In this paper the impact of ability and learning potential on incentive contracts is analyzed. A central feature of the model is that the true ability will not be revealed. The learning potential of an agent is modeled as the magnitude of impact on the agent's expected ability that learning-by-doing has in a given task. Absent a managerial labor market, depending on an agent's learning potential, a monotone or non-monotone pay structure may be optimal. The second important result is that using agents' ability distributions as inputs to information systems, higher learning potentials lead to less costly information systems, i.e. actions can be implemented at lower costs. Additionally, it is proven that the criteria cost minimization and value maximization are equivalent in the model's context.
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