Artificial intelligence driven sales-force optimisation: Enhancing productivity, forecasting and customer engagement

Abstract

This paper reviews the expanding literature on AI’s role in sales-force effectiveness, spanning lead generation, customer relationship enhancement, forecasting accuracy, personalised selling, team management and emerging applications such as generative artificial intelligence (AI) and reinforcement learning. Building on empirical studies that demonstrate up to 30 per cent gains in lead qualification, 20 per cent improvements in forecast accuracy, and notable productivity increases from AI-driven coaching and dynamic pricing, it highlights technological capabilities and ethical challenges around data quality, algorithmic bias and governance. Managerial implications emphasise the need for robust data infrastructure and phased AI deployment via pilot projects, cross-functional collaboration and continuous upskilling; they also underscore the importance of explainability and human–AI collaboration to maintain trust and strategic alignment. Concluding with practical guidance, the paper argues that organisations integrating AI responsibly, balancing innovation with ethical oversight, will secure competitive advantages, while setting an agenda for future research on sustainable, human-centred AI in sales management. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.