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The impact of Artificial Intelligence within a digital sales environment: A quantitative view of salesforce automation adoption and perceived value

Cousineau, Daniel (2020) The impact of Artificial Intelligence within a digital sales environment: A quantitative view of salesforce automation adoption and perceived value. Masters thesis, Dublin, National College of Ireland.

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Abstract

Background: Artificial Intelligence is the engine driving the 4th industrial revolution and is at the forefront of global digital transformation across all industries, the global AI market is expected to be worth up to $15.7 trillion by 2030 (Brauer, 2019). Over the last decade businesses have actively invested in AI to create a competitive edge, the sales function is no exception.

Purpose: The purpose of this paper is to investigate the perceived value of AI within a digital sales environment, whether the adoption of AI is impacted by the experience of tenure of a sales professional, and will training of an AI tool influence adoption.

Methodology: A cross-sectional, research design using a quantitative survey method was used to investigate the impact of AI in a digital sales environment within the technology sector. Specifically building on the current literature in relation to perceived usefulness. The data for the quantitative analysis was collected from 41 respondents through a structured survey. The SPSS software was used for statistical analysis.

Findings: The findings of this research revealed that sales executives in a digital sales environment are adopting AI and perceiving the technology to be valuable. In addition, tenured salespeople are adopting the new AI technology, despite conflicting literature. Finally, a formal training structure is not required or has no substantial baring to improve the adoption rate of salesforce automation tools. This paper adds to the existing literature in the field and supports evidence that organisations risk future market share by not leveraging AI across the sales business function.

Item Type: Thesis (Masters)
Subjects: T Technology > T Technology (General)
H Social Sciences > HF Commerce > Customer Service
H Social Sciences > HF Commerce > Marketing
Divisions: School of Business > Master of Business Administration
Depositing User: Dan English
Date Deposited: 17 Feb 2021 17:50
Last Modified: 17 Feb 2021 17:50
URI: http://norma.ncirl.ie/id/eprint/4791

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