October 05, 2021
October 05, 2021
Contributor: Gloria Omale
AI has enormous transformative potential for sales, but reaching this potential requires a firm understanding of its capabilities.
Artificial intelligence (AI) can improve sales processes, identify selling opportunities, resolve sales challenges and boost overall sales performance. Understandably, these possibilities have led sales organizations to take an active interest in AI.
The Gartner 2021 CSO Priorities Pulse Survey reveals that 88% of chief sales officers (CSOs) have already invested in or are considering investing in AI analytics tools and technologies. However, the rapid rise in AI’s popularity as a business topic, coupled with vendors trying to reposition their offering portfolio as AI, has created confusion about what it truly represents.
88% of chief sales officers (CSOs) have already invested in or are considering investing in AI analytics tools and technologies.
“AI has many subdomains that often overlap with one another in different applications, and a universal definition has not yet been accepted,” says Greg Hessong, Senior Director, Advisory, Gartner. “For business purposes, AI is a piece of software designed for specific use cases. It analyzes available data to gain understanding, then uses this understanding to help achieve the desired business outcomes.”
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Traditionally, AI was dominated by rule-based systems, but as it evolved to tackle more complex problems, machine learning (ML) developed. With ML, “telling machines what to do” has shifted to “helping machines learn what to do.” With this approach to AI, machines are able to repetitively learn from data, identify patterns and uncover hidden insights without being explicitly programmed to do so.
Identifying the type of AI technology solutions most suited to the sales organization requires a foundational understanding of its varied capabilities. Those commonly seen in AI-enabled sales technology solutions are:
“By understanding the commonly leveraged AI capabilities, CSOs will be able to effectively assess whether a proposed AI technology’s features serve their intended use case,” says Hessong.
While AI can improve business outcomes, be aware of the common challenges — such as poor use-case selection, low data quality and inadequate attention to employee upskilling — that can hinder successful implementation. If you are responsible for investing in AI, and/or implementing and managing AI capabilities, you should:
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