{"id":9817,"date":"2024-03-06T12:29:13","date_gmt":"2024-03-06T12:29:13","guid":{"rendered":"https:\/\/www.salesforce.com\/?p=9817"},"modified":"2024-03-08T12:52:37","modified_gmt":"2024-03-08T12:52:37","slug":"ai-powered-crm-research","status":"publish","type":"post","link":"https:\/\/www.salesforce.com\/eu\/blog\/ai-powered-crm-research\/","title":{"rendered":"AI Trends from 700+ Business Leaders Reveal Global Keys to Success"},"content":{"rendered":"\n

Nine out of ten leaders know a strong data strategy is critical to AI success \u2014 so why are only a third of them integrating a unified data strategy across their company? In January 2024, Salesforce commissioned Forrester Consulting to find answers to these gaps and more in the rapidly developing AI landscape. <\/p>\n\n\n\n

The research<\/a>, conducted with 773 business leaders in 14 countries, sheds light on global business decision-makers\u2019 mindsets around AI-powered CRM.  These trends prove that regardless of fast shifts in AI, there are certain foundational principles that companies must prioritise for growth.<\/p>\n\n\n\n

Before we explore these key success factors and recommendations, let\u2019s understand the current state of AI-powered CRM.<\/p>\n\n\n\n

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Keep up with global trends in AI<\/h2>\n\t\t\t\t\t\t\t

Salesforce commissioned Forrester Consulting to survey 773 global decision-makers to find out how they succeed with AI-powered CRM \u2014 and what it all means for you.<\/p>\n\t\t\t\n\t\t\t\n\t\t\t\t\t\t\t

\n\t\t\t\t\tLearn what's new<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\n\t\t
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Gaps in basic AI understanding reveal room for growth<\/h2>\n\n\n\n

The research reveals organisations worldwide are embracing AI across various CRM use cases. But, it’s not all smooth sailing. The research uncovers critical gaps that could impact the success of AI adoption in CRM.<\/p>\n\n\n\n

Here\u2019s a striking revelation: Despite all respondents making plans to adopt AI, only half were able to choose the correct definition for both predictive and generative AI when presented with both side by side. <\/p>\n\n\n\n

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Predictive AI: analyses existing data to make forecasts<\/h4>\n\n\n\n

Generative AI: creates new content based on learned patterns<\/h4>\n\n\t<\/div>\n\t
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Considering that an AI strategy likely encompasses both types of AI models \u2013  which serve specific purposes and goals \u2013 this signals an opportunity for more comprehensive education. People need to know the specific use cases each type of AI enables, the anticipated business outcomes, and how to design a strategic plan for AI<\/a> grounded in those goals. <\/p>\n\n\n\n

Another key finding is the significant gap in data maturity and readiness. While 92% of leaders emphasise the importance of a robust data strategy, only 34% claim to have one implemented across their business. Bridging this gap is crucial to using AI effectively.<\/p>\n\n\n

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While 92% of leaders emphasise the importance of a robust data strategy, only 34% claim to have one implemented across their business.”<\/p>\n<\/blockquote>\n\n