In a recent survey conducted by CRM solution provider Workbooks, participants voiced a strong preference for human support over AI-powered solutions in CRM deployments, seemingly shedding some light on the limitations associated with the reliance on AI within CRM systems, said the company. The survey, which gathered insights from a diverse range of businesses, revealed a clear consensus among respondents: direct human contact and access to a support team during and after deployment are paramount. While AI-powered support may offer efficiency and cost-effectiveness, the survey found that direct access to a human support team during and after deployment was voted the most important kind of support, receiving an average rating of 8.4 out of 10. In contrast, access to an AI-powered support bot was rated the least important, with an average score of only 4.3 out of 10. According to executives at Workbook, these results underscore a growing disillusionment with increasingly AI-driven solutions in CRM deployments. While AI has its merits in streamlining certain processes and deriving data-driven insights, it presently lacks the empathy, understanding and adaptability inherent in human interactions, they argue. In terms of CRM deployments, a business might have unique requirements, for example, and AI bots might struggle to address the specific needs and challenges that arise during deployment. Human support teams, on the other hand, can provide the flexibility and expertise necessary to navigate these complexities. “While AI is beginning to play a role in streamlining aspects of CRM, our survey underscores the enduring value of the human element in implementing and supporting this business-critical software,” said Dan Roche, chief marketing officer at Workbooks. “People crave more than just digital assistance; they seek the irreplaceable value of human support in navigating the complexities and nuances of CRM implementations.” The survey results, said Workbook executives, simply reinforce the importance of “R” in CRM. Despite the inevitability of its importance in ongoing digital transformation, network-as-a-service (NaaS) has been adopted by only 8 percent of enterprises as of the end of 2023, according to researchers at TeleGeography. Another 8 percent were in the process of adopting, while the largest group of respondents had heard of NaaS but had not looked into it. “Customer self-service automation” and “workforce management” are the top ways AI currently is being used within organizations’ contact center platforms, named by about 50 percent of respondents to a new 8x8 survey. Moving forward, however, for those organizations just beginning to experiment with or planning to use AI, “quality management/interaction evaluation” jumps onto the top of list and “knowledge management” moves into the top three. Human Support Trump’s AI in CRM Deployments Enterprises Slow to Adopt NaaS AI Contact Center Priority Shifts EMERGENT What best describes your stage of adoption of NaaS (2023) We head about NaaS but have not done research 33% Have begun research but have not selected a service 26% Decided not to use NaaS 17% Have purchased and used NaaS solution(s) 8% In the process of adopting NaaS 8% Not familiar with NaaS 8% Source: TeleGeography; 2024 state of WAN report 10 CHANNELVISION | JULY - AUGUST 2024 Edge Computing Market Growth, 2022 to 2032 Source: Uptime Institute; 2022 How would your organization use AI within its combined unified communications and contact center platform? Source: 8x8 Source: GMI Insights; Mordor Intelligence Emerging Tech Impact Radar – Artificial Intelligence GenAI-native applications Fully autonomous driving Smart Self-supervised learning Composite Ienabled technollogies Core AI technologie $200B $175B $150B $125B $100B $75B $50B $25B $0 2022 $9B $13B $28B 2023 2028 (Projected) 2032 (Projected) Voice of employer (VoE) Out-of-the-box access to developer tools Mobile applications Speech/interaction analytics Voice of Consumer (VoC) Predictive/other analytics Recruiting/onboarding Customer journey analytics Real-time agent assistance Workforce management (WFM) Performance management Knowledge management/knowledge base Customer self-service automation Quality management/interaction evaluation 43% 41% 41% 37% 34% 33% 32% 31% 31% 27% 27% 27% 24% 22% $157B
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