62% of enterprises plan to rely on third-party providers for Generative AI solutions and enhanced technical capabilities: WNS – Everest Group
Supported by WNS, Everest Group has launched a report titled ‘Generative AI in CXM: Assessing Enterprise Readiness for this Disruptive Transformation.’ To gauge enterprise readiness to implement generative AI within CXM operations, it surveyed CXM, digital transformation, and innovation leaders from 200 companies across North America, UK and Europe, and Asia Pacific with annual revenues of over US$ 500 million. The responses were gathered from global enterprises primarily in the telecom & media, Banking, Financial Services, and Insurance (BFSI), healthcare, retail, and technology and fast growth technology (FGT) / Hi-Tech industries.
The findings analyse the transformative potential of Generative AI for Customer Experience (CX) and the associated challenges to its adoption including robust technology infrastructure, cultural inertia, data privacy and security concerns, regulatory ambiguity, among other factors. It explores the ability for generative AI to foster innovation, increase productivity, and deliver better experiences to customers – ultimately driving business growth.
Generative AI – Potential & Key Drivers
The report found that there is a significant awareness of generative AI and its applications across text (75%), code (62%), and image generation (52%) capabilities. Notably, even less-aware enterprises acknowledge its transformative potential despite a preference for familiar applications. More than 90% of businesses recognize its high potential in text generation, with approximately 70% expressing confidence in its capabilities for code and image generation in CXM.
Beyond these creative applications, the technology equips enterprises with valuable insights for informed decision-making, product enhancements, and service improvements. Around 80% of enterprises are confident that using generative AI applications in CXM will improve operational efficiency and CSAT scores, with 70% foreseeing potential cost reductions. In fact, 75% are actively piloting, deploying, or scaling up solutions that leverage text generation capabilities.
Generative AI Deployment Roadmap
Enterprises around the globe are strategically investing substantial resources in generative AI initiatives, engaging in pilot projects, and prioritizing workforce upskilling to leverage its full potential. A notable trend emerges as 14% of enterprises intend to allocate between US$ 5-10 million for generative AI technology within the next 12-18 months. The significance of third -party providers facilitating and supporting generative AI initiatives are paramount. Enterprises seek crucial support from providers that ranges from aiding in-house technical teams in specific tasks to shaping the overall generative AI adoption roadmap.
Nearly 60% of surveyed enterprises say that the main areas of help they expect from third-party providers are supporting in-house technical teams, aiding maintenance and troubleshooting activities, and supervising the functioning of generative AI solutions. They also note technical support areas such as enhancing technological capabilities, training generative AI models on enterprise data, customizing foundational models, and creating necessary bridges with other technologies to integrate generative AI with existing business intelligence tools to provide a more comprehensive view of customer interactions. Furthermore, about 58% of surveyed enterprises say they need significant strategic support from third-party providers in activities such as designing the generative AI adoption strategy and redesigning CXM processes and customer journeys to incorporate generative AI solutions, while 52 percent say they leverage third-party providers to help implement privacy, security, and regulatory compliance measures.
Enterprise Readiness to adopt Generative AI solutions in CXM
In terms of technology readiness, at least half of surveyed enterprises believe they are ready for generative AI across parameters including availability of adequate computing power, ability to scale, and cloud-based infrastructure capacity. They attribute their readiness to either internal investments or collaborations with third-party partners.
Yet, more than 45% of enterprises say a shortage of internal technical expertise is the foremost challenge in the people part of generative AI solution implementation. enterprises currently fall short in preparedness across these technical domains. Less than half of the surveyed enterprises feel they possess adequate present capabilities for these roles, with the most significant gap observed in the case of AI/ML engineers and data scientists.
