Generative AI in CXM: How Enterprises Are Adapting

Generative Artificial Intelligence (Gen AI) has sparked a wave of excitement and curiosity among enterprises seeking to harness its transformative potential within Customer Experience Management (CXM).

To gain a deeper understanding of the current state of organizational readiness for adapting to Gen AI, Everest Group, supported by WNS, conducted a comprehensive survey involving CXM, digital transformation and innovation leaders from 200 companies across North America, the UK, Europe and Asia-Pacific. The survey delves into crucial aspects such as technology, data, people and processes that impact successful Gen AI integration.

This blog dissects the survey findings and sheds light on organizational challenges and opportunities in the Gen AI journey.

1. Empowering Tech Infrastructures for Gen AI Success

   Enterprises are making significant strides in their technological preparedness for Gen AI. Adequate computing power, scalability and cloud-based infrastructure capacity are seen as critical determinants of success. Yet, the journey is not without its hurdles. Despite active investments in in-house computing power, concerns persist, underscoring the imperative for collaboration with specialized AI firms.

2. Navigating the Data Quality Conundrum

   While enterprises showcase commendable capabilities in data storage, privacy and security, the Achilles' heel lies in the availability of high-quality training data. Nearly 40 percent express reservations about the quality of data for training AI models, highlighting a significant bottleneck in Gen AI adoption.

3. Cultivating a Hybrid Workforce for Gen AI Solutions

   The shortage of internal technical expertise is a glaring challenge in the human dimension of Gen AI solution implementation. Roles such as AI / Machine Learning (ML) engineers and data scientists are particularly in demand, highlighting the need for a workforce with hybrid skills that bridge the gap between specialists and developers.

4. Overcoming Process Hurdles for Gen AI Integration

   Regulatory compliance, cultural inertia and redundancy measures emerge as key process readiness challenges. Understanding and adhering to regulations is paramount, with over 70 percent of Banking, Financial Services and Insurance (BFSI) and healthcare enterprises citing regulatory compliance issues as a major challenge to embracing Gen AI.

5. Confronting Financial & Change Management Challenges

   Financial considerations are a pivotal aspect. The landscape of expenses, encompassing data storage, processing and accelerated computing infrastructures, demands strategic navigation. Simultaneously, change management emerges as a critical hurdle. While approximately 50 percent of enterprises express confidence in their change management capabilities, a substantial one-third acknowledge the need for additional investments to fortify this strategic facet. It’s not just about technology; it's about orchestrating transformation seamlessly.

   Consumer acceptance, a linchpin for Gen AI success, introduces complexity. This underscores the need for strategic communication, trust-building initiatives and a focused presentation of the tangible benefits that Gen AI can offer to end-users.

Charting the Course for Gen AI Success

As organizations embark on their Gen AI journey, a strategic approach encompassing technology advancements, data quality improvements, talent development and robust processes is essential. By learning from the successes and challenges of earlier digital CXM solutions, enterprises can formulate effective Gen AI implementation strategies that leverage existing strengths while addressing known weaknesses. The path to Gen AI success is paved with thoughtful consideration, collaboration and a commitment to continuous learning and innovation.