Executive Summary: AI and Customer Experience Insights
“Doing more, with less”
- The Executive Context
This report examines the evolving role of artificial intelligence (AI) and human interaction within modern service environments, with a specific focus on the executive context and operational enhancements.
Key Themes:
- Language Preferences: English is the preferred working language, with considerations for other languages where relevant.
- AI Integration in Professional Services:
- Automation of Content Generation: AI is being used to generate biographical film synopses and other narrative content.
- Personalisation and User Interface (UI): AI enables enhanced personalisation and supports global user experience through multilingual capabilities.
- Job Evolution: While AI may reduce the need for certain roles, it is expected to create new job categories – e.g. Reviewing code instead of writing it.
- Educating AI: AI needs human intervention, especially in the development and validation of digital competencies.
- Information Integrity: AI can support the validation of information and enhances objectivity in tasks such as candidate evaluation.
- Empowerment and Organisational Culture
Challenges:
- Employee engagement and performance had seen a decline.
- The customer advisor role is under pressure, with implications for retention and satisfaction.
Strategic Responses:
- Customer Guidance: Advisors act not only as service providers but as guides, offering a higher level of customer experience.
- Retention Strategies: Addressing root causes of poor service and bad sales is essential for long-term retention.
- Cultural Support:
- Balancing breadth and depth of advisor knowledge.
- Empowering employees to resolve issues independently.
- Fostering a supportive and collaborative environment.
- Channel Effectiveness and Service Innovation
Optimising Customer Service Channels:
- Human Agents:
- Emphasis on delayed, yet genuine and empathetic interactions.
- Simplicity and personalisation remain key.
- Agents are adopting more flexible, non-traditional working patterns (e.g., self-managed schedules and “inside hours” shifts).
- Initiatives like “Try Before You Apply” offer candidates a 1-day preview of roles outside of their core area of expertise, improving recruitment quality.
Multi-Channel Engagement:
- Customers often use multiple service channels simultaneously to seek faster resolutions.
- Insights from Workforce Management (WFM) systems show the need for more dynamic issue resolution and engaging interaction styles.
- Automation vs. Human Touch
Emerging Technologies:
- Facial Recognition: Used to assess emotional state and guide next steps in customer interaction.
- Hybrid Intelligence: Combining AI analytics with human empathy to better understand customer sentiment and behaviour.
- Quality Assurance (QA): AI tools can assist in QA processes, making them more efficient and less subjective.
Conclusion
The integration of AI in customer-facing roles and executive decision-making is redefining operational dynamics. A strategic blend of human expertise and AI capabilities is essential for enhancing service effectiveness, improving workforce engagement, and delivering measurable business outcomes. Organisational culture must adapt to support this transition through empowerment, support mechanisms, and recognition of excellence.
Insight taken from The Executive ConneXion’s face to face event “Doing more, with less” at BT HQ, Aldgate, in May 2025.
