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TLDR

The IBM Institute for Business Value has developed a series of guides to assist CEOs in understanding and leveraging generative AI, with a focus on various business aspects such as customer service. The goal is to help leaders navigate the rapid changes brought about by generative AI, which is rapidly transforming business operations and societal interactions. This particular guide emphasizes the transformation of customer service from a cost center to a value creator using generative AI.

Methodology:

  • The insights are derived from three proprietary surveys conducted by the IBM Institute for Business Value in collaboration with Oxford Economics.
  • The surveys targeted 200 US-based CEOs, 369 executives from various countries, and 108 executives from 18 countries, conducted between April and July 2023.
  • The surveys sought to capture perspectives on the implementation and impact of generative AI in customer service.

Key Findings:

  • Generative AI as a Top Priority: Customer service has become the number one priority for CEOs when it comes to generative AI applications, surpassing other areas such as research and innovation.
  • Direct Customer Interaction: 85% of executives anticipate that generative AI will interact directly with customers within the next two years, suggesting a significant shift in customer service dynamics.
  • Investment in Agent Tools: 63% of executives plan to invest in generative AI tools to directly support customer service agents by the end of 2023, aiming to enhance agent capabilities and improve customer interactions.
  • Risk Management: While generative AI presents opportunities, it also poses risks such as off-brand responses or transparency issues, necessitating careful deployment and oversight.
  • Learning from AI: Generative AI is being used as a research tool to understand customer sentiment and drive innovation, with a focus on data governance and brand differentiation.
  • Pilot Successes: Piloting generative AI in customer service is seen as a way to expedite enterprise-wide adoption, with the customer service sector acting as a testbed for broader organizational transformation.

Recommendations:

  • Empower Agents: Equip human agents with generative AI tools to automate routine tasks and focus on personalized customer engagement, transforming them into “heroes” of customer service.
  • Transparent AI Use: Maintain transparency with customers about the use of generative AI bots and provide easy access to human assistance when needed.
  • Innovation through Service: Leverage customer service as an innovation hub, using generative AI to gather insights and drive organizational change.
  • Share Successes: Publicize successful generative AI applications within customer service to motivate and inspire adoption across other departments.
  • Encourage Broad Participation: Foster a culture of innovation by inviting employees to contribute generative AI use case ideas that can benefit their work and the organization as a whole.
  • THINKING CRITICALLYImplications:
    • The adoption of generative AI in customer service is expected to transform the sector from a cost center to a value creator. If organizations across the board implement these AI tools, we could see a significant shift in how customer service is perceived, potentially leading to heightened customer satisfaction, increased efficiency, and the creation of new revenue streams. Conversely, failure to adopt such technology could result in businesses falling behind in competitive markets, as they miss out on opportunities to enhance customer experience and operational efficiency.
    • The strategic deployment of generative AI tools could redefine the role of human customer service agents, elevating their work to focus on complex, sensitive, and high-value interactions. This could lead to a more fulfilling work environment and the development of new skill sets among employees. However, if not managed carefully, there is a risk of job displacement or a devaluation of human touch in customer interactions.
    • The report suggests that piloting generative AI in customer service could act as a catalyst for broader organizational change. Successful implementation could serve as a model for enterprise-wide AI adoption, potentially leading to widespread operational improvements and innovation. On the flip side, if these pilots result in negative customer experiences or public relations issues, it could lead to a backlash against AI technologies and hinder their adoption.
    Alternative Perspectives:
    • While the report is optimistic about the potential of generative AI, there may be concerns about the quality and authenticity of AI-generated interactions. Some customers may prefer human interaction and perceive AI as less trustworthy or empathetic, which could impact customer loyalty and brand image.
    • The report assumes a smooth integration of AI with existing systems and workflows. However, technical challenges, data privacy concerns, and resistance to change among staff could complicate the deployment and scaling of generative AI solutions, potentially leading to unanticipated costs and delays.
    • The findings are based on surveys that reflect the intentions and expectations of executives, which may not fully capture the practical challenges and customer attitudes towards AI in customer service. There could be a gap between executive optimism and on-the-ground realities, including the readiness of AI technology to handle nuanced customer service scenarios.
    AI Predictions:
    • Within the next two years, we can expect to see a significant increase in direct customer interactions handled by generative AI, as executives are keen on implementing these technologies. This will likely lead to a new wave of innovation in customer service tools and platforms.
    • As generative AI becomes more prevalent in customer service, there will be a growing emphasis on agent training and development to ensure that human agents can effectively collaborate with AI tools and manage the more complex customer issues that AI cannot resolve.
    • The rise of generative AI in customer service will likely prompt a reevaluation of metrics for success in the industry. Traditional measures such as call handling time may become less important compared to customer satisfaction, retention, and the ability to generate actionable insights from customer interactions.
  • GLOSSARY
    • Value creator: A new role for customer service, transitioning from a cost center to a generator of value through the use of generative AI.
    • Operational proficiency: The ability to efficiently operate and manage new ways of engaging with customers through AI tools and human agents.
    • Leapfrogged: The act of customer service overtaking other functions as the top priority for generative AI implementation among CEOs.
    • Trust and reliability: Essential design principles for customer service when implementing generative AI, ensuring customer engagement is supported while maintaining human touch.
    • Heroes: A term used to describe human agents who are empowered by generative AI tools to provide enhanced customer service.
    • Revenue accelerator: The potential transformation of customer service from a cost center to a significant contributor to revenue through the use of generative AI.
    • White-glove service: A high standard of customer service that can convert unhappy customers into brand loyalists, achievable through skilled human agents supported by generative AI.
    • Guardrails: Measures or controls put in place by human agents to prevent or correct less-than-ideal outcomes from unsupervised generative AI.
    • Emotional connections: The human ability to forge relationships with clients, leading to new insights and opportunities, enhanced by AI.
    • Sentiment-based metrics: Data collected and analyzed by generative AI to understand customer emotions during service interactions.
    • Data governance: The management of data availability, usability, integrity, and security in an organization, which should be refocused around with the use of generative AI.
    • Proof of concept: Demonstrating the effectiveness of generative AI in customer service as a model for its potential impact across the entire enterprise.
    • Innovation hub: A new role for customer service as a center for generating innovative ideas and practices through the use of generative AI.
    • Gamified opportunities: Interactive and competitive scenarios created for employees to engage with generative AI and propose new use cases.

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