Sourcing and Contracting for CCaaS Solutions in the Age of AI

Sourcing and Contracting for CCaaS Solutions in the Age of AI

In today’s rapidly evolving technological landscape, Contact Center as a Service (CCaaS) has emerged as a pivotal solution for enterprises aiming to enhance customer engagement and operational efficiency. The integration of Artificial Intelligence (AI) into CCaaS platforms has introduced a plethora of advanced features and capabilities, transforming the way businesses interact with their customers.

AI continues to dominate the CCaaS space, delivering significant improvements in areas such as call transcription and summarization, predictive capabilities, trending topic detection, sentiment analysis, natural language Q&A, and automated scoring. These functionalities provide compelling use cases that can be tracked and measured, offering enterprises valuable insights and efficiencies.

Despite the influx of AI-driven features, the key players in the CCaaS market remain largely unchanged. However, new product names and offerings have been introduced, adding complexity to the pricing structures. For instance, Genesys has incorporated AI Experience tokens into its pricing model, which includes features like answer highlights and wrap-up code prediction. These tokens are purchased in units measured per event, route, seat, or session, depending on the type of cloud product, further complicating the pricing exercise.

From a contracting perspective, the migration from on-premises solutions to cloud-based CCaaS platforms necessitates a thorough understanding and contractual agreement on the use of AI and AI-driven features. Enterprises must establish comprehensive AI policies that address data protection, intellectual property, liability, regulation, and ethics. These policies should include a governance model and an ongoing governance board to ensure continuous oversight and updates based on the latest developments.

Defining an AI policy involves addressing foundational questions such as the nature of the AI component, data usage and sensitivity, data residency, consent requirements, and applicable laws4. This approach ensures that enterprises are well-prepared to navigate the complexities of AI integration in their CCaaS solutions.

The process of sourcing CCaaS services has also evolved with the advent of AI. While the fundamental process of issuing a Request for Proposal (RFP) remains unchanged, the questions and terms within the RFP must now include AI-specific language aligned with the enterprise’s policies5. This includes defining AI, understanding data storage and usage, and ensuring compliance with ethical and regulatory requirements.

Ultimately, the goal of any CCaaS solution is to address the enterprise’s business objectives, such as improving customer satisfaction, customer experience, and employee experience. Understanding the use cases, environment size, and integration requirements is crucial to developing a cost model that fully contemplates the target environment, including AI-related costs.

In conclusion, the integration of AI into CCaaS solutions presents both opportunities and challenges for enterprises. By establishing robust AI policies, engaging in thorough contracting processes, and continuously updating governance models, businesses can effectively leverage AI to enhance their contact center operations and achieve their strategic objectives.