The Hidden Risks of GenAI in Customer Communication—& How to Fix Them

Businesses are increasingly adopting GenAI solution to enhance the way they communicate with their customers. As with any rapid adoption of technology, there are a set of challenges that have arisen. These include the complexity of how generated content flows through an organization, the multiple points of failure that can introduce risk, numerous and varied communication channels, and a multi-vendor environment. To address these challenges, a comprehensive solution is required that ensures secure and safe adoption of customer-facing content generated using AI. 

Challenges in Customer Communication 

Let's explore each of the challenges listed above.  

Complex Content Generation Flows: Creating personalized and relevant content for customers involves multiple inputs, generation types, human input, and intricate processes that can introduce errors. From drafting initial messages to fine-tuning responses based on customer interactions, each step must be carefully managed and supervised to maintain relevance and accuracy. 

Multiple Points of Failure and Vulnerabilities: The integration of GenAI introduces several potential vulnerabilities that need to be managed effectively. These include risks associated with data accuracy, privacy, misinformation, and data cross contamination, which can negatively impact the customer’s experience with your organization and the trust they have in your products or solutions. 

Multiple Communication Channels: Businesses communicate with customers through various channels like email, social media, chatbots, in-product, and each channel has its own context and content requirements. Ensuring that content creation is consistent across all platforms is critical to maintaining customer confidence. 

Multi-Vendor Environment: It is typical for different groups within larger organizations to have a different set of vendors they use that are specific to that groups’ needs. But the more vendors that are used or integrated into various systems and processes complicates the implementation and maintenance of GenAI platforms. Different vendors will have varying oversight standards and practices, making it challenging to ensure a unified posture. 

The Solution 

To overcome these challenges, we recommend a holistic solution that focuses on ensuring accurate risk analysis, consistent use of business logic, and proactive risk management that covers all content generation methods and content dissemination processes. That solution must include the following functionality:  

Accurate Risk Analysis (Business-Context Aware): Uses a risk analysis framework that can interpret and understand the organization’s specific business context to identify potential threats and vulnerabilities in generated content. The solution should also continue to learn and adapt to changes in the business logic and context to adhere to a high level of accuracy. This allows for more tailored and effective risk mitigation strategies specific to the organization's content needs. 

Agnostic to Generation and Human Edits: The solution should be capable of handling both AI-generated content and human edits seamlessly, ensuring consistency and security across all communications and content types. This flexibility ensures that the communication flow remains uninterrupted and secure, regardless of the source of content. 

Single Business Logic Applied Consistently: Establishes a unified business logic that is consistently applied across all communication channels and content generation processes to maintain coherence and reduce the risk of errors. This ensures that all customer communications are aligned with the organization’s policies and standards, regardless of dissemination channel. 

Detect and Prevent Risks in Communication Channels (Content in Motion): Implements real-time monitoring and risk detection mechanisms for content being transmitted through various communication channels ensuring that any potential content-related threats are identified and mitigated promptly. This proactive approach helps in preventing privacy issues and other security incidents. 

Identify and Disable/Remove Risky Content in Data Stores (e.g. CRM, Knowledge Base): Regular audits and automated tools can help in identifying and flagging data in repositories that needs to be remove or disabled, such as CRM systems, to prevent any potential communication issues. This ensures that sensitive information is protected, and that the organization’s data remains trustworthy and accurate. 

Continuous Improvement and Adaptation: To stay ahead of emerging threats and challenges, businesses must adopt a continuous improvement approach, especially considering the rapid advancements and growth in the AI space. This involves regularly updating content rules and expectations, conducting training sessions for staff, and staying informed about the latest developments in AI and cybersecurity. 

By addressing these challenges with an intentionally-built and comprehensive solution that is designed specifically to address the nuances of AI and how organizations use it day-to-day, businesses can ensure the secure and safe adoption of customer-facing GenAI, ultimately enhancing customer communication and trust. This not only improves the quality of interactions with your customers but also streamlines internal processes, introduces efficiencies, and does so while delivering security and trust.