In the rapidly evolving landscape of Artificial Intelligence (AI), recent events such as Air Canada’s legal dispute over its chatbot refund policy have sparked a mixture of excitement and fear among organizations. While AI promises to streamline processes and enhance customer experiences, it also carries the potential for unexpected pitfalls, including the dread of hallucinations—misguided outcomes that AI may produce. However, amidst these concerns, there are invaluable lessons to be learned that can guide businesses in crafting robust and future-proof AI strategies.
Lesson 1: Know Your AI Model
For industries with stringent compliance requirements, particularly those seeking to deploy AI-generated responses directly to customers, opting for a closed or proprietary AI model is a must. Unlike open AI models that leverage vast datasets, closed models keep sensitive data within the organization’s confines, bolstering security and mitigating risks associated with data privacy breaches. By harnessing an in-house AI model, companies can maintain control over the generation process, ensuring accuracy and compliance with regulatory standards.
Lesson 2: Human in the Loop
AI is promising to solve many problems for organizations. Creating a more efficient workforce is leading the pack in terms of meaningful Return on Investment (ROI). Microsoft’s Copilot has burst out of the gate with some pretty impressive stats – 86% say Copilot makes them more productive and 81% say it helps them complete tasks faster.
So, does that mean Gen AI is ready for end user consumption? Maybe, but with some clear conditions.
Augmented AI refers to the integration of AI systems with human expertise to enhance decision-making processes and problem-solving capabilities. In this approach, AI serves as a supporting tool alongside your Knowledge Managers and Subject Matter Experts (SMEs). This collaborative model enables organizations to harness the transformative potential of AI technology while maintaining control and ensuring alignment with business objectives and ethical considerations.
By involving Knowledge Managers and Subject Matter Experts in the loop, businesses can leverage AI’s capabilities while upholding the integrity of their knowledge base. This approach fosters collaboration between AI and human intelligence, enriching the quality of generated responses and bolstering customer satisfaction.
Lesson 3: Knowledge Management as a Single Source of Truth
Regardless of the channels through which customers interact—whether it’s through conversational AI, voice IVR, or direct human interaction—a centralized and governed knowledge management system is critical. This system serves as the backbone for creating, enriching, and delivering information, ensuring the right answer every time regardless of the channel.
The legal challenges faced by Air Canada underscore the significance of robust knowledge management practices. By establishing a governed knowledge management framework, organizations not only elevate the customer experience but also mitigate the potential risks associated with AI implementations.
Customers can trust that the responses provided are derived from a vetted and approved source, instilling confidence, and fostering positive interactions.
While the idea of diving into AI innovation might be exciting, it’s important for organizations to tread carefully and plan ahead. But don’t let fear hold you back! Instead, find a trusted partner to guide you through the journey. By sticking to these three simple principles—understanding your AI model, valuing human expertise, and establishing a reliable knowledge management system—businesses can confidently navigate the complexities of AI adoption. Rather than seeing Air Canada’s legal issues as a reason to hesitate, let it remind you to stay alert and ready for the challenges ahead.
If you’re starting your AI journey or need help assessing your current strategy, don’t hesitate to reach out to our Upland Knowledge experts.