Fostering Customer Engagement and Trust with Generative AI

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Only with a commitment to ethics and transparent communication of that commitment will you be able to take full advantage of customer-centric opportunities presented by gen AI.

AI Tools Can Help Build Customer Loyalty

Decorative image representing an AI-powered chatbot with the Cascadeo logo in white.Generative AI presents both opportunities and challenges in the area of customer engagement. While gen AI implementations offer a wide range of ways to more closely connect to your customers, doing so will require building customer trust in emerging technologies about which many feel skeptical or uneasy.  

What does that mean for your generative AI strategy? It means that you need a strong policy for AI ethics from the outset, one that establishes your responsibilities as an AI user, is communicated clearly, and contains flexibility to address emerging technologies and uses. As engagement with AI through both vendor-supplied applications and custom implementations rapidly expands, you can then continue to update your policy to reflect shifts in use case.  

Only with a commitment to ethics and transparent communication of that commitment will you be able to take full advantage of customer-centric opportunities presented by gen AI. While responsible use of AI is always important, it takes primacy in customer-facing use cases, considering the AI anxieties many in the general public carry into their interactions with businesses and vendors.  

Gartner’s definition of responsible AI provides a good start to understanding the complications of building customer trust around AI; it includes “business and societal value, risk, trust, transparency, fairness, bias mitigation, explainability, sustainability, accountability, safety, privacy, and regulatory compliance.” Of these aspects, transparency may be the most important to customers who want to know whether a human or an LLM created the content they’re reading* or is interacting with them via a customer service interface. They may also want to know how the accuracy of AI-generated information was verified, how the data generated from their interaction with that interface will be used and protected, and how bias is being combatted. 

Making responsible AI choices as you build your program helps, as well. AI vendors often publish their own ethical policy statements, which you can review for alignment with your own corporate priorities as you choose implementations. Anthropic uses it’s own technology to ensure that Claude will, “avoid toxic or discriminatory outputs,” among other endeavors, for example. Adobe purports to put “creators at the center” of its Firefly tool, training on licensed content, which helps quell IP fears. Choosing AI providers whose ethics mirror your own and address your customers’ concerns, and communicating those choices clearly, can go a long way toward building a trusting relationship that will invite your constituents to engage with your AI tools.  

Once that trust has been established, AI tools can open a wide array of lines of customer communication. More responsive and eloquent chatbots are already widely in use. Content creation tools like Microsoft O365 and the Adobe Creative Suite offer generative AI augmentations to increase productivity and reduce communication lag time. Social posts can be automated, and self-serve customer service options have dramatically expanded. Customer interfaces can be augmented by AI to improve engagement via disability access and multilingual translation functions, as well.  

AI can also support more complex customer communications. For example, MSPs using tools like Cascadeo AI can provide customers automated reporting in plain language to improve observability into their managed accounts, opening new lines of communication, articulating cloud operations, and providing evidence of the value of cloud management services.  

Customer data analytics is another area where this evolving technology shines bright, by providing visibility into patterns of behavior gathered through every interaction. In B2B contexts, it can customize content campaigns, offer personalized recommendations, highlight upsell opportunities, predict churn, suggest dynamic pricing options, and analyze contracts to provide renewal and renegotiation insights. In B2C contexts, it adds hyper-personalized product recommendations, email outreach, social ads, and interactive product experiences to your marketing toolbox, as well as analyzing customer sentiment and buying patterns. Overall, generative AI can dramatically increase your responsiveness to customer needs, giving you more opportunities than ever before to build brand loyalty, keep the clientele you have, and increase your sales with knowledge and insight for sustained, scalable business growth.  

*this blog post was written by a human 



2024-02-12T10:48:40-08:00January 19, 2024|Blog, GenAI, News|
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