AI’s Data Privacy Bottleneck

AI has dominated every pitch, plan, and conference in contact centers for a few years now, and it’s fascinating to see how the early phases are playing out.

Customer service stands out as a sector where AI can actually deliver on the hype, particularly the transformation savings promised from self-service containment. Skeptics that callers will choose to talk to bots need only look at the usage of LLMs. The question is simply when, not if, AI can provide better support than virtually any human agent, and there’s an argument to be made that we’ve already crossed that threshold in many sectors, with initial analyst reports pointing to 35-40% gains in self-service containment.

Now that we’re a few years into this industry transformation, patterns are emerging with real-world data around both results and challenges. Analysis from McKinsey’s latest quarterly insight on the future of CX, along with Gartner’s latest contact center mq, both converge on a pivotal tension: data privacy.

~Half of AI contact center deployments are stalling or being scaled back due to data privacy concerns.

The concern makes sense. Regulations, redaction tools, and manual practices have been in place for decades around protecting sensitive data that agents get exposed to, but those problems multiply when you have an LLM seeing and hearing those details. LLMs are a lot better at remembering 16-digit card numbers than human agents, for example.

Data privacy should be a basic human right, and we founded Journey with the belief that the current paradigm of requiring people to expose sensitive data with promises of protecting it and redacting it later was unacceptable, and a promise to create a better way.

I’m proud to say that we now have tens of thousands of human agents using our applications to deliver on that promise, collecting and verifying sensitive data spanning PII, PFI, and PHI without the contact center (or Journey) ever having exposure to the data.

Unlocking the true potential of AI-driven self-service containment hinges on solving this data privacy bottleneck, and the answer is NOT to assume the AI has to see the data and introducing a new litany of regulations and tools to manage it. The answer is clean, simple, and available from Journey today: Zero Knowledge.

We’re excited to be inundated with requests to integrate to a growing list of leading AI platforms to provide the ‘easy button’ for interacting with sensitive and complex data in a way that fully de-scopes the AI systems from most regulatory frameworks. There’s a hell of a lot more to come in this once in a lifetime transformation, get in touch if you want to learn more about integrating to Journey’s growing list of MCP servers to tackle this head on.

McKinsey report on the future of CX with AI: https://lnkd.in/gsCt4mQ6

Gartner MQ: Direct: https://lnkd.in/ggtQXMUh