Putting AI To Work In Your Customer Experience

GenAI is evolving quickly, new models, new competition, new possibilities. That's why I am back continuing the conversation with Andrew McInnes from Genesys about how to integrate AI into your customer and employee experiences.

CX Skills & Methodologies Must Guide Use Case Discovery

There are so many possibilities for applying AI or Generative AI to your experiences, where should you focus first for possible pilots? Andrew encourages listeners (and readers) to use their existing skillsets to guide this decision-making process.

Customer journey mapping turns up pain points and sections of the friction with more friction than you'd like. Those pain points and sections of friction are pilot possibilities for AI agents to smooth out the friction, to address the pain points.

For me, this is really clarifying!

You don't have to know where to pilot AI agents for customers. You also don't have to mimic what others are doing. As with other technologies, other changes to your experience, you should simply observe where customers and employees struggle the most, and then design an intervention that removes that friction or pain point.

And it's not just customer use cases that benefit from these skills. Andrew talked about the potential of text and voice analytics to spot opportunities for pilots with employees.

And then also observation matters here. Go and see what employees are struggling with. Rep shadowing in the call-center. Mystery shopping in the stores and other physical locations.

Don't guess. Don't copy what others are doing. Look for the highest-potential implementation use cases in your experience.

Your Goal Is To Complete A Successful Pilot

Targeting high-friction parts of the experience, high-potential moments or touchpoints not only makes your likelihood of success higher, it also builds trust with stakeholders - employees, customers - that your AI efforts are in their interest.

This trust is crucial to the success of your initiatives. After all, you need employees and customers to try the Co-pilot or Agent. You want them to adopt the Co-pilot or Agent. These behaviors - trying and adoption - are much more likely in trusting environments.

Focusing on the needs of users, the struggles of users builds that trust you need to complete a successful pilot. The success of the first pilot gets you permission for the 2nd pilot, and on from there.

Co-pilots that empower your employees to be more human make your customer experience better.

Look For Unexpected Constraints & Second Order Effects

Humans are complicated. Experiences are complicated. You will encounter unexpected constraints, unforeseen second-order effects. Be ready for this, plan for this.

Ok, but how?

Measure and observe beyond the narrow pilot or use-case you implemented for.

Andrew talked about one company he worked with that found a significant increase in appointment schedule after they implemented customer-support agent co-pilots, even though that wasn't the goal of the co-pilot implementation.

They looked into it, and found that the Co-pilot was enabling the call-center agents to be more present on customer calls, pay attention to the person they were talking to, attend to their emotional needs rather than having to devote so much of their mental focus to retrieving information. This is the kind of benefit that can then become the evidence for the success of the pilot.

Be vigilant for unforeseen constraints and second-order effects - they can sink your pilots.

Job Losses From AI Will Happen & Are Already Happening

We can't look away from this very real first-order effect of a new technology that eliminates types of work, and makes other types of work more efficient and productive. When that happens, job loss follows.

That is true today for AI. It's been true for every single disruptive technology in history. It is not a reason to stop progress.

Why?

Because AI, like past disruptive technologies isn't going to lead to less work for humans to do.

Andrew highlighted the emphasis of so many of his clients is on doing more with their existing employees, but also that they're looking for new use cases that AI agents or co-pilots can handle that humans couldn't, or that weren't economical for humans to handle. This is the promise of a new technology, it creates new types of work. And when it does, inevitably, there will be complimentary new types of work for humans to do.