Stop Your AI Project From Going Out of Control

I love to ride my bicycle; it doesn’t matter if it’s on the road, along gravel tracks or down mountain paths. I enjoy the challenge, the physical effort and just being out in open air. However, I hate to feel out of control, not being ready for what’s ahead scares me. So, I prepare. I service my bike, I (mostly) eat right, I ensure that I have enough nutrition and liquids for the ride, I carry the tools needed to fix my bike if it breaks, I research where I’m going and the terrain I’ll encounter, and I ride with others who know the area. Being prepared helps me avoid accidents and incidents. Your AI project should be no different.

I’m always surprised when customer experience leaders don’t properly plan an artificial intelligence (AI) project. Without properly planning, that project can quickly feel like you’re riding a bicycle downhill — out of control — with little preparation and no proper tools.

Here are some pointers for avoiding a crash and staying upright throughout the entire AI project and journey.

Goals
Start with clear goals — think big but start small. Know the strategic rationale for AI and machine learning for customer experience — how they’ll improve your business? Understand how big the business opportunity is — what is its value to you? What is the cost of doing nothing — are you losing out by not doing it? How much will the entire project — not just the pilot or test project — cost? What business or technical benefits will each project in the program ultimately deliver?

Outcomes
It’s vital to know what results to expect and how you’ll obtain them. What will be your ROI, will it really add long term value to your business? Does it fit well in your longer-term business and technology strategies? What is the time to value — how quickly will you see a return? What are the first small steps you need to take to achieve those long-term goals? And do you have the right stakeholders involved to succeed?

Stakeholder Buy-In
Without stakeholder buy-in, your AI project will crash and that hurts. Here’s how to get the buy-in you need.

  • Know the revenue potential across the program and each project — short, medium and long-term.
  • Recognize the power of the fear of missing out (FOMO). What if your competitors implement this? leverage this to help obtain buy-in.
  • Show where the small wins are and how the stakeholder will benefit.
  • Don’t talk about AI; it scares people. Instead, allay their fears by focusing on the benefits and the value it will deliver.
  • Educate, educate, educate about how AI and machine learning will improve your business.

It’s a Team Sport
In cycling, even when it’s an individual competitive event, there’s still a degree of collaboration — with bike stores and suppliers, event organizers and even other riders. The same is true for your customer experience AI project.

You need to work cross-culturally — across marketing, sales and customer service — to deliver the best results. This means regularly repeating the stakeholder buy-in process.

Decide who on your team is best to work on this program — not just who’s free. Work across your department and others to create synergy. Determine if there are other organizations with whom you can collaborate: suppliers, customers, even competitors.

Analytical Culture
Ultimately, your AI project should become an AI program that generates an analytical culture. Analysis happens at many levels, it’s more than for AI and machine learning. This rigor needs to be ingrained in the very heart of your business.

Implementing a customer experience AI project or program doesn’t have to be over-complicated and you can avoid crashing out. With proper planning and the right partner, it’ll be just like riding a bike.

Register now for Xperience19, June 10 – 13, in Denver, Colorado — and don’t miss the customer experience event of the year.

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