8 Keys to a Successful Conversational AI Deployment
So, you’re thinking about introducing a conversational AI project into your business? There’s a multitude of ways you could have arrived here. Maybe all the AI buzz has you thinking you need to get a project on the books, or risk being left behind (or lacking that bullet point on your Linkedin profile). Possibly, you’re looking for a creative way to get an edge on a larger competitor. Or maybe you’re just curious about how AI could benefit your particular business or industry. In any of these scenarios, you’re probably looking for a quick, easy win. A project that will help you build understanding and support within your organization for larger AI initiatives in the future. But, like any leading-edge technology, your AI project can risk getting mired in the experimental weeds if you don’t clearly define the benefits to the business and a short path to those benefits. To that end, let’s take a look at eight keys to creating the most direct and successful path to your first conversational AI deployment.
1. Start with a Real Business ProblemOne of the most common reasons AI implementations fail is because they lack a clear business problem to solve. Too often our expectations of artificial intelligence are still in the realm of science fiction. For instance, we assume that AI will find problems to fix or reveal treasure under a mountain of unstructured business data.This is my first cautionary note: These kinds of soft, aspirational objectives make for great research projects, but disastrous business initiatives.The priority for a new conversational AI project should be to clearly define a customer need and finding a project team of subject matter experts that are committed to solving that problem with conversational AI and Machine Learning. After that, your business case and project plan are not so different from any other technology project in your organization. A strong conversational AI proposal will be one that has well-defined goals and objectives, focused on solving a specific business need, and filled with very detailed use cases that we expect conversational AI is well suited to tackle. In a simple phrase, your goal with your first conversational AI project is to create a clear vision with a pragmatic plan.
2. Think Big, But Work SmallThink big, but work small is one of my favorite technology project mantras. This simple philosophy is well suited for implementing any leading-edge technology but particularly appropriate for new AI initiatives.We’re not looking to create revolutions, but rather evolutions. In doing this, it’s quite alright to think big about your ultimate vision. Have grand plans for where conversational AI will take your business in the future, but your starting point should be small and specific. When looking for the right place to start, I recommend looking for areas with lots of customer interactions and a clear expectation of how conversational AI might make those experiences better. Common examples might include:
- Customer service calls that are filled with routine and frequently asked questions, but force customers to wait in long, unprioritized queues for simple answers
- Drive-through ordering that is typically guided by well-defined menu choices, but forces customers to experience a slow and error-prone process at the hands of employees that can be overwhelmed by this inherently frenetic traditional human-to-human interface
- Routine transactions that can be assisted by machines learning from your repeated behaviors and then assisting in reducing your participation in these repetitive activities. A perfect example of this is what x.ai has done for scheduling meetings.