How to Make a Business Case for Conversational AI


How to Make a Business Case for Conversational AI

If you’re like me, you’ve probably found yourself talking to your phone more than talking on itlately.

I ask it to play music, podcasts, and audiobooks, answer oddball questions, find directions and text my friends and family.  I wish I could ask it to pay my bills, check my investments, schedule a flight and hotel for an upcoming conference, and negotiate a better deal with the cable company – soon, very soon, all of this will be possible.

Chris Brogan got me thinking about all of this with his question: “Do you even go to websites?”

Why Create a Business Case?

You and I have noticed that people are walking around talking to their phones. To you and I, it seems logical that we should be building something for them to talk to? A way for consumers to buy things from us with their voices.  But, what’s obvious to us might not even be on the radar of senior management. After all, most of us tend to spend most of our time heads down on short-term, incremental operational improvements.

A business case is an essential tool to help the-powers-that-be to peek over the horizon for a moment and see the opportunity you’re envisioning. Preparing a business case is also a great way to discipline your analysis and present the most persuasive case possible to your management, committee, or board.

What Should Be in Your Business Case?

Clarity is key.  A business case should take your stakeholders on a quick, but a thorough, journey to a world where the consumer’s voice is the default user interface.

Here is a simple framework to build that journey.

Key objectives

What business priorities can conversational AI solve? Instead of finding a new or unique problem for AI to solve, dive into existing business challenges or goals and find one where conversational AI could provide the best solution.

Customer services, sales, and marketing are target rich environments for a conversational AI solution. I also recommend aligning your project with opportunities to directly impact the bottom line – increase revenue, decrease cost, or a little of both.

Outline the business need

I’ll reiterate this throughout this article – pick a real business need.

Whenever possible propose an AI project that will solve a real problem, deliver a better customer experience, or make a process much more efficient. Then take that problem and break it down into its components.

Map out who is affected by this business objective. What customer segment, what business unit, or what product could benefit from conversational AI? Then create a clear vision and requirements for a better experience.

Provide important background and support

Do your research and inform your audience through your business case.

Don’t assume that managers or committees have a full appreciation of the problem. They might not realize all of the ways your department or the company at-large has attempted but failed to solve this problem or seize an opportunity in the past.

A strong business case often builds on the backs of past failures. Educating business leaders on previous attempts can be particularly valuable in making a case for innovations, like conversational AI where more traditional approaches have repeatedly failed.

Describe business alignment

Tuck your business case into the ordinary course of business.

For big ideas and radical innovation, I recommend suppressing the hype a bit. Instead, make sure that your proposal is closely aligned with current business objectives. Show how conversational AI can move a specific initiative forward, without distraction.

Build a case that demonstrates how conversational AI perfectly aligns with the experience your business is attempting to bring to the customer, and that the customer is beginning to expect.

Provide a detailed analysis of the investment

Do the math. Make sure that the finance and accounting folks see that you have your eye on the bottom line. Document a clear and reasonable path to a positive ROI.

Outline the approach – timelines, resources, solutions

A detailed project plan is probably the most crucial part of your business case.

Preparing a well-organized plan to provide a viable AI assistant to help customers engage with your products and services inspires confidence. Managers and executive can start to see precisely how your project can help them achieve their objectives, timelines, and is the best solution and use of their resources.

Embedding a high-level project plan in your business case begins to make everything feel reasonable and achievable.

Risk assessment

In your zeal to appeal, don’t ignore or bury potential risk factors.  Demonstrate that you have a firm understanding of the strengths and weaknesses of the current state of AI technology. Carefully consider and outline what you can foresee going right and wrong.

My favorite approach is to use ranges of probability. This technique lays out the various potential outcomes and then assign them high and low probabilities. This list of results and possibilities is a simple tool for stakeholders to review risk bands and consider those that concern them the most.

Provide options

Finally, never rest your conversational AI proposal on an up or down, yes or no vote. Instead, provide a full range of options from a pilot program to an all-in investment on the future.  With the emergence of highly capable enterprise conversational AI platforms, like Clinc carefully dipping your toe into AI, while still delivering an incredibly compelling customer experience is an option.

Your Conversational AI Business Case in Hand, Now What?

You’ve taken the time to write a tight and compelling business case, now what?

I always recommend a think big, work small approach when you’re trying to be the change agent in an organization.  Begin sharing AI research and examples with all levels of your organization, from business analyst and programmers to management. These little seeds begin to germinate in a variety of ways.

Business analysts will propose, and programmers will begin to investigate and introduce new libraries, frameworks, and data stores that bring in AI and machine learning on the edge of other projects. Managers and executives’ competitive juices begin to flow, and they desire a place in the emerging AI assistance ecosystem.

Before you know it all of these stakeholders become eager to engage your company’s products and services with their voice!

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