Thinking about using AI to solve a business problem? Follow our practical guide to get the best-possible value from any AI investment.
With our AI scheduling assistants surpassing the 10M email mark back in mid-January, we know a thing or two about maximizing the value of our AI for the businesses we serve.
A lot of what we’ve learned applies to the larger enterprise AI landscape, so we wanted to share our knowledge with a quick rundown of the lessons we covered in our “Leveraging AI for Business” webinar (which you can watch in full below).
Understand the different types of AI
If you’re seeking AI as a business solution, you should first understand the differences between horizontal and vertical AI. The former can answer a broad range of disparate questions (i.e. “how tall was Napoleon?), but without much additional action (think Siri, Alexa or Google Assistant). The latter automates only one task, but can handle all the complex logistics that comprise that task, which usually makes them more valuable for businesses. Our scheduling AI assistants are examples of vertical AI.
Determine whether an AI investment has true business value.
This really comes down to making sure you can track a clear ROI. Here are a few helpful ways to discern between the AI that has true value to your business, and the ones that don’t:
AI with true business ROI:
-Solves a business problem that is wasting tangible money, time, or resources
-Can be adopted at scale to address depth of problem
-Is more cost-effective than pre-existing or internal solutions
-Features AI/Machine Learning that’s vital to the solution
AI with limited or no business ROI:
-Seems fun or intriguing, but promises no clear trackable ROI
-Is too complicated to use for easy teamwide adoption
–Costs a lot or doesn’t offer significant savings of time/money/resources vs. other solutions
-Features AI/Machine Learning that seems like a superfluous add on
Narrow down the business solution(s) AI can solve for you
In today’s AI landscape, we consider there to be three main business problems that AI can solve at scale:
-Replacing menial work tasks (like meeting scheduling or sorting job applicants for qualified candidates)
-Managing data and media (like visual search or reading data from paper)
-Expanding and retaining business (like automatic customer responses and deeper communication insights)
Introducing AI to your team.
We’ve found teams have the most success when everyone understands that AI is designed to be complementary to them, giving them superhuman abilities. For instance, because our AI handles scheduling logistics, workers can reinvest the time in higher volume of meetings, or a higher quality of communication.
Paul Daugherty, Chief Technology Innovation Officer at Accenture, terms this concept “collaborative intelligence.” Here are 5 tips for fostering a healthy working relationship between your humans and your AI:
- Affirm that AI is designed to complement workers, not supplant them.
- Encourage patience, AI is more effective through stronger rapports.
- Remind workers of the positive career opportunities AI affords them.
- Introduce your team to AI tools with a detailed onboarding plan.
- Identify early adopters and utilize them as internal champions.
We love answering AI-related questions for our community of teams and businesses. If you’d like to put these lessons into practice, sign up for a free team trial today.
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