AI FOR BUSINESS – Should you start with a use case?

AI is the future for business and somewhat already here. Here are a few thoughts on how to start on this journey and the importance of a single use case.
Artificial Intelligence (AI) is already part of our business. Gartner survey shows 37% of organizations have Implemented AI in some form. The number of enterprises that implement artificial intelligence (AI) grew 270% in the past four years and tripled in the past year, according to the Gartner, Inc. (Jan. 2019)

source:CES Technologies Association ウェブサイト

AI technology is now extra powerful. Tesla’s Elon Musk could merge your brain with AI as soon as 2020 through his new startup Neuralink. Our eyes will get shiny when we see new capability of AI, and we shall remind ourselves that AI is a new resource to help drive business outcomes.
I spend a lot of time talking to professionals about how to drive successful AI implementation. One common good practices of AI implementation is to start with one use case. Otherwise you will bite off to much technology and not be able to drive this outcome. This first step will lead your organization to a meaningful result – you will then not stop at adding one “AI-toy”.
When you bring AI to your organization, the first thing is to define a clear use case, often times, a simple use case. With this use case, we will be able to understand what “tools” you need, to prototype, test, then scale.

Photo: Jun@CES Fanuc booth

Here are some use case examples from CES2020:
• Bosch concept virtual visor: Bosch Virtual Visor links an LCD panel with a driver or occupant-monitoring camera to track the sun’s casted shadow on the driver’s face. The system uses artificial intelligence to locate the driver within the image from the driver-facing camera. It also utilizes AI to determine the landmarks on the face ‒ including where the eyes, nose and mouth are located ‒ so that it can identify shadows on the face. The algorithm analyzes the driver’s view, darkening only the section of the display through which light hits the driver’s eyes. The rest of the road is more clear than ever.
The Bosch Virtual Visor is a great example of start with a use case, bring AI and other technologies, to solve a “old” problem, and deliver a result: safety and comfort for drivers.

• Another example is well known Industrial robotics giant Fanuc. At CES, I “talked” to a Fanuc robotics arm to pick up a ball from a bin. The robot was very smart and completed the mission. In this case, the use case for Fanuc is to make robots easier to train.
“Making these rules in the past meant having to through a lot of iterations and trial and error. It took time and was very cumbersome,” said Dr. Kiyonori Inaba, the head of Fanuc Corporation’s Robot Business Division.
This is where Fanuc’s new AI-based tool comes in. It simplifies the training process so the human operator just needs to look at a photo of parts jumbled in a bin on a screen and tap a few examples of what needs to be picked up, like showing a small child how to sort toys. This is significantly less training than what typical AI-based vision sensors need and can also be used to train several robots at once.

How to start a use case? I will ask myself and clients:
• What problem you want to solve?
• What business outcome you want to drive?
• What new capabilities and tools you will need to solve the problem or achieve the goal?

One day, I will like to work with AI to help define more use cases – in the right business context.

Jun – Greeting from Silicon Valley, California! I am Jun and run a consulting firm to support Japanese companies that drive and create innovation solutions by leveraging technologies like AI.
Let me know your thoughts, topics you will like to know.