Gartner believes that by 2022, 85% of AI projects will fail. One of the key reasons for this high failure rate is that often the use case being applied has not been through a rigorous selection process and the following considerations are overlooked. For example, is the AI use case:
- Based on an operational challenge that has high OPEX and therefore has the opportunity to generate revenue or create savings?
- Has enough of the right data
- Has measurable benefits and ROI
- Does not jeopardize plant safety; and
- Can be scaled to similar processes and plants.
To help industrial companies avoid the pitfalls of selecting the wrong AI use case, Canvass AI has compiled the top 10 AI Use Cases for the Industrial Sector, to help industrials identify the right AI use case for success.
Download the e-book here.