HBR describes a project that after 4 years and $62mill achieves nothing and makes the point that "low-hanging fruit" should be the focus rather than big "moonshot" projects.
The lure of AI can be seductive; leapfrog analogue competitors and transform the business. But, as always, data is key and the quantity and quality beyond the capabilities of most enterprises. If you can only access 20% of your data you will not be able to manage "moonshot" scope AI. And that is the case for most companies and organisations- all that nasty unstructured data hidden in data silos and multiple legacy systems inherited with each M&A.
Try smaller projects and the results may well make a huge difference in three areas.
- Process Automation
- Cognitive Insight
- Cognitive Engagement
To do so you will need to:-
- Understand your customers and future behaviour
- Understand the technologies
- Create a portfolio of projects
- Launch pilots
- Focus on low hanging fruit
- Scale up
Follow the advice in Harvard Business Reviews' "Artificial Intelligence for the Real World" January-February 2018 article below.
Our survey of 250 executives who are familiar with their companies’ use of cognitive technology shows that three-quarters of them believe that AI will substantially transform their companies within three years. However, our study of 152 projects in almost as many companies also reveals that highly ambitious moon shots are less likely to be successful than “low-hanging fruit” projects that enhance business processes. This shouldn’t be surprising—such has been the case with the great majority of new technologies that companies have adopted in the past. But the hype surrounding artificial intelligence has been especially powerful, and some organizations have been seduced by it.
https://hbr.org/2018/01/artificial-intelligence-for-the-real-world
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