What companies need to know before using AI
While most companies struggle to make sense of artificial intelligence (AI), some have made significant progress. Within retailers and consumer brands, two reasons for this separation are bubbling up to the surface: “explainability” and having the capacity to test many use cases.
Retailers and brands should not embark upon the use of AI without first understanding how the insight is generated, what data sources it relies upon and the ethical implications. Why? Those in the business will definitely ask, your customers may ask, and ultimately the entire company could be called to account to explain why a particular action was taken. It could be as seemingly benign as a dynamic price offer for a customer — an action a large retailer recently found was not so benign.
Consumers are becoming increasingly anxious today about their data privacy and how their data is used. This is only going to escalate and those prepared to answer for it will be better off. So business, technology and analytics staff need to be educated consumers.
Test and Learn
The ability to test many use cases goes hand-in-hand with explainability. Why? Analytics, like machine learning (behind most AI use cases), are all about continuous improvement. If you can’t understand the most basic factors driving an AI solution, how can you hope to measure and improve? To scale value and reap the most benefits, companies of all sizes need the capacity to evaluate, improve and completely renovate AI use cases.
When you can do this, you support efficient exploration of many use cases that map to your company’s business strategy. Companies can derive greater benefits when AI flows from a use case portfolio as opposed to leaving it to silos to explore point solutions in a disconnected manner.
The companies that address these two points well are among the largest and most experienced with advanced analytics. The challenge for the masses is how to adopt these best practices with less human, financial and technical capital. Anything short of a thoughtful plan supported by the CEO is probably going to fail.
DISCUSSION QUESTIONS: Why do retailers seem to have a hard time explaining their use of AI and fail to adequately employ testing and learning strategies around the technology? What should retailers do differently to address these challenges?