#RetailTech: Prioritising AI opportunities in retail – Retailers’ guide to identify the right AI use cases
A critical element for success of AI initiatives is to pick the right use cases that create long-term value for the enterprise. My previous article on AI use case landscape in retail: Guide to start your AI journey showcases a periodic table highlighting the breadth of AI use cases that retailers can implement today to start their AI journey. However, it is important that they prioritise the right use cases to accelerate their AI journey and this article talks just about that.
Source: MarTech Advisor
A comprehensive framework encompassing all the vital parameters is necessary before making the business case for working on an AI use case.
Enterprises need to evaluate the use cases thoroughly based on their organisation’s priorities, vision, road map, culture and capabilities. Here is a simple, yet powerful, use case prioritisation matrix based on a combination of business impact and ease of implementation considering existing capabilities and limitations of the enterprise. The below framework, prioritises the use case categories and provides a directional view for enterprises who want to start or scale their AI journey.
Enterprises can start with “Quick wins” – use cases that have high business impact and but are also easy to implement, or “Big bets” – use cases having high business impact but also higher implementation effort, or retailers can look to implement “Incremental” use cases – uses cases that are easily implementable but may not have a huge impact on business.
The above graphic highlights illustrative use cases in each category.
For more details download NASSCOM’s full report on AI in Retail here
Photo sources used in the graphic: Chatbots Magazine, Getty Images, Towards Data Science
In case you are looking for some use cases that will help you amidst the pandemic. You should also checkout our recent article on #TechFightsCOVID: 10 AI use cases to help retail enterprises amid COVID-19
The pandemic has affected MSMEs the most, and technology can help them get back on their feet. The critical factors that MSMEs consider while implementing AI uses cases are cost effectiveness, ease of implementation, high business impact and low business risk.
Some Illustrative Priority use cases for MSMEs – customer service chatbot, theft detection, smart vending machine, personalised marketing and shopping assistant
Our full report on Indian retail: AI imperative to data-led disruptive growth provides further details of these use cases, AI in retail ecosystem and bold plays for retailers to traverse the AI maturity curve.
Watch out for more interesting articles.