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#RetailTech: AI use case landscape in retail – Guide to start your AI journey

Blog: NASSCOM Official Blog

9 out of 10 retail enterprises who implemented AI are still not entirely satisfied with their AI implementations

Globally, retail organisations are at varying levels of AI adoption across the value chain segments. Very often, enterprises that are starting their AI journey, quickly jump to an assumed end state and start working on a use case without completely understanding feasibility and/or resultant benefits.

This results in enterprises facing one or more of the following scenarios:

To avoid this common pitfall, our recently launched report on Indian retail: AI imperative to data-led disruptive growth proposes a unique way of highlighting AI uses cases in retail through a periodic table. It provides spectrum of use cases in retail industry solving specific value chain challenges that will help enterprises understand the landscape, application areas and come up with an action plan for AI.

The research also highlighted that globally, popular enterprise focus areas for AI implementation in retail comprise Customer experience, In-store and on-line operations and Distribution and logistics (specifically as a fallout of COVID-19)

Download our report here for accessing the full periodic table and instructions to interpret and use it

Here are some illustrative use cases that are amongst the most popular AI use cases implemented by retailers globally across each of the value chain segments

Retailers have been successfully deploying these popular AI use cases globally, as highlighted in the above examples. Increasingly, new areas in customer services and in-store and online operations are emerging as AI hotspots apart from operations focused solutions. The basic premise of these new areas of AI solutions is to improve customer experience, reduce customer churn and increase the top line of the enterprise. Enterprises are required to invest in AI solutions that specifically target their weakest performing areas across value chain to benefit from the efficiency gains and financial impact.

Feel free to reach out to me for any queries/suggestions. Watch out for our next article on how to prioritise the right use cases with our unique use case prioritisation matrix.

To access the full periodic table and detailed use cases download our full report: https://tinyurl.com/y9johts2

References

[1] https://www.forbes.com/sites/rachelarthur/2018/01/15/ai-ibm-tommy-hilfiger/#15df2a1978ac

[2] https://www.forbes.com/sites/bernardmarr/2019/04/26/the-amazing-ways-ebay-is-using-artificial-intelligence-to-boost-business-success/#736b9d682c2e

[3] https://community.nasscom.in/communities/emerging-tech/ai/hows-ai-making-business-more-profitable-dynamic-pricing.html

[4] https://www.infosys.com/insights/ai-automation/documents/moving-goalposts.pdf

[5] https://go.vue.ai/hubfs/resources/tata-cliq-report-2020.pdf

[6] https://digital.hbs.edu/platform-rctom/submission/ai-chatbot-behind-alibabas-31-billion-singles-day-sales-miracle/

[7] https://www.nasscom.in/knowledge-center/publications/indian-retail-ai-imperative-data-led-disruptive-growth

The post #RetailTech: AI use case landscape in retail – Guide to start your AI journey appeared first on NASSCOM Community |The Official Community of Indian IT Industry.

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