When Artificial Intelligence (AI) meets 3 retail industry pain points

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Artificial intelligence (AI) solutions can help the retail industry not just survive in today’s challenging economy but thrive in a post-pandemic world. Consider these three timely examples

AI retail- At the beginning of 2020, artificial intelligence (AI) was predicted to become what some experts called a “key ingredient” technology across many industries over the next decade.

Fast-forward to today, and interest in AI is surging even more. As we are now deeply entrenched in the COVID-19 pandemic, the need to enhance manual business processes with more automation through AI has hit many industries with urgency, but especially retail. About two-thirds of executives surveyed by McKinsey in June said they had accelerated the implementation of robotics, artificial intelligence, and other emerging technologies in response to COVID-19.

The retail industry has a unique opportunity to learn from consumer behavior this year and implement AI solutions that can meet shoppers’ needs in the long term. From enhancing store intelligence to real-time inventory management, AI has the power to help companies withstand further shifts.

However, implementing AI brings challenges. Many organizations look to AI for its promising efficiency gains, only to find they lack the basic automation, product identification, and data quality best practices that are essential for success.

Step one for many retail CIOs exploring AI is to leverage global data standards in their business processes to support digital transformation, as these provide a necessary bridge between the physical product and the data associated with it.

Here are three ways retail CIOs can leverage AI in combination with standardized, structured data to solidify their relevance, even after COVID-19 is no longer a driving force in the economy.

1. Supporting consumers with useful data

Retail CIOs can use AI to meet consumers where they feel most comfortable. The physical and digital shopping experiences are merging, creating an opportunity to provide consumers with the data they need to shop safely and efficiently.

Even as online sales of grocery delivery and pickup in the U.S. have surged from $1.2 billion in August 2019 to $7.2 billion U.S. in June 2020, according to Statista, the vast majority of grocery shopping still takes place in traditional brick-and-mortar grocery stores. Consumers now want to make the most of fewer shopping trips with as little contact as possible. This presents retailers and brands with a way to extract more valuable data from consumers to create future engagement opportunities.

For example, a startup called Locai uses artificial intelligence to parse recipes for ingredient information, enabling consumers to plan meals more easily by finding the items they need online and in store. AI that anticipates consumer needs and makes it easier to move between digital and in-store experiences will continue to grow, as long as the data being served up to consumers is accurate and complete.

2. Analyzing demand patterns

CIOs can use AI to analyze demand patterns and ensure consumers have what they want, when they want it. The pandemic has caused consumers to try new brands and stores that they had never tried before – 75 percent of Americans had changed how they shop as a result of the pandemic, according to the June McKinsey consumer sentiment study. Retailers and brands are leveraging new solutions to analyze store activity and help automate processes like on-shelf availability to keep up with pantry-loading shoppers.

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Article Credit: The Enterprisers Project