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Home » As Retailers Embrace Generative AI, Lack of Data Strategy Presents Challenges

As Retailers Embrace Generative AI, Lack of Data Strategy Presents Challenges

Peter Oluka by Peter Oluka
March 25, 2024
in Commerce
0
Retailers Embrace Generative AI, Lack of Data Strategy
Retailers and Generative AI -

Retailers and Generative AI -

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A new report from Salesforce and the Retail AI Council finds global retailers are quickly adopting generative AI to personalise and improve in-store and online shopping experiences.

However, nearly half of the 1,300 retailers surveyed are struggling to make their data accessible, and just 42% are connecting their various data silos, which can lead to ineffective or inaccurate AI outputs.

Generative AI is expected to have a $9.2 trillion impact on the retail sector by 2029 as retailers see the benefit of implementing this technology to streamline operations, increase productivity, and deliver more personalised experiences for shoppers and associates.

However, just 13% of customers completely trust companies to use AI ethically, and 63% are concerned about bias in AI outputs.

Salesforce perspective

“The AI revolution is about data, trust, and customer experience. Looking at artificial intelligence in isolation, without understanding these elements as a package, will hurt a retailer’s ability to build loyalty and improve customer relationships. This research we’re announcing today aims to help retailers better understand the need for a unified data strategy, the practical applications of generative AI and how that can be used to enhance the experience for both shoppers and associates,” says Linda Saunders, salesforce director solutions engineering Africa.

Retailers are eyeing generative AI for personalisation and customer service use cases

The retail industry isn’t shying away from AI adoption.

  • Retail executives surveyed estimate that 36% of their employees are already using generative AI today, with that number expected to grow to 45% by the end of 2025.
  • 93% of these retailers state they are already using generative AI for some sort of personalisation, such as personalised email copy and product recommendations.
  • 81% of respondents also report having a dedicated AI budget, with an average of 50% of that assigned to generative AI.
  • The top three areas where these retailers plan to use generative AI are customer service, marketing, and store operations.
    • Retailers are prioritising customer service use cases, with a desire to augment agents with highly personalised, automated messages and content to send to customers quickly.
    • After customer service, the second most important use case for retailers is creating conversational digital shopping assistants to help shoppers find the right product or service.
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Retailers struggle with data strategies to support effective generative AI

Retailers understand the importance of data, according to the survey, but many are still working through how to unify all of their data and build a single view of their customers to unlock more effective generative AI outputs.

  • Only 17% of respondents reported having a complete, single view of their customers and harnessing their data effectively. Forty-nine percent are still in the preliminary stages of building or even considering the creation of a complete customer data profile.
  • The inability to harmonise and manage data means that a retailer’s generative AI model could deliver ineffective or inaccurate results, or responses laced with toxicity and biases. Even though 67% of retailers say they are fully able to capture customer data, only 39% say they are fully able to clean that data, and just 42% say they are fully able to harmonise it.
  • Many retailers are also struggling with using their data for making decisions (40%) and making their data accessible (47%), indicating many retailers have a significant amount of siloed data not being leveraged for effective generative AI outputs.

Trust, ethics increasingly critical to generative AI adoption

Retailers are aware of the security and trust risks surrounding generative AI. Fortunately, they’re ready to address them and are already taking steps to do so.

  • Fifty percent of retailers surveyed say they have the ability to fully comply with data security standards and data privacy regulations.
  • Retailers cite bias, when AI algorithms produce prejudiced results or responses, as the top risk in using generative AI — with half of respondents noting this was a concern for them. In addition to bias, retailers see hallucinations (38%) and toxicity (35%) as large risks.
  • 62% report having guidelines to address transparency, data security, and privacy, when it comes to the ethical use of generative AI in technology, as well as commitments around trustworthy and unbiased outputs.

The Retail AI Council perspective:  

“In today’s retail landscape, AI isn’t just changing the game; it’s reshaping the entire playbook. It isn’t only a backstage assistant to merchants; it’s also the emerging co-star in the customer’s shopping journey. AI is now the imperative for anticipating needs, tailoring experiences, and transforming shopping from a transactional chore into a personalized and evolving adventure,” Jenna Posner, CDO of Solo Brands and Vice Chair of Retail AI Council.

Summary:

  • Retailers are eyeing generative AI for personalisation and customer service use cases: 93% of retailers surveyed state they are already using generative AI for personalization, prioritising customer service use cases as a top area for implementation.
  • Retailers struggle with data strategies to support effective generative AI: Only 17% of respondents reported having a complete, single view of their customers and harnessing their data effectively. 49% are still in the preliminary stages of building or even considering the creation of a complete customer data profile.
  • Trust, ethics increasingly critical to generative AI adoption: 50% of retailers surveyed say they have the ability to fully comply with data security standards and data privacy regulations. but cite bias as the top risk in using generative AI.

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  • Peter Oluka
    Peter Oluka

    Peter Oluka (@peterolukai), editor of Techeconomy, is a multi-award winner practicing Journalist. Peter’s media practice cuts across Media Relations | Marketing| Advertising, other Communications interests. Contact: peter.oluka@techeconomy.ng

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Peter Oluka

Peter Oluka

Peter Oluka (@peterolukai), editor of Techeconomy, is a multi-award winner practicing Journalist. Peter’s media practice cuts across Media Relations | Marketing| Advertising, other Communications interests. Contact: peter.oluka@techeconomy.ng

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