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Leveraging AI to Create Meaningful Insights and Visibility in Retail

AI prominence across the enterprise value chain

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  • Enterprise struggles to mature key AI capabilities as it entails a more significant level of development in all organization abilities to ensure success.
  • Business functions are looking for financial impact with AI, ML, deep learning and data science adoption to achieve cost and competitive advantage.
  • Transformation requires superior tech-stack artificial intelligence competencies, infrastructure technology, data management capabilities, forecasting tools and applications.
  • The organization needs a fully comprehensive strategy and infosec governance operating models to address evolving customers’ needs and to ramp up results.

Our Advice

Critical Insight

Enterprises are embracing AI and ML expertise to provide cost and competitive advantage creators across the business functions to enhance personalization, operations, and information security throughout the customer lifecycle. Businesses that embrace AI ML are likely to differentiate and gain market share.

Impact and Result

  • Identify how the best-in-class retailers are already reaping business benefits from adopting technology demands with artificial intelligence, etc.
  • Realize the effects of artificial intelligence that are being felt by all entities in the retail value chain.
  • Analyze the value chain to understand stakeholder pain points better and craft an AI or ML use-case around them to ramp up results.
  • Recognize cost and competitive opportunities across the enterprise to capitalize on the AI, ML, deep learning, and data science environments to monetize key customer insights.

Leveraging AI to Create Meaningful Insights and Visibility in Retail Research & Tools

1. Leveraging AI to Create Meaningful Insights and Visibility in Retail Storyboard - AI prominence across the enterprise value chain.

This storyboard analyzes artificial intelligence technology adoption cases across the enterprise ecosystem. Additionally, it provides awareness and readiness on how retailers can capitalize on evolving technologies to realize “Leveraging AI to create meaningful insights and visibility.”

Leveraging AI to Create Meaningful Insights and Visibility in Retail Storyboard
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Leveraging AI to Create Meaningful Insights and Visibility in Retail


Analyst Perspective

Artificial intelligence prominence across the enterprise value chain

Rahul Jaiswal, Principal Research Director for Retail, Info-Tech Research group

Rahul Jaiswal

Principal Research Director, Retail

Info-Tech Research Group

The retail industry has been at the forefront of digital transformation for several years. It has noticeably increased speed, operation efficiency, and accuracy across every business segment due to a data surge and predictive analytics systems serving brands to make data-driven business decisions.

In retail, artificial intelligence enables businesses with high-level data and information to be leveraged into improved operating models and new business opportunities. As technology evolves, organizations increasingly seek to understand how artificial intelligence will provide value and reshape the industry ecosystem to provide contextual personalization seamlessly across channels and ensure information security measures.

Leading brands are leveraging artificial intelligence (AI) at various stages to create meaningful customer insights and provide infosec effectiveness as global ransomware costs its victims millions of dollars. Moreover, consumers report that digital trust matters; many will shop elsewhere when businesses don't deliver a secure environment.

As AI applications integrate into various business functions, envision business capability components, costs, and competitive advantage creators in harmony with AI services for retail streams.

Executive Summary

Your Challenge

  • Enterprises struggle to mature key AI capabilities as they entail a more significant level of development in all organization abilities to ensure success.
  • Business functions are looking for financial impact with AI, ML, deep learning, and data science adoption to achieve cost and competitive advantage.
  • Transformation requires superior tech-stack artificial intelligence competencies, infrastructure technology, data management capabilities, forecasting tools, and applications.
  • Need a fully comprehensive strategy and infosec governance operating models to address evolving customers’ needs and ramp up results.

    • Common Obstacles

  • Leaders have an ambiguous understanding of AI, ML and their benefits, let alone how it they impacts an organization.
  • Businesses are reluctant to execute artificial intelligence, which is the key to the success of the cost and competitive organization strategy.
  • Line of businesses (LOBs) struggle to begin and ramp-up. Business teams do not take a structured approach to execute technology in each phase and deploy technology before developing a robust strategy.
  • Prioritizing the demand for AI programs and governing the projects to prevent the overloading of resources.

    • Info-Tech's Approach

  • Discover how the best-in-class retailers are already reaping business benefits from adopting technology demands with artificial intelligence.
  • Realize the effects of artificial intelligence that are being felt on all entities of the retail value chain.
  • Analyze the value chain to understand stakeholder pain points better and craft an AI or ML use case around them to ramp up results.
  • Recognize cost and competitive opportunities across the enterprise to capitalize on the AI, ML, deep learning, and data science environments to monetize key customer insights.

    • Info-Tech Insight

    Enterprises are embracing AI and ML expertise to provide cost and competitive advantage across business functions to enhance personalization, operations, and information security throughout the customer lifecycle. Businesses that embrace AI and ML are likely to differentiate and gain market share.

    AI is a modus operandi that mimics human behavior

    Artificial intelligence (AI) is a multidisciplinary research field aiming to make machines intelligent. Applied to specific tasks like computer vision, speech recognition, and language translation, AI has advanced exponentially in the last few years.

    Info-Tech Insight

    Scaling artificial intelligence can generate an enormous cost and competitive expansion.

    Ven Diagram showing Artificial intelligence applied to computer vision, deep learning, natural language processing and cognitive computing.

    As technology evolves, retail organizations increasingly seek to understand how artificial intelligence will reshape the industry

    Current state

    • The worldwide artificial intelligence in retail was estimated at $4.84 billion USD in 2021.
    • Machine learning accounted for around 39.7% ($1.92 billion) of the global artificial intelligence in retail market in 2020.

    Automation: Retailers are rapidly executing AI expertise to enhance intelligent automation in retail stores. The technology empowers retail brands to drive online automation to offline services and contextual personalization, adopting AI-based automation to increase YOY. Thus, retailers will likely invest more to understand customer preferences and cost optimization to drive value (e.g. Amazon Go).

    Graph showing regional Global AI in retail market. 38.6% in North America and 61.4% in the rest of the world Global AI in Retail Market (USD billion) shows increase CAGR of 30.5% from 2021 to 2028

    Future state

    • AI services in the retail sector are predicted to rise from $5 billion to above $31 billion by 2028 (WEF at DAVOS, 2023)
    • AI-as-a-service (AIaaS ) and ML-as-a-service (MLaaS) models will become prevalent because of their convenience, cost-effectiveness, relative ease, and security of carrying out implementations.
    • Sustainability: Consumer retail is expected to have the most significant sustainability potential for AI-driven improvement use cases at 45 percent emissions intensity (EEI) reduction by 2030.

    Automation: Retailers are rapidly executing AI expertise to enhance intelligent automation in retail stores. The technology empowers retail brands to drive online automation to offline services and contextual personalization, adopting AI-based automation to increase YOY. Thus, retailers will likely invest more to understand customer preferences and cost optimization to drive value (e.g. Amazon Go).

    AI's contribution as a share of EEI reduction. Consumer Retail at 0.45, Utilities at 0.32, Automotive at 0.22, Oil and gas at 0.18, and Wholesale Retail at 0.11

    Sources: World Economic Forum, 6 Jan. 2023. Cision PR Newswire. 23 Jan 2020. Fortune Business Insights, 16 Nov. 2021.

    Leveraging AI to Create Meaningful Insights and Visibility in Retail visualization

    AI prominence across the enterprise value chain

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    Author

    Rahul Jaiswal

    Contributors


    • Rajiv Shankar, Chief Information Officer, REDTAG
    • Naomi Jackson, Chief Financial Officer, Goodwill Industries North Florida
    • Anitha Reddy, Vice President of Software Engineering at Qurate Retail Group
    • Prabhu Sundararajan, Director IT at Qurate Retail Group
    • Laura Becker, Enterprise Architect at Qurate Retail Group
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