#120- Retail and Wholesale business Tectonic shifts in Employment and automation- Digital Maturity Model in the Age of AI, IoT, and Robots

Sidhartha Sharma-Personal Views

Before the year 2015, SMART robots were still in the nascent stages of being developed, 5G did not exist, and there needed to be more mention of artificial intelligence and IoT.

A lot has changed over the last 8 years (2015–2023) and the next 3 YEARS will bring exponential disruption:

BCG
  1. COVID-19 happened- A pandemic that preponed the need to be digitally agile and automated by at least 5–10 years
  2. AI suddenly came back in day-to-day conversations as Generative AI
  3. E-commerce and logistics delivery network has been more or less mapped
  4. Consumer behavior shifted irreversibly in favor of online shopping
  5. Companies are employing robots full-time and even testing bi-pedal robots

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Grocery is the fastest-growing category in retail both online and offline

Retail’s Digital Arsenal: Technologies & Processes

To understand the concept better, let’s dive deeper:

Source: Wil Hunt and Steve Rolf, Artificial Intelligence and Automation in Retail (2022).

Technologies:

  • Sales and Customer Data: The cornerstone of any retail operation, capturing and analyzing sales and customer data can help tailor offerings and streamline operations.
  • Loyalty Cards and Memberships: Personalized offers, capturing spending habits, and building a customer-brand relationship.
  • Store Sensors & Remote-Sensing: Tracking in-store movements, stock levels, and even customer sentiment.
  • Cameras & CCTV: Beyond security, these tools offer insights into customer behavior and store hotspots.
  • Robots and Autonomous Vehicles: Used for inventory, delivery, and even customer service in some innovative retail spaces.
  • Mobile Devices and Wearable Tech: Enhancing the in-store experience, offering real-time deals, and serving as a personal shopping assistant.

Processes:

  • Networking, the Web, and IoT: Linking devices, stock, and even customers to create a fully integrated shopping experience.
  • Advanced Image Processing: For virtual dressing rooms or augmented reality shopping experiences.
  • Natural Language Processing: Chatbots, voice assistants, and automated customer service.
  • Machine Learning and AI: For predictive analytics, stock management, and personalized marketing.

Applications: Making Tech Tangible

The real potential of these technologies and processes is unlocked when they’re applied effectively in the retail space.

  • E-commerce and Outsourcing: Expanding market reach beyond brick-and-mortar stores.
  • Cashless/Contactless Payment Systems: Over 50% of consumers now prefer contactless payments, emphasizing safety and convenience.
  • Ordering, Inventory, and Stock Replenishment: Predictive analytics can foresee stock shortages or overages, optimizing inventory levels.
  • Work/Staff Planning and Scheduling: AI-driven tools can predict busy hours and schedule staff accordingly.
  • Task Allocation, Targets, and Rewards: Gamifying the retail environment for both customers and staff.
  • Surveillance and Monitoring Systems: Enhancing security and understanding customer pathways.
  • Predictive Marketing and Personalization: Offering promotions before the customer even realizes they want them.
  • Automated/Self-Service HR Transactions: Reducing overhead and administrative tasks.
  • Augmented/Virtual Reality & Product Visualization: Try before you buy — virtually. Perfect for online furniture or fashion retailers.
  • Counterfeit Detection: Ensuring product authenticity, especially in luxury goods.

Generative AI- Use cases in retail

Check this example of customer service in auto retail- booking a test car drive for a customer. The dealerships can leverage AI

Here are top 10 use cases of GEN AI in retail and wholesale:

  1. Personalized Shopping Experience: AI algorithms can analyze a customer’s purchase history and browsing behavior, offering tailored product recommendations, enhancing user experience, and driving sales.
  2. Virtual Try-Ons: AI-powered augmented reality tools allow customers to virtually “try on” clothing, jewelry, or makeup before making a purchase, especially useful for online shopping platforms.
  3. Price Optimization: AI can dynamically adjust prices based on factors like demand, inventory levels, competitor prices, and market trends, ensuring retailers stay competitive while maximizing profitability.
  4. Chatbots and Virtual Assistants: Retailers use AI chatbots for instant customer service, answering queries, providing product information, or helping with the checkout process 24/7.
  5. Inventory Management: AI can predict which products will be in demand, assisting retailers in optimizing stock levels, reducing carrying costs, and minimizing stockouts or overstock situations.
  6. Visual Recognition for Checkout: Some stores use AI-powered cameras and visual recognition systems to allow for automated and cashier-less checkouts, enhancing customer convenience.
  7. Fraud Detection: AI systems can analyze transaction patterns in real time to identify and flag potentially fraudulent activities, protecting both the business and its customers.
  8. Customer Sentiment Analysis: By analyzing online reviews, social media comments, and other user-generated content, AI can gauge customer sentiment, helping retailers address concerns and capitalize on positive feedback.
  9. Store Layout Optimization: AI can analyze in-store foot traffic patterns and customer behavior, suggesting changes to store layouts or product placements to maximize sales and enhance the shopping experience.
  10. Supply Chain Optimization: By predicting demand and analyzing external factors (like weather patterns or local events), AI can assist retailers in making informed decisions about distribution, warehousing, and transportation, ensuring timely delivery and cost-efficiency.

The adoption of these AI-powered tools and strategies can significantly enhance operational efficiencies, improve customer experiences, and drive growth for retailers in today’s competitive landscape.

Conclusion

The journey towards digital maturity in retail is ongoing and dynamic. With the rapid pace of technological advancements, retailers must remain nimble, open to innovation, and always customer-centric in their approach. It’s not just about the tools and technologies; it’s about creating memorable, efficient, and personalized shopping experiences.

By understanding and harnessing the power of the Digital Maturity Model, retailers can set themselves apart in a crowded market, driving both profit and customer loyalty.

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Regards,

Sidhartha Sharma

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Sidhartha Sharma- Future of AI,Tech,Digital & Data

~18+yrs Consulting- Amazon, AWS, McKinsey & BCG-Digital Strategy, Ecosystems & Ventures | EY| Start-Up| Platforms | AI | Author & TEDx Speaker. Views Personal