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1
© IDC |
Redefining Intelligence
Exploring the latest advances in next-generation AI and
ML algorithms for retail
Ananda “Andy” Chakravarty
VP Research, IDC Retail Insights
7/11/2023
2
© IDC |
Agenda
Retail Currency
AI is a Catalyst
Next Generation – Generative AI
Retail AI Future
3
© IDC |
Data is Retail Currency
Retail is merchandising. Managing data drives business outcomes
Note: These estimates are subject
to maturity of the business, retail
business model , type of retail
vertical and independent business
operations.
4
© IDC |
Data is Retail Currency
Source: Future Enterprise Resiliency & Spending Survey Wave 2, IDC,March, 2023
Retailers have wide disparity in managing data
5
© IDC |
Data is Retail Currency
2022 2026
Source: Worldwide IDC Enterprise Global Datasphere by Vertical Industry Forecast 2021-2026
CAGR 26.9%
Retail Data Volume
4000 EB
14000 EB
Time
Rule Based
Manual Automated
Automated,
Prioritized
AI/ML
Retail Data is massive and discordant. Retailers must move
from manual to AI-based data management.
6
© IDC |
AI is a Catalyst for Data Use
Source: IDC Report – An Intelligence Driven Theory of Retail US45840120 November 2022
87% of Retailers already use Artificial Intelligence.
Retail Artificial Intelligence
Machine Learning
Kinetic Robotics
Cognitive Processing
Computer Vision
Deep Learning
RPA
Rule-Based Expert Systems
Predictive Ordering & Management
25% Food Waste
3% Sales
Vector Product Search
2MM Products Online
35K Products per Store
7
© IDC |
AI is a Catalyst for Data Use
Source: IDC’s Worldwide Artificial Intelligence Spending Guide, March 2023 – Retail only
Retailers continue to spending on AI and it continues to grow
$19 B
Retail AI Spending
AI is very real..
Fahim Siddiqui, EVP &
CIO Home Depot
8
© IDC |
Next Generation AI : Generative AI
Algorithms that can develop new content based on input
characteristics and a body of training knowledge.
Generative AI will
be transformative.
Andy Jassey,
Amazon CEO
Speech &
Audio
Images &
Video
Text &
Language
Multi-Modality
Google’s LaMDA & Github Copilot
Facebook LLaMa
OpenAI’s ChatGPT & Dall-E
Midjourney
Well Known Models
BERT GPT
Encoder Decoder
Foundational Models
9
© IDC |
Generative AI : Design Characteristics
Human-Machine understanding
Interface
Developed across unstructured
and semi-structured data
Unstructured Data
Text, Images, Audo, Video
generation & interpretation
Multi-Modal
Fixed, Large body of knowledge,
Knowledge Base
Automated content generation
Generative
10
© IDC |
Next Generation AI : Generative AI
Source: Future Enterprise Resiliency & Spending Survey Wave 2, IDC,March, 2023
There’s been a shift – Generative AI changes the playing
field, leaving a retail opportunity – but few have jumped in
Ultimately, AI is
something that
we cannot afford
to ignore,
Michael Miebach,
Mastercard CEO
11
© IDC |
Generative AI : Challenges for Retail
Works well with language, poor
results with numbers or risk
Language Based
AI is invisible to retail teams,
automated and autonomous
Invisible AI
Existing AI Tech is already
effective, no new system training
Incumbent Tech
Most retail apps are specific and
fine-tuned (not GenAI)
Specific Apps
Vendor SaaS include state-of-the-
art Gen AI modeling
Vendor Support
Most retailers are looking to buy
off-the-shelf than build in-house
Retailers Buy
Hallucinations exist, though
human-in-the-loop and other
measures can mitigate
Bias & Falsification
12
© IDC |
Generative AI : Incremental Retail Applications
Customer Experience
▪ Chatbots – NLP human-
machine interaction
▪ Customer Service
Routing/call ctr mgt
▪ Net Promoter/CSAT score
encapsulation
▪ Product fitting
▪ Live Shopping Assist
Marketing
▪ Auto marketing content
generation, both copy and
images
▪ Personalized marketing
campaign and dynamic
promotions
▪ Real-Time coupon/
discount generation
▪ Consolidate UGC/reviews
Supply Chain
▪ Optimized procurement
▪ Auto-negotiation with
suppliers, vendor mgt,
RFP development.
▪ Delivery estimations,
costing and dynamic
shipping
▪ Multi-supplier
coordination, inventory
contingency planning
Discovery
▪ Data grounded search
functionality
▪ Product recommendation
generation, prioritization
and selection
▪ Web design and onsite
commerce flow
▪ Shopping Asst./ Concierge
Training & Enablement
▪ Auto-generated self-
service training modules
▪ Compliance and policy
training and data access
▪ Sales tracking to identify
propensity to purchase
Operations
▪ Synthetic Data generation
for training, and
eliminating cold-starts
▪ Store workflow/task mgt,
and shift scheduling
▪ In-store loss prevention,
video monitoring, fraud
▪ Dynamic digital signage
IT & Technology
▪ Automated online
translation/ localization of
products
▪ New code generation for
custom product design
▪ In-store environment and
safety monitoring tech
▪ Development copilot
▪ Personalized Real-Time
front-end/mobile Design
Planning & Merch.
▪ Visual merchandising,
matching customers to
product images/details
▪ Auto Assortment optim./
SKU rationalization
▪ Auto Space planning
based on customer data
▪ Auto-replenishment and
data driven allocation
▪ Analytic data Insights
33 Retail Use Cases
Chatbots
Live Shopping Assist
Auto Marketing
Content
Consolidated UGC
Data Grounded Search
Shopping Asst.
Opt. Procurement
13
© IDC |
Retail AI Future is Innovative, not Incremental
Source: Future Enterprise Resiliency & Spending Survey Wave 2, IDC,March, 2023
14
© IDC |
Market Examples -
Walmart’s recent Text To
Shop launch in April 2023
• Generative AI
• GPT-4
• Enables Conversational
AI capabilities
15
© IDC |
Market Examples-
• Automated detailed product
content generation
• > 45,000 cars at any time
• The pre-purchase research
capability also includes SEO.
• Over 60+ product teams use Gen
AI models without teams of data
scientists
• 11 years -> Hours
Source: CIO.com, Microsoft
“We would have had to have hired tens or maybe hundreds of content writers and taken years to
generate this content We were able to do this literally in a matter of hours.
Shamim Mohammad,
EVP & CITO Carmax
16
© IDC |
Market Examples -
Levi Strauss is working with Lalaland.ai to test AI generated models for adding
diversity and supplement actual model set
17
© IDC |
Market Examples-
• Ask Instacart leverages OpenAI’s ChatGPT
• Data grounded with its own catalog
• > 1B shoppable items
• > 80,000 Retail partner locations
Search Tool
Source: Photo courtesy of Instacart
18
© IDC |
Takeaways
The next gen AI will be revolutionary. As leaders, you need to think about
new, innovative applications for Gen AI in retail.
Future of Retail AI will not be incremental
Data Proliferation
Retail data is huge, and parsing through the data is a universal challenge
that only AI/ML can help humans solve.
Both predictive AI in back office functions and Generative AI
initially in consumer facing engagements will change the field.
AI Proliferation
IDC.com linkedin.com/company/idc twitter.com/idc blogs.idc.com
© IDC
Ananda “Andy” Chakravarty
Research VP, IDC Retail Insights
6/8/2023
achakravarty@idc.com

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Redefining intelligence: Exploring the latest advances in next-generation AI and ML algorithms for retail

  • 1. 1 © IDC | Redefining Intelligence Exploring the latest advances in next-generation AI and ML algorithms for retail Ananda “Andy” Chakravarty VP Research, IDC Retail Insights 7/11/2023
  • 2. 2 © IDC | Agenda Retail Currency AI is a Catalyst Next Generation – Generative AI Retail AI Future
  • 3. 3 © IDC | Data is Retail Currency Retail is merchandising. Managing data drives business outcomes Note: These estimates are subject to maturity of the business, retail business model , type of retail vertical and independent business operations.
  • 4. 4 © IDC | Data is Retail Currency Source: Future Enterprise Resiliency & Spending Survey Wave 2, IDC,March, 2023 Retailers have wide disparity in managing data
  • 5. 5 © IDC | Data is Retail Currency 2022 2026 Source: Worldwide IDC Enterprise Global Datasphere by Vertical Industry Forecast 2021-2026 CAGR 26.9% Retail Data Volume 4000 EB 14000 EB Time Rule Based Manual Automated Automated, Prioritized AI/ML Retail Data is massive and discordant. Retailers must move from manual to AI-based data management.
  • 6. 6 © IDC | AI is a Catalyst for Data Use Source: IDC Report – An Intelligence Driven Theory of Retail US45840120 November 2022 87% of Retailers already use Artificial Intelligence. Retail Artificial Intelligence Machine Learning Kinetic Robotics Cognitive Processing Computer Vision Deep Learning RPA Rule-Based Expert Systems Predictive Ordering & Management 25% Food Waste 3% Sales Vector Product Search 2MM Products Online 35K Products per Store
  • 7. 7 © IDC | AI is a Catalyst for Data Use Source: IDC’s Worldwide Artificial Intelligence Spending Guide, March 2023 – Retail only Retailers continue to spending on AI and it continues to grow $19 B Retail AI Spending AI is very real.. Fahim Siddiqui, EVP & CIO Home Depot
  • 8. 8 © IDC | Next Generation AI : Generative AI Algorithms that can develop new content based on input characteristics and a body of training knowledge. Generative AI will be transformative. Andy Jassey, Amazon CEO Speech & Audio Images & Video Text & Language Multi-Modality Google’s LaMDA & Github Copilot Facebook LLaMa OpenAI’s ChatGPT & Dall-E Midjourney Well Known Models BERT GPT Encoder Decoder Foundational Models
  • 9. 9 © IDC | Generative AI : Design Characteristics Human-Machine understanding Interface Developed across unstructured and semi-structured data Unstructured Data Text, Images, Audo, Video generation & interpretation Multi-Modal Fixed, Large body of knowledge, Knowledge Base Automated content generation Generative
  • 10. 10 © IDC | Next Generation AI : Generative AI Source: Future Enterprise Resiliency & Spending Survey Wave 2, IDC,March, 2023 There’s been a shift – Generative AI changes the playing field, leaving a retail opportunity – but few have jumped in Ultimately, AI is something that we cannot afford to ignore, Michael Miebach, Mastercard CEO
  • 11. 11 © IDC | Generative AI : Challenges for Retail Works well with language, poor results with numbers or risk Language Based AI is invisible to retail teams, automated and autonomous Invisible AI Existing AI Tech is already effective, no new system training Incumbent Tech Most retail apps are specific and fine-tuned (not GenAI) Specific Apps Vendor SaaS include state-of-the- art Gen AI modeling Vendor Support Most retailers are looking to buy off-the-shelf than build in-house Retailers Buy Hallucinations exist, though human-in-the-loop and other measures can mitigate Bias & Falsification
  • 12. 12 © IDC | Generative AI : Incremental Retail Applications Customer Experience ▪ Chatbots – NLP human- machine interaction ▪ Customer Service Routing/call ctr mgt ▪ Net Promoter/CSAT score encapsulation ▪ Product fitting ▪ Live Shopping Assist Marketing ▪ Auto marketing content generation, both copy and images ▪ Personalized marketing campaign and dynamic promotions ▪ Real-Time coupon/ discount generation ▪ Consolidate UGC/reviews Supply Chain ▪ Optimized procurement ▪ Auto-negotiation with suppliers, vendor mgt, RFP development. ▪ Delivery estimations, costing and dynamic shipping ▪ Multi-supplier coordination, inventory contingency planning Discovery ▪ Data grounded search functionality ▪ Product recommendation generation, prioritization and selection ▪ Web design and onsite commerce flow ▪ Shopping Asst./ Concierge Training & Enablement ▪ Auto-generated self- service training modules ▪ Compliance and policy training and data access ▪ Sales tracking to identify propensity to purchase Operations ▪ Synthetic Data generation for training, and eliminating cold-starts ▪ Store workflow/task mgt, and shift scheduling ▪ In-store loss prevention, video monitoring, fraud ▪ Dynamic digital signage IT & Technology ▪ Automated online translation/ localization of products ▪ New code generation for custom product design ▪ In-store environment and safety monitoring tech ▪ Development copilot ▪ Personalized Real-Time front-end/mobile Design Planning & Merch. ▪ Visual merchandising, matching customers to product images/details ▪ Auto Assortment optim./ SKU rationalization ▪ Auto Space planning based on customer data ▪ Auto-replenishment and data driven allocation ▪ Analytic data Insights 33 Retail Use Cases Chatbots Live Shopping Assist Auto Marketing Content Consolidated UGC Data Grounded Search Shopping Asst. Opt. Procurement
  • 13. 13 © IDC | Retail AI Future is Innovative, not Incremental Source: Future Enterprise Resiliency & Spending Survey Wave 2, IDC,March, 2023
  • 14. 14 © IDC | Market Examples - Walmart’s recent Text To Shop launch in April 2023 • Generative AI • GPT-4 • Enables Conversational AI capabilities
  • 15. 15 © IDC | Market Examples- • Automated detailed product content generation • > 45,000 cars at any time • The pre-purchase research capability also includes SEO. • Over 60+ product teams use Gen AI models without teams of data scientists • 11 years -> Hours Source: CIO.com, Microsoft “We would have had to have hired tens or maybe hundreds of content writers and taken years to generate this content We were able to do this literally in a matter of hours. Shamim Mohammad, EVP & CITO Carmax
  • 16. 16 © IDC | Market Examples - Levi Strauss is working with Lalaland.ai to test AI generated models for adding diversity and supplement actual model set
  • 17. 17 © IDC | Market Examples- • Ask Instacart leverages OpenAI’s ChatGPT • Data grounded with its own catalog • > 1B shoppable items • > 80,000 Retail partner locations Search Tool Source: Photo courtesy of Instacart
  • 18. 18 © IDC | Takeaways The next gen AI will be revolutionary. As leaders, you need to think about new, innovative applications for Gen AI in retail. Future of Retail AI will not be incremental Data Proliferation Retail data is huge, and parsing through the data is a universal challenge that only AI/ML can help humans solve. Both predictive AI in back office functions and Generative AI initially in consumer facing engagements will change the field. AI Proliferation
  • 19. IDC.com linkedin.com/company/idc twitter.com/idc blogs.idc.com © IDC Ananda “Andy” Chakravarty Research VP, IDC Retail Insights 6/8/2023 achakravarty@idc.com