The document discusses the transformative potential of next-generation AI and machine learning algorithms in retail, emphasizing the crucial role of data management. It highlights that while most retailers are currently utilizing AI, the adoption of generative AI is still in early stages despite its capabilities to generate content and enhance customer experience. Retailers need to leverage AI for various applications, including customer service, marketing, supply chain management, and operational efficiency to navigate the vast volume of retail data.

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