2. Generative AI - Explained
âą In simple terms it can be thought of as a kind of smart computer
program that's really good at creating new things.
âą Imagine you have a magic art box that can draw new pictures or write
stories all by itself when you ask it to.
âą This art box uses what it has learned from looking at lots of other
pictures and stories to make something new and different each time
3. đ Generative AI's Rising Demand
âą 77% of Executives' Endorsement: Recognized as a pivotal technology
to boost productivity and collaboration.
âą Operations as a Priority: Over half the executives see immediate
opportunities in operational deployment.
âą
* KPMG - Supply chain leaders consider generative AIâs potential (2023)
4. đ€ AI-Powered Efficiency & Enhancing
Customer Service : Utilize generative AI
to enhance interactions across
partners, assets, and inventory.
5. 1ïžâŁ Network Service
Collaboration
đ Case Study:
A global sustainable energy specialist implemented
generative AI in their customer service platform to assist
teams in drafting detailed and effective email responses.
âą This AI application led to an 18% increase in customer
happiness scores compared to emails written solely by
humans. The AI system now responds to a third of all
customer inquiry emails, freeing up agents to focus on
more complex tasks.
6. âïž Optimizing Complex Processes:
Implement generative AI for policy and
procedure optimization across supply
chain functions.
7. 2ïžâŁ Operations Excellence
and Improvement
đ Case Study: A case study involving BMW highlights how
Industrial Generative AI was applied to optimize their
manufacturing plant scheduling to meet production targets
while minimizing idle time
âą BMW worked with Zapata AI to employ a technique
called Generator-Enhanced Optimization (GEO), which
outperformed traditional state-of-the-art optimization
solvers in 71% of problem configurations
9. 3ïžâŁ Product and Inventory
Evaluation
đŠ Case Study: Logistics companies like DHL are leveraging
generative AI for dynamic route optimization, considering
real-time data such as traffic conditions and weather
âą DHL has launched a powerful algorithm for optimizing
delivery routes and stop sequences that can save up
to 20% in costs compared to standard route
optimization solutions
10. đ Key Success Factors
âąValue, Scalability, Adoption: Focus on
these principles for effective generative
AI implementation.
âąOvercoming Barriers: Address strategy,
investment, and adoption challenges for
successful integration.