Cracking AI Black Box - Strategies for Customer-centric Enterprise Excellence

The democratization of Generative AI is ushering in a new era of innovation for enterprises. Discover how you can harness this powerful technology to deliver unparalleled customer value and securing a formidable competitive advantage in today's competitive market. In this session, you will learn how to:
- Identify high-impact customer needs with precision
- Harness the power of large language models to address specific customer needs effectively
- Implement AI responsibly to build trust and foster strong customer relationships

Whether you're at the early stages of your AI journey or looking to optimize existing initiatives, this session will provide you with actionable insights and strategies needed to leverage AI as a powerful catalyst for customer-driven enterprise success.

1. Quentin Reul,
Ph.D.
Cracking the AI Black Box
Strategies for Customer-centric Enterprise Excellence
?????? Jul 16, 05:30 PM CDT
?????? Illinois Institute of Technology

2. Cracking the AI Black Box
Strategies for Customer-centric Enterprise Excellence
AI Camp Meetup (Chicago) -
July 16th, 2024
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Credit: DALL-E 3 by Microsoft Copilot

3. ●Academic Background
○Ph.D. in Computing Science from Aberdeen University (Scotland)
■Leveraged Semantic Technologies to facilitate inter-department data integration
■Introduced an approach to map entities across semantic schemas (Thesis)
■Contributed to the development of W3C standards

●Work Experience
○Track record of leveraging AI to address customer needs across different industries .
○Guide companies in deploying AI solutions, emphasizing customer-centric and iterative strategies.
○Drive innovation to achieve competitive advantage while adhering to ethical and responsible principles.
○Cultivate a culture of experimentation, continuous improvement, and rapid innovation within teams.
○Skilled at translating complex AI concepts into tangible business value for diverse stakeholders.
○Recognized for the deployment of multiple impactful AI solutions across various domains
Who am I?
Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence 3

4. Agenda
●Introduction
●Finding the Needle in the Haystack
●The Right Fit for the Job
●From Launch to Longevity
●Building AI Solutions Responsibly
●Key Takeaways
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence

5. What is Generative AI?
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Credit: DALL-E 3 by Microsoft Copilot
Source: What is generative AI? McKinsey & Company
Generative AI is a branch of AI that focuses
on creating entirely new content. This
content can come in many forms, including
text, images, audio, and even videos.

6. How Generative AI is Transforming Industries?
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Source: The economic potential of generative AI: The next productivity frontier
75% of Generative AI value focuses on:
-Customer Operations
-Marketing & Sales
-Software Engineering
-Research & Development

7. How Generative AI is Transforming Industries?
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Credit: DALL-E 3 by Microsoft Copilot
Source: How Generative AI Is Revolutionizing Customer Service, Forbes, January 26 2024
Octopus Energy build a conversational AI into
its customer service channels and reported that
it does the work of 250 people and receives
higher customer satisfaction rating.

8. Agenda
●Introduction
●Finding the Needle in the Haystack
●The Right Fit for the Job
●From Launch to Longevity
●Building AI Solutions Responsibly
●Key Takeaways
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence

9. Find Your Ideal Customer Partners
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Source: The Power of "Jobs-to-be-Done" in Crafting Winning AI Solutions
Credit: Diffusion of Innovation
The diffusion of innovation theory explains how new
ideas, technologies, or products spread and gain
acceptance within a social system or market over time.

10. Uncover Customer Needs
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Credit: Jobs To Be Done Framework
The jobs-to-be-done framework is an approach to
product development that focuses on understanding
the underlying motivations and goals that drive
customers to use a product or service.
Source: The Power of "Jobs-to-be-Done" in Crafting Winning AI Solutions

11. Uncover Customer Needs
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Methods to identify customer needs:
-Talk directly with customers
-Ask with surveys
-Study your competitors
Credit: DALL-E 3 by Microsoft Copilot
Source: A Better Way to Think About Your Business Model, HBR, May 06, 2013

12. Validate Early, Iterate Often
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
The Lean startup method is a
customer-centric approach to
developing products. It emphasizes
gathering early feedback through
rapid iterations to validate
product ideas and minimize waste.
Source: Lean Startup: How the lean method works

13. Agenda
●Introduction
●Finding the Needle in the Haystack
●The Right Fit for the Job
●From Launch to Longevity
●Building AI Solutions Responsibly
●Key Takeaways
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence

14. The Right Fit for the Job
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Credit: DALL-E 3 by Microsoft Copilot
Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Source: Generative AI & Human Abstract Thinking, Medium, June 17, 2023

15. Large Language Models (LLMs) Wild West

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Source: Yang, et al. Harnessing the Power of LLMs in
Practice: A Survey on ChatGPT and Beyond, 2023
Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Notable LLM Releases in 2024 Q2
●March:
○Databricks DBRX
●April:
○Mistral AI Mixtral
○Meta Llama 3
○Microsoft Phi-3
●May:
○OpenAI GPT-4o
○Google Gemini 1.5 Flash
●June:
○Anthropic Claude 3.5 Sonnet

16. Evaluating LLMs for Fitness
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Source: Artificial Analysis, Comparison of Models: Quality, Performance & Price Analysis,
Retrieved 15 July, 2024
Benchmarks play a crucial role in
comparing the performance and
capabilities of different LLMs.

17. Don't Get Blinded by the Shine
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●Potential of overfitting: Training data
may include knowledge of benchmark
●Limited Task Diversity: Benchmarks
cover limited set of tasks
●Rapid model evolution: Benchmarks
don’t evolve as same speed as models
●Narrow focus: Don’t assess specific
knowledge required for your industry
Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Credit: DALL-E 3 by Microsoft Copilot

18. TechType Rocket: A Practical Example
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
TechType Rocket© helps authors with
overcoming the “blank page”
syndrome. It also includes guardrails to
ensure that the input and output does not
contain toxic content.

19. TechType Rocket: A Practical Example
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Source: It' Official Gemini Advanced Admits It Can't Count - Reddit

20. Agenda
●Introduction
●Finding the Needle in the Haystack
●The Right Fit for the Job
●From Launch to Longevity
●Building AI Solutions Responsibly
●Key Takeaways
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Cracking the AI Black Box:
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21. Adapting to a Changing World
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Cracking the AI Black Box:
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Access to new / updated training data is
necessary to expand the capabilities and the
knowledge of LLMs.
Credit: DALL-E 3 by Microsoft Copilot

22. Adapting to a Changing World
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Cracking the AI Black Box:
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Changes in customer expectations and
regulatory requirements have forced
companies to implement stringent training
data policies.
Credit: DALL-E 3 by Microsoft Copilot

23. Adapting to a Changing World
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Cracking the AI Black Box:
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With the rapid evolution of the Generative AI
landscape and the lack of transparency in
training data, challenges in the assessment of
performance and efficiency of LLMs over
time have been introduced.
Credit: DALL-E 3 by Microsoft Copilot

24. Monitoring Model Drift
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Credit: DALL-E 3 by Microsoft Copilot
Rigorous monitoring is crucial to detect
issues like performance drift caused by
different versions of LLMs.

25. Agenda
●Introduction
●Finding the Needle in the Haystack
●The Right Fit for the Job
●From Launch to Longevity
●Building AI Solutions Responsibly
●Key Takeaways
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence

26. Credit: DALL-E 3 by Microsoft Copilot
AI with a Conscience
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Source: Don't Get Left Behind: Why Responsible AI is the Key to Customer Success
Responsible AI refers to the practice of
developing and deploying AI systems in an
ethical, transparent, and accountable
manner, while mitigating potential risks
and negative impacts.

27. A Framework for Sustainable Growth
The main pillars of Responsible AI are:
●Fairness: Treat all customers fairly,
without discrimination or unfair bias
●Transparency & Explainability: Be
opened about the algorithms, data used
●Accountability & Reliability: Maintain
detailed audit trails of interactions
●Privacy & Security: Safeguard data to
prevent data breaches and misuse

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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Source: Don't Get Left Behind: Why Responsible AI is the Key to Customer Success
Credit: DALL-E 3 by Microsoft Copilot

28. Putting Responsible AI into Action (Voluntary)
●NIST AI Risk Management Framework
provides guidelines to identify,
assess, and manage risks
●OECD AI Principles promote the
development and use of trustworthy
AI systems that respect human rights
and democratic values
●Experts from 27 nations, including the
UK government, have published an
interim report on safety of advanced
AI to minimize severe risks.
●AI 2030 promotes the development and
adoption of Responsible AI systems
that benefit humanity while
minimizing potential negative
impacts

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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Credit: DALL-E 3 by Microsoft Copilot

29. Putting Responsible AI into Action (Regulatory)
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Minimal
Source: EU AI Act - Regulation 2024/1689 RISK
Limited
High
Art 5.
Art 6.
Art 52.
Art 69.
Minimal
Credit: DALL-E 3 by Microsoft Copilot

30. Putting Responsible AI into Action (Regulatory)
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Cracking the AI Black Box:
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TN ELVIS Act protects artists from having their
voices and pictures used in AI.
CO SB24-205 establishes comprehensive regulations
for the development and deployment of high-risk AI
systems in Colorado.
CA Executive Order N-12-23 outlines a plan for the
responsible development and use of AI through
conducting risk assessments within state government.

31. Putting Responsible AI into Action (Regulatory)
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
At the Federal level, the United States currently does
not have a comprehensive federal law specifically
governing the integration of AI in solutions.
The COPIED Act will prohibit companies to use
unauthorized content and to require provenance
information to be attached to content.
Generative AI Copyright Disclosure Act of 2024
proposes the disclosure of copyrighted material
used to train models
, but some have been
introduced in U.S. Congress.

32. Agenda
●Introduction
●Finding the Needle in the Haystack
●The Right Fit for the Job
●From Launch to Longevity
●Building AI Solutions Responsibly
●Key Takeaways
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence

33. 33
Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence
Credit: DALL-E 3 by Microsoft Copilot
“[...], and yet we cannot control what
we don't understand.” -

Mustafa Suleyman

34. The Journey Continues
1.Understand the specific customer needs
your AI solution addresses.
2.Evaluate various LLMs to determine
suitability for your specific problem.
3.Implement continuous monitoring to
ensure your solution remains effective
and relevant.
4.Embed responsible AI principles from the
start to build trust and sustainability.
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Credit: DALL-E 3 by Microsoft Copilot

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Credit: Mario ? Block

36. Let’s Connect!
●Email: [email protected]
●LinkedIn: https://www.linkedin.com/in/quentinreul/
●X (formerly Twitter): https://x.com/rqle_ai
●Personal GitHub: https://github.com/qhreul
●RQle.ai GitHub: https://github.com/RQledotai
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37. Disclaimer
This presentation includes content that was generated with the assistance of
Generative AI. While AI technology has been used to aid in the creation of this
material, all content has been curated, reviewed, and finalized by the author.
The author assumes full responsibility for the accuracy, originality, and
integrity of the information presented.
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence

38. Resources
●Courses
○IBM Generative AI Fundamentals Specialization on Coursera
○Microsoft Azure AI Fundamentals: Generative AI
○Google Generative AI for Developers Learning Path
●News & Trends
○TLDR AI
○Gradient Flow: Unlocking Data & AI
●Podcasts
○AI for Humans
○What’s the BUZZ? — AI in Business
○In AI We Trust?
●Communities
○AI Tinkerers
○AI Makerspace
○AICamp
○MLOps Community
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Cracking the AI Black Box:
Strategies for Customer-centric Enterprise Excellence