How to Unlock Productivity and Innovation with Generative AI and ChatGPT

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©2023 Cprime, Inc. All rights reserved and no copying without express written permission.
Turn Ideas into Action Faster
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How ChatGPT is Transforming Workflows
How to Unlock Productivity and
Innovation with Generative AI

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Housekeeping Items
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be sent to everyone via email
within 24-48 hours after the
webinar concludes.
Submit questions any time
during this presentation via
the Q&A box on the bottom
panel of your screen.
Audio is streamed
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©2020 Cprime, Inc. All rights reserved and no copying without express written permission. WWW.CPRIME.COM | 877.753.2760
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Turn Ideas into Action Faster 4
Meet our Authors
Chris Knotts
Cprime Learning
Product Director
Alan Koch
Cprime Technology
Product Specialist

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Agenda
01 What is “Generative AI (gAI)?
02 How Can We Use ChatGPT and
Other Forms of gAI?
03 Cool Examples of “Enterprise”
Grade Usage
04 Opportunities to Use gAI and
ChatGPT In Your Own Work
05 Keep the Conversation Going/Q&A

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Polling Questions

POLL QUESTION #1
Does your company have any initiatives underway for:
q Generative AI
q ChatGPT
q Some other type of AI
q Data science
q Predictive analytics
q Agility
q DevOps
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❑ I’m not sure
❑ Research
❑ Automation
❑ Generating content
❑ Personalized
Customer Interaction
Poll Question #2
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How do you think ChatGPT could help you in your job?
❑ Training and Onboarding
❑ Design and Prototyping
❑ Forecasting
❑ Idea Generation
❑ Translation and Localization

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What is Generative AI?
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Generative AI (gAI): An AI system which can create content
(text, audio, imagery) from principles, algorithms, and examples,
rather than selecting predetermined responses provided by a
human. Computationally expensive compared to some types of
AI, but generally much less costly and faster than paying a
human to perform the same task. Cam be prone to producing
inaccurate results – sometimes offensive, or even dangerous
(i.e. AI "hallucinations“).

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What about other types of AI?
There is more to being successful with enterprise AI than just generative (gAI) tools and large
language models (LLMs) . Other types of AI matter, and technology dependencies do, too.

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Generative AI starts with Data…Lots of Data
First things first:
• Huge volumes of data are necessary for
AI algorithms to perform effectively.
• Data trains the AI to identify and
understand relationships in the data. It
can then generate new data based on its
understanding of those relationships.
• ChatGPT is a generative AI tool which
produces language-based content.
Other GenAI tools can generate images,
software code, etc.

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Generative AI starts with Data…Lots of Data
First things first:
• Huge volumes of data are necessary for
AI algorithms to perform effectively.
• Data trains the AI to identify and
understand relationships in the data. It
can then generate new data based on its
understanding of those relationships.
• ChatGPT is a generative AI tool which
produces language-based content.
Other GenAI tools can generate images,
software code, etc.
• Out of the box, ChatGPT’s training data is a
“snapshot” of internet text from September
2021 – about 571 gigabytes.
• The more business-specific data an
organization can feed into the algorithm,
the more relevant and high-quality AI
applications become available.
• GPT performance can be further enhanced
and fine-tuned in domain-specific areas by
integrating aftermarket “vectors,” which
contextually refine the AI.

What about YOUR company’s data?
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Remember the “Big Data” Hype?
• Organizations could imagine the possibilities
of big data but often struggled to execute
usable applications.
• Many orgs didn’t have sufficient training data
or models that were sophisticated enough.
• Recent evolutions in neural network models
power tools like ChatGPT which deliver vast
utility based on giant text-based datasets
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Buzzword
Flashback
In many ways, large language models and tools like ChatGPT
are the mainstream realization of this hype.

©2022 Cprime, Inc. All rights reserved and no copying without express written permission. 17
Other stuff:
Topics for another day:
• Is generative AI alive? (No)
• Is generative AI a threat to humanity? (No)
• Will generative AI cause disruptions in the
labor market? (Yes)
• Will generative AI tools look the same two
years from now? (No)
• Can generative AI help my company make or
save money? (Yes…with proper planning)

Other stuff:
Topics for another day:
• Is generative AI alive? (No)
• Is generative AI a threat to humanity? (No)
• Will generative AI cause disruptions in the
labor market? (Yes)
• Will generative AI tools look the same two
years from now? (No)
• Can generative AI help my company make or
save money? (Yes…with proper planning)

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What is ChatGPT?

What is ChatGPT?
ChatGPT: Generative Pre-trained Transformer. A generative AI program
designed to generate human-like text based on user input.

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Using ChatGPT
2121

What is ChatGPT good at? And not good at?
ChatGPT is good at:
• Generating Text
• Answering Questions
• Language Translation
• Mimicking Writing Styles
• Basic problem solving
• Summarizing Information
• Recommending Resources
• Conversational Role-playing
• Providing Programming Help
• Offering Explanations on Concepts
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ChatGPT is NOT good at
• Real-time Updates
• Deep Expertise
• Understanding Context
• Avoiding Biases
• Emotion and Empathy
• Complex Tasks Outside Text
• Memory of Past Interactions

Cprime on
Where Can ChatGPT Assist?
• Customer service
• Sales professionals
• Marketing professionals
• Human resources professionals
• Financial analysts
• Operations managers
• Project managers
• Legal professionals

Writing prompts for ChatGPT
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Good Prompting

Tips for Good Prompting
• Be Specific
• Ask Open-ended Questions
• Set the Context
• Experiment with Different Phrasings
• Guide the Format
• Limit Biases
• Use Iterative Questions
• Be Patient
• Avoid Overloading the Prompt
• Understand the Model's Limitations

Chained Prompts
A series of prompts to the model in a single
input to simulate an ongoing conversation or
to build upon previous responses.
Remember, while ChatGPT is great for asking
individual questions, some of the most useful
output comes from evolving conversations
and iteratively refining or building on output
through a series of prompts.

Live Usage
Over the next few minutes, we’ll
use ChatGPT to demonstrate
some examples which bring
these concepts to life.
• We’ll use ChatGPT to assist
with code review,
documentation, and testing
• We’ll use ChatGPT to produce
financial scenarios to plug in
to an investment proposal

Imagine you’re a business analyst…

As a business analyst, I need to
summarize and document core
features for our web-based Online
Medical Center Management System so
our software team’s work is traceable,
and future development can be more
test-driven.

As a business analyst, I need to
summarize and document core
features for our web-based Online
Medical Center Management System so
our software team’s work is traceable,
and future development can be more
test-driven.
• Provide summaries of software
feature functionality
• Produce documentation for
newly-coded features
• Assist with starter tests my team
can use to validate the feature
• Produce documentation for the tests

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We used these prompts:
1. I have some code here written in Java. Can you explain what it does, please?
2. Based on this example, please generate software documentation which a business analyst could
use to satisfy documentation requirements.
3. Please provide a one-paragraph summary for my product owner team explaining what this piece of
code is for and what requirements it likely satisfies
4. Now for this current Java example, can you please reverse engineer a set of tests for this code that
reflect the functions and the described classes
5. Given the gherkin format of the tests you just provided, please generate some additional auto tests
written in java in a separate class for this code. However, the tests should be in the same scope to
be able to test the code
6. Finally, please provide documentation I can use for the tests.
Live Usage
Let’s Head Over To ChatGPT

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Let’s Look at a Financially Oriented Example
An associate of ours was creating a business development proposal for
Mastercard, and needed to show realistic financial scenarios which
would prove the viability of the potential ROI on the investment.
We’ll start by quickly explaining the context for this use case, followed by a
flyover of the entire conversation in which they used ChatGPT to research
and develop the proposal, and finally we’ll look specifically at the prompting
used to generate the financial scenarios.
Live Usage

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Let’s Look at a Financially Oriented Example Live Usage
Give me concrete numbers of how Mastercard will convert 200,000 average
gameday viewers with peaks of 5,000,000 concurrent viewers into that
35 million dollar investment considering what percentage of the fanbase
and how many total users at what dollar amounts will be needed to recoup
the investment and beyond.
Break it down into two different user/dollar amount combinations to make
back the 35 million, and 2 different user/dollar amounts into a surplus of
45 million total dollars.
“
”

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Finding Opportunities to use ChatGPT
(and other generative AI, too)

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Automation Basics
Before thinking about how an AI application
can save time or money, it’s worth thinking
about automation in general.
While generative AI isn’t just about
automation, applying automation concepts
are useful any time you want to evaluate the
feasibility of giving a machine a job that
formerly had to be done by a person.

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Automation Basics
Before thinking about how an AI
application can save time or money,
it’s worth thinking about automation
in general.
1. Identify Repetitiveness
2. Assess Complexity & Variability
3. Score Error Rate & Impact
4. Ensure Scalability
5. Understand ROI
6. Gauge Resource & Time Intensity
7. Prioritize Human-Machine Synergy
8. Assess Data Quality

Should I Automate It?
Hackaday, May 15 2021
hackaday.com/2021/05/15/should-i-automate-this/
How long can you work
on making a routine task more
efficient before you’re spending
more time than you save?
(across five years)

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Canvass for automation opportunities
(ChatGPT might be able to help)

We’ll use these prompts:
1. If I am a business professional who works with agile software development teams, can you help me
generate a rubric which I could use to scan and identify high-potential use cases for using ChatGPT
to boost efficiency or automate work on my teams?
2. Excellent - can you now organize the rubric according to the job title of people who could best
utilize the rubric, and provide a list of the most useful criteria for those roles?
3. Very good - finally, for the roles above, can you expand each bullet to identify specific things the
person in the role can do to satisfy the rubric? Then format those things in the form of a checklist.
Let's do the roles one at a time. Start with #1 please and let's see what it looks like.
4. This is excellent - in the first two items for "task automation" above, you provide examples for
identifying repetitive tasks and evaluating automation feasibility. Examples like this are probably
the most valuable content I want to get out of this conversation. For each of the checklist items
above, can you provide a nice list of examples like this so that people in the role get a better idea of
specific situations they should look for?
5. This looks great. Let's do the other examples in a moment.
For now, can you reformat your content above into something that uses tables?
Live Usage

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APIs, Plugins, and
Vectors – Oh My!
You can do a lot more with
GPT and other generative
AI applications.

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For Best Results, COLLABORATE!
To really achieve enterprise-grade results with generative AI applications,
you’ll need to collaborate with colleagues or consultants who bring technical
expertise to the mix.
• ChatGPT is versatile – although it’s a natural
language chatbot out of the box, output can be
crafted in a way that translates to other formats.
• ChatGPT can be used with third-party data
platforms as an AI engine for things like:
- Data visualization
- Music
- Code
- Sensor input
- Etc.

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Keep the Conversation Going…
Check out Cprime’s upcoming webinars, read our blog, and
download resources such as whitepapers and case studies:
www.cprime.com/resources
Connect with our Panelists on LinkedIn!
• Chris Knotts
• Alan Koch
Reach out to Cprime at learn@cprime.com

QUESTIONS?
WWW.CPRIME.COM | 877.800.5221
Q U ESTI O N S?

QUESTIONS?
TH AN K YO U

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