Companies which want to benefit from the transformative power of AI need to embrace change and adapt their organizations with new roles and organizational structure. Disclaimer: AI is not taking your job.

1. How AI is
transforming
companies,
inside out AI Restart
22.6.2023, Prague

2. X
Omlouvám se
⌛👎
No
fancy
slides

3. Já jsem
Guillermo
(Řiká se Gyjermo) ● I’m an entrepreneur and AI consultant
● Since 2016, delivered 60+ AI projects

4. AI for
Business
People
What do you want AI for?
1. Make money
2. Save money

5. AI Copilots
AI does the heavy work.
Human experts makes the calls.

6. Legal research
The AI copilot helps analyze
vast amounts of legal
documents, cases, and
statutes, providing relevant
insights and
recommenda:ons. The
expert lawyer makes the call.
AI Copilots Examples - 1/2
Medical diagnosis
Scans images and detects
anomalies. The doctor
makes the call.
Content moderation
AI scans thousands of
interactions, comments and
detects violations or
inappropriate content.
Human makes the call.
Financial trading
AI analyzes huge amounts of
financial data and generates
insights. Human traders
make decisions.
Cyber security
The AI copilot continuously
monitors network activities,
identifies anomalies, and
alerts human security
analysts.
Customer support
AI handles easy things,
human expert intervenes
when things get tough.

7. HR & recruitment
The AI copilot analyzes
video interviews, assesses
candidate responses, and
provides insights to hiring
managers, who make the
final decisions regarding
candidate selec:on.
AI Copilots Examples - 2/2
Sales
Ai analyzes calls, meetings,
customer sentiment and
sales teams can fix and
refine their strategies.
Fraud detection
The AI copilot monitors
patterns, behavior, and
various data points to
identify potentially
fraudulent activities, Human
analyst makes teh call.
Marketing
AI creates content, blogs,
email subject lines, makes
recommendations and
marketing expert decides.
Energy management
The AI algorithms analyze
energy consumption
patterns, weather data, and
grid conditions to optimize
energy distribution and
usage. Human operators
make the calls.
Air traffic control
he AI systems analyze real-
time data and make
suggestions to the
controllers, who make
decisions.

8. Does anyone still
think AI is just a
hype? 🤔

9. But, what do YOUwant to do as a business?
Use AI ready-made tools Build your own AI tools
Almost immediate results
Low cost
Reduce internal costs (effort)
Increase turnover
Differentiation vs competition
Increase in company valuation (IP)
Creates more revenue streams
Security / privacy compliant
Every company can use the same tools
Limited increase in company valuation
Vendor lock-in, not so flexible
Compliance
Require bigger investment
Takes longer to see results
Require deeper organizational changes
Hard to keep up on R&D (impossible in
some cases)

10. Data is KING 👑
👉 Garbage in = Garbage out
👉 Data is anything: documents, images, spreadsheets, meeting notes, not only databases!
👉 Your differentiation as a company will be determined by how good is your data

11. Get used
to these
roles
Prompt
engineer
knows how to write clear instructions that
make AI models give the answers or results
they want.
Data
engineer
organize and process data so that it can be
easily used by others
Data
scientist
specializes in applying data science techniques
and machine learning algorithms to analyze and
extract insights from large datasets.
AI business
strategist
combines domain expertise with AI knowledge
to develop strategies that leverage AI
technologies for business growth.
AI ethics
officer
focuses on ensuring the ethical development
and deployment of AI technologies within the
company. They address ethical considerations,
biases, and fairness in AI systems, and ensure
compliance with regulatory frameworks.

12. BAD BUSINESS
● Lack of understanding of the problem
● Wrong expectations
REAL-WORLD DISCONNECT
PIZZA INSTEAD OF LASAGNA
WHY AI PROJECTS
FAIL?
● Data based on lab datasets
● Focus on theoretical modelling
● Lack of long term strategy
● Lack of involvement of different stakeholders
❌
❌
❌

13. HOW
TO
WIN
WITH AI

14. Think
Big
Start
Small
Scale
Fast
Keep It
UP
● Assess your data
● Select an important
problem
● Involve all
stakeholders
● Set realistic
expectations
● Quick prototypes
● Setup scalable
infrastructure
● Go to production
ASAP
● Observe real data
● Scale infrastructure
● Watch
performance decay
● Act on feedback
● Keep collecting
data

15. How Can I
Help You?
AI consulting
Build an AI product or service
Build an AI team

16. www.nivity.ai
guillermo.alda@nivity.ai
+420 775 487 557