The document discusses how artificial intelligence (AI) is revolutionizing project management. It begins by defining AI and providing examples of how AI is used for automation and prediction in project management tasks like task prioritization, schedule optimization, and analytics/forecasting. The document then discusses how the role of project managers must embrace working with AI by setting up and monitoring AI tools, defining responsibilities when working with AI assistants, and managing AI-related projects. It emphasizes that AI will not replace project managers but that those who know how to work with AI will succeed. The document concludes by discussing the importance of project managers developing data literacy and learning skills like ethical leadership to collaborate effectively with AI and ensure it is implemented properly.

1. ARTIFICIAL
INTELLIGENCE AND
PROJECT
MANAGEMENT
Revolutionizing the Way We Work
Thursday, November 09, 2023

2. Cornelius Fichtner, PMP
60 Free PDUs:
pm-podcast.com/pdu

3. AI isn’t yet going to take your job
– but you may have to work with it
https://www.washingtonpost.com/technology/interactive/2023/ai-jobs-workplace/

4. Agenda
25% 75%
AI You

5. It’s all Hype!
Or is it…?

9. What is AI?

10. Artificial intelligence (AI) is the
development of computer systems that
can perform tasks typically requiring
human intelligence, such as learning,
reasoning, problem-solving, and
decision-making.

11. Examples
Virtual
assistants
Self-driving
cars
Recommen-
dation engine

12. In the context of PM, AI refers to
technologies that assist PMs in
automating repetitive tasks, analyzing
complex data, forecasting project
outcomes, and enhancing decision-
making to improve project efficiency,
reduce risks, and optimize resource
allocation.

13. You can split AI into roughly
two areas of application in PM:
automation and prediction
AI in Project Management – Expert Views of practical use cases - 2023

14. Examples in PM
Task
prioritization
 40/60
Schedule
optimization
 50/50
Analytics and
forecasting
 30/70

15. AI in PM Evolution – by PWC
Integration
& Automa-
tion
Now
Source: PWC. Retrieved from https://www.pwc.ch/en/insights/risk/ai-will-transform-project-management-are-you-ready.html on 2023-03-21
Chatbot
Assistants
2 years
Machine
learning-
based PM
10 years
Autono-
mous PM
20+ years

16. PMs Must Embrace AI in Projects
Current PM software
will include more
and more AI features
to support our
projects.
AI Tools
AI-powered team
members – or
AIssistants – will
become the norm.
Simple at first,
sophisticated over
time.
AIssistant
Your employer will
ask you to lead
projects that add AI
capabilities to your
company.
AI Project

17. PMs Must Embrace AI in Projects
• Set up
• Train
• Input data
• Monitor output
• Use insights
• Communicate
insights
AI Tools
• Define R&R
• Set expectations
• Feedback &
Training
• Monitor ethics
• Data security
• Foster human
upskilling
AIssistant
• Know AI landscape
• Apply PM good
practices
• Manage data &
infrastructure
• Address ethical
concerns
• Set expectations
AI Project

18. Future Proofing
Yourself

19. AI won’t take your job.
The person who knows
how to work with AI
will.
David Luria

20. Are You Wondering:
What will I do once artificial
intelligence does all my work?

21. Ask This Instead:
Who will be I once artificial
intelligence works by my side?

22. • Ethical Thought Leader
• AI Interpreter
• Human Liaison
• Relationship Architect
• Strategic Orchestrator
• Innovation Champion
Who Will I Be?
I Deliver “The Human Value”

23. To Take Up
New Ideas &
Technology
Adopt
To Adjust
To New
Environment
Conditions
Adapt
To Be
Skilled Or
Proficient
Adept

24. • Data Literacy
• Ethical Thought Leadership
• Earn PDUs
• Hands-On Experimentation
• Human-AI Collaboration
Where Do I Start Learning?

25. Data Literacy for Project Managers
It’s a Core Skill!

26. Data Literacy for Project Managers
It’s a Core Skill!

27. Data Literacy:
The ability to understand, interpret,
analyze, and communicate data in a
manner that effectively supports
decision-making, problem-solving,
and project performance tracking.

28. A project manager with strong data
literacy can effectively use data to
inform project planning, execution,
and monitoring, as well as drive
continuous improvement.

29. Importance of Data Literacy in PM
Decisions Risk Advantage
• Informed
• Less bias
• Identify early
• Contingency
• Competitors
• Job market

30. Aspects of Data Literacy for PMs
• Identify sources
• Gather data
Collect
• Structure
• Store
Organize
• Examine
• Extract patterns
Analyze
• Understand
• Inform decisions
Interpret
• Gather insights
• Informed choices
Decide
• Convey insights
• Visualize
Convey

31. Central Ethics Intersection
is Undiscovered

33. Earn PDUs
Podcasts Books YouTube Conferences
Blogs/Articles Surveys

34. Hands-On Experimentation
• Write wedding speech
• Critique your writing
• Design spaceship parts
• Teach curling
• Cope with ADHD
• Describe D&D world
• Draw like Sol Le Wit
• Find new place to live
Source: The New York Times: , 2023, https://www.nytimes.com/interactive/2023/04/14/upshot/up-ai-uses.html

35. Don’t Know How? Ask AI!

36. Human-AI Collaboration
Speed
Consistency
Forecasting
AI
The Vision
Informed
Intuition
Enhanced
Efficiency
Balanced
Perspective
Together
Creativity
Empathy
Contextual
Decisions
PM

37. PM and Human-AI Collaboration
• The bridge between
man & machine
• Ensures that projects
resonate
Evolving Role Human Touch
• Ensure smooth
transitions for all
• Make AI relatable &
highlight benefits
Change Mgmt. Buy-in

38. The Choice