rtificial intelligence (AI) is a technology science focused on machine learning. As technology research grows, so do the career opportunities involving AI products and systems. Researching the various jobs in artificial intelligence could help you determine whether it's the right career path for your goals.

1. Artificial Intelligence and
Youth Employment
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2. ARTIFICIAL INTELLIGENCE: INTRODUCTION
In simple terms AI, or Artificial Intelligence, is when computers and machines can
do tasks that usually need human thinking, like learning, problem-solving, and
understanding language.
It's like giving computers the ability to be smart in their own way.
In recent years, the growing use of digital technologies and the internet has
considerably aided the expansion of the worldwide artificial intelligence industry.
AI is playing an increasingly vital role across various industries, transforming the
way businesses operate and providing new opportunities for efficiency, innovation,
and growth.

3. • According to Next Move Strategy Consulting, the artificial intelligence (AI) sector will increase rapidly over the next
decade.
• Its current worth of roughly 100 billion US dollars is predicted to more than double by 2030, reaching nearly two
trillion USD.

4. AI AND JOB AUTOMATION
AI technologies, such as machine learning, natural language processing,
and robotics, have the ability to perform tasks that traditionally required
human intelligence and skills.
As AI continues to advance, it has the potential to automate various jobs
across different industries.
While AI has the potential to automate certain tasks and jobs, it also
brings opportunities for innovation, productivity improvement, and the
creation of new job roles.

5. PRESENT STATISTICS ON YOUTH EMPLOYMENT RATES
GLOBALLY
The COVID-19 pandemic has worsened the already existing challenges in the job market that youth
usually encounter.
In 2020, the global employment deficit for youth was 8.2%, compared to 2019. Meanwhile, the
deficit for adults was less than half of that.
The global deficit fell to 5.9 per cent in 2021 and decreased further to 4.5 per cent in 2022.
621 million youth aged 15-24 years old are not in education, employment or training.
75 million youth are trained but have no job.
In the next decade, one billion youth will enter the labour market, and large numbers of young
people face a future of irregular and informal employment.
Almost 90% of all young people live in developing countries.
Youth are approximately three times more likely to be unemployed than adults (2.7).
It is estimated that 23% of young people currently employed in the world earn less than $1.25 US a
day.

6. CHALLENGES FACED BY YOUTH IN FINDING EMPLOYMENT
Finding employment can be challenging for youth due to a combination
of factors that affect their entry into the job market.
These challenges can vary depending on the region, economy, education
system, and societal norms.
Here are some common challenges faced by youth when seeking
employment:
Lack of Experience
Educational Mismatch
Limited Skills and Training
Competition
Lack of Professional Network
Unpaid Internships and
Exploitation
Age and Perception
Geographical Constraints
Economic Factors
Automation and Skill Shifts
Language and Communication
Barriers
Mental Health and Well-Being
High Expectations

7. IMPORTANCE OF EQUIPPING YOUTH WITH RELEVANT SKILLS
Equipping youth with relevant skills is of paramount importance for their personal
development, employability, and the overall progress of society.
Here's why ensuring that young people have the right skills is crucial:
Enhanced Employability
Economic Growth
Reduced Unemployment
Increased Income Potential
Adaptability to Change
Global Competitiveness
Innovation and Entrepreneurship
Job Satisfaction and Fulfillment
Reduced Dependency on Social
Support
Talent Development
Addressing Industry Needs
Civic Engagement and
Participation
Long-term Prosperity

8. AI has substantial potential to create
significant employment opportunities
across various sectors.
AI fuels innovation and
entrepreneurship across a wide range
of industries.
In coming slides we will discuss some
examples of AI-driven industries that
can create employment.
AI-DRIVEN INDUSTRIES AND EMPLOYMENT OPPORTUNITIES

9. AI-DRIVEN INDUSTRIES AND EMPLOYMENT OPPORTUNITIES
Product and Service
Enhancement
Applications
AI-powered chatbots
AI-driven analytics
Job Opportunities
AI Customer Support Agents
Chatbot Trainers
Customer Experience
Analysts
Healthcare and Life Sciences
Applications
AI-powered Medical Devices
Diagnostic Tools
Health Monitoring Systems
Personalized Treatment Plans
Drug Discovery
Medical Image Analysis
Job Opportunities
AI Specialists
Medical Data Analysts
Healthcare AI Trainers
Telemedicine Professionals
E-commerce and Retail
Applications
Optimize inventory
management and pricing
strategies
More relevant product
suggestion
Job Opportunities
AI-driven Marketing Specialists
E-commerce Data Analyst
Chatbot Developers
Logistics Optimization Managers

10. Financial Technology (FinTech)
Applications
Fraud Detection
Algorithmic Trading
Credit Scoring
Credit Risk Assessment
Customer Support
Job Opportunities
AI Financial Analysts
Fintech Software Developers
AI-driven Investment Advisors
Blockchain Experts
Smart Manufacturing
Applications
Smart Factories
AI-driven Automation
Predictive Maintenance
Job Opportunities
Robotics Engineers
Industrial AI Programmers
Automation System
Maintenance Technicians
Education and Training
Applications
Personalized Learning
Adaptive Tutoring
Educational Content
Creation
Job Opportunities
AI Educators
Instructional Designers
Edtech Software Developers
Data Analysts
AI-DRIVEN INDUSTRIES AND EMPLOYMENT OPPORTUNITIES

11. Smart Cities
Applications
Traffic Management
Waste Management
Public Safety
Energy Usage Optimization
Job Opportunities
Urban AI Planners
Smart City Project Managers
IoT Integration Specialists
Entertainment and Media
Applications
Content Recommendation
Personalized Content Creation
AI-generated Art, Music, &
Content
Immersive Experiences
Job Opportunities
AI Content Creators
VR/AR Developers
Media Data Analysts
Agricultural Innovation
Applications
AI-powered sensors and drones
Precision Agriculture
Crop Management
Optimization
Resource Utilization
Yield Prediction
Job Opportunities
Agricultural Data Analysts
Precision Agriculture
Consultants
AI Agricultural Engineers
AI-DRIVEN INDUSTRIES AND EMPLOYMENT OPPORTUNITIES

12. Transportation and Mobility
Applications
AI-driven Transportation
Solutions
Innovations in Autonomous
Vehicles
Traffic Management
Job Opportunities
AI Vehicle Engineers
Transportation System
Planners
Autonomous Vehicle Safety
Testers
Energy and Utilities
Applications
AI-driven Energy
Management
Grid Optimization
Job Opportunities
Energy Data Analysts
AI Energy Consultants
Smart Grid Engineers
Environmental Monitoring
and Conservation
Applications
Analyze Environmental Data
For Conservation Efforts
Job Opportunities
Environmental Data
Scientists
AI Ecologists
Conservation Technology
Specialists
AI-DRIVEN INDUSTRIES AND EMPLOYMENT OPPORTUNITIES

13. Transportation and
Mobility
Applications
AI-driven
Transportation
Solutions
Innovations in
Autonomous Vehicles
Traffic Management
Job Opportunities
AI Vehicle Engineers
Transportation System
Planners
Autonomous Vehicle
Energy and Utilities
Applications
AI-driven Energy
Management
Grid Optimization
Job Opportunities
Energy Data Analysts
AI Energy Consultants
Smart Grid Engineers
Environmental Monitoring
and Conservation
Applications
Analyze Environmental
Data For Conservation
Efforts
Job Opportunities
Environmental Data
Scientists
AI Ecologists
Conservation
Technology Specialists
AI-DRIVEN INDUSTRIES AND EMPLOYMENT OPPORTUNITIES
Cybersecurity
Applications
Threat Detection
Anomaly Detection
Real-time
Cybersecurity
Monitoring.
Job Opportunities
AI Cybersecurity
Analysts
Penetration Testers
AI-driven Security
Software Developers

14. The AI-driven job market demands a combination of
to effectively develop, implement, and manage AI technologies
KEY SKILLS NEEDED IN THE AI-DRIVEN JOB MARKET
TECHNICAL SKILLS SOFT SKILLS
ANALYTICAL SKILLS

15. TECHNICAL SKILLS NEEDED FOR AI-JOBS
Programming Languages: Proficiency in programming languages such as Python, R, and Julia is crucial
for AI development and data analysis.
Machine Learning and Deep Learning: Understanding machine learning algorithms, neural networks, and
deep learning frameworks (e.g., TensorFlow, PyTorch) is essential for creating AI models.
Data Science: Skills in data preprocessing, cleaning, and feature engineering, as well as statistical
analysis, are fundamental for extracting insights from data.
Natural Language Processing (NLP): NLP skills are essential for developing applications like chatbots,
sentiment analysis, and language translation.
Computer Vision: Knowledge of computer vision techniques and tools is important for applications
involving image and video analysis.
Reinforcement Learning: Understanding reinforcement learning concepts is valuable for AI systems that
learn through interaction and feedback.
Data Mining and Big Data: Proficiency in tools like Hadoop and Spark for handling and analyzing large
datasets is important.
Algorithmic Thinking: Ability to design and implement algorithms for various AI tasks.
Cloud Computing: Familiarity with cloud platforms like AWS, Azure, and Google Cloud for scalable AI
applications.
AI Frameworks and Libraries: Proficiency in using AI libraries and frameworks for development, such as
scikit-learn, Keras, and NLTK.
TECHNICAL SKILLS NEEDED FOR AI-JOBS

16. ANALYTICALSKILLSNEEDEDFORAI-JOBS
Problem-Solving: Strong problem-solving skills to identify appropriate AI solutions for different
challenges.
Data Analysis: Ability to analyze and interpret complex data to derive meaningful insights.
Pattern Recognition: Skill in recognizing patterns in data for developing predictive models.
Critical Thinking: Capacity to evaluate AI models and algorithms critically for optimization.
Experimental Design: Ability to design experiments and conduct A/B testing to evaluate AI
system performance.
Statistical Analysis: Proficiency in statistical techniques and hypothesis testing for data
analysis.
ANALYTICAL SKILLS NEEDED FOR AI-JOBS

17. SOFT SKILLS NEEDED FOR AI-JOBS
Communication: Effective communication skills to convey complex AI concepts to both
technical and non-technical audiences.
Collaboration: Ability to work in cross-functional teams, including engineers, data
scientists, and domain experts.
Creativity: Innovative thinking to develop new AI solutions and applications.
Adaptability: AI technologies are rapidly evolving; being adaptable is crucial for staying
current.
Ethical Consideration: Understanding the ethical implications of AI and being able to
make responsible decisions.
Problem Identification: Skill in identifying business challenges that can be solved using
AI.
Continuous Learning: Willingness to continuously learn and update skills as AI evolves.
Domain Knowledge: Depending on the industry, having domain-specific knowledge can
greatly enhance the effectiveness of AI solutions.
Project Management: Ability to manage AI projects, including scoping, timelines, and
resource allocation.
Leadership: For roles involving AI team management, leadership skills are important.
SOFT SKILLS NEEDED FOR AI-JOBS

18. THE ROLE OF EDUCATION IN PREPARING YOUTH FOR AI-RELATED JOBS
Curriculum Development: Educational institutions can incorporate AI-related topics into their curriculum,
ranging from introductory courses to specialized programs. This includes teaching programming
languages, machine learning concepts, data analysis, and ethics in AI.
STEM Education: Emphasizing STEM subjects (Science, Technology, Engineering, and Mathematics) early in
schooling can provide a strong foundation for youth to understand the technical aspects of AI.
Critical Thinking and Problem-Solving: These abilities are essential for understanding AI concepts and
applying them to real-world challenges.
Data Literacy: Teaching students how to work with data, interpret data visualizations, and understand
statistical concepts will be crucial as AI relies heavily on data analysis.
Ethical Considerations: Encouraging students to think about the responsible development and deployment
of AI systems.
Interdisciplinary Learning: Encouraging interdisciplinary learning can help students bridge the gap
between AI and various industries.
Practical Experience: Incorporating hands-on projects, case studies, and simulations can provide students
with practical experience in working with AI tools and technologies.

19. Collaborative Skills: Many AI projects are team-based. Teaching collaboration, communication, and teamwork skills
prepares students for working effectively in AI-related roles.
Continuous Learning Mindset: Instilling a mindset of continuous learning helps students understand that the field of
AI is dynamic and requires ongoing skill development.
Industry Partnerships: Collaborating with AI-driven industries can provide insights into the skills required by
employers, allowing educational institutions to tailor their programs accordingly.
AI Clubs and Competitions: Establishing AI clubs, coding competitions, and hackathons can encourage students to
engage with AI in a fun and interactive way.
Teacher Training: Equipping educators with the knowledge and skills to teach AI-related topics is essential for
effective delivery of AI education.
Online Resources: Providing access to online resources, courses, and tutorials can supplement formal education and
allow students to explore AI topics at their own pace.
Real-World Applications: Showcasing real-world applications of AI in various fields helps students understand how AI
impacts industries and society.
Career Guidance: Offering career guidance and counseling that highlight AI-related job opportunities can help
students make informed choices about their future paths.

20. AI4K12
An initiative focused on
integrating AI education
into K-12 classrooms. It
offers curriculum
resources, lesson plans,
and teacher training to
help students understand AI
concepts from an early age.
AI for Youth
A program by Intel that
offers workshops, online
courses, and educational
resources for students to
learn about AI, machine
learning, and data science.
AI4ALL
An organization that provides
summer camps and programs
for high school students from
underrepresented backgrounds
to learn about AI, explore AI-
related careers, and work on
hands-on projects.
Google AI Education
Google offers a range of AI
educational resources,
including AI Experiments,
TensorFlow tutorials, and
the "Machine Learning
Crash Course" for
beginners.
Career Essentials in
Generative AI by
Microsoft and LinkedIn
A free AI training course on
LinkedIn. The course
provides a certificate and
teaches responsible AI use.
Coursera
A Platform that offers a wide
range of AI-related courses
from universities and
institutions worldwide. For
example, the "Deep Learning
Specialization" by Andrew Ng is
a popular choice
xPRO and edX
Designing and Building AI
Products and Services by
MIT xPro.
edX offers AI courses from
institutions like MIT,
Harvard, and UC Berkeley
IBM Applied AI
Professional Certificate
This Professional Certificate
contains a number of hands-on
learning projects that will help
develop your understanding of
AI concepts and tools.
EXAMPLES OF AI-RELATED EDUCATIONAL PROGRAMS AND INITIATIVES

21. Entrepreneurship Support
establish incubators,
accelerators, and funding
programs to support AI-driven
startups and entrepreneurial
ventures.
Skill Development Initiatives
Partner with educational
institutions, industry experts,
and training organizations to
create reskilling opportunities
for youth.
AI Research Centers
Establishing AI research
centers and Investing in
research and innovation in AI-
related fields
Data Privacy and Security
Enact legislation to protect data
privacy and security
Youth Employment
Programs
Creating targeted youth
employment programs that focus
on AI-related industries
International Collaboration
Sharing best practices,
knowledge, and resources in
addressing AI-related youth
employment challenges.
Education and Training
Funding education and
training programs that equip
youth with the necessary
skills for AI-related jobs.
Promotion of STEM Education
Encourage and support STEM (Science,
Technology, Engineering, and
Mathematics) education from an early
age.
ROLE OF GOVERNMENTS IN ADDRESSING AI AND YOUTH EMPLOYMENT

22. POLICIES AND INITIATIVES THAT SUPPORT YOUTH EMPLOYMENT IN AI
FIELDS
AI Education and Training Programs
AI Scholarships and Grants
Industry-Academia Collaboration
AI Apprenticeships and Internships
Diversity and Inclusion Initiatives
Establishment of AI-focused startup
incubators
Organize AI-related competitions and
challenges
Setting up career centers
Organizing Networking Events and
Conferences
Government Grants for AI Startups
Support for youth-led AI Research
projects
Establishing AI Mentorship Programs
Launching fellowship programs
Develop and promote AI Ethics and
Regulation Guidelines
Encourage a culture of Lifelong
Learning and Continuous Education
Invest in digital infrastructure and high-
speed internet
Establish AI innovation hubs and
clusters

23. POSITIVE IMPACTS OF AI ON YOUTH EMPLOYMENT
New Job Opportunities: AI is expected to create new types of jobs that require skills in AI
development, data analysis, and human-AI collaboration. Youth with relevant skills can benefit
from these emerging roles.
Innovation and Entrepreneurship: AI-driven innovation can lead to the creation of startups and
entrepreneurial ventures, offering youth the chance to develop AI-powered products and
services.
Productivity Enhancements: AI automation can streamline processes, increase efficiency, and lead
to higher productivity, which can result in more job openings across industries.
Remote Work and Flexibility: AI-enabled remote work technologies can offer youth the flexibility
to work from different locations, accommodating their preferences and lifestyles.
Skill Development and Learning Opportunities: The demand for AI-related skills can motivate
youth to pursue education and training in areas like programming, data science, and AI ethics.

24. CHALLENGES AND CONCERNS ASSOCIATED WITH AI AND YOUTH EMPLOYMENT
AI is not neutral: AI-based decisions are susceptible to inaccuracies, discriminatory outcomes,
embedded or inserted bias.
Lack of transparency of AI tools: AI decisions are not always intelligible to humans.
Skill Mismatch: Rapid technological advancements could result in a mismatch between the skills
youth possess and those demanded by AI-related jobs.
Job Displacement: While AI can create new job opportunities, it can also lead to the displacement
of traditional jobs, particularly for entry-level positions that youth often seek.
Digital Divide: Unequal access to technology and the internet can hinder youth from participating
in AI-driven employment opportunities.
Dependence on AI Recommendations: Relying solely on AI recommendations for career choices
might limit youth's exploration of diverse opportunities and passions.
Job Insecurity: Youth might experience heightened job insecurity due to the volatility of AI-driven
industries, requiring ethical measures to ensure job stability.
Privacy Concerns: Ensuring the privacy of youth's personal information and protecting their digital
rights is paramount.
Youth Vulnerability: Inexperienced youth might be more susceptible to unethical AI-driven job
offers or exploitation by employers using AI systems.

25. Conclusion
The increasing role of AI in various industries is transforming the way
businesses operate and revolutionizing traditional practices. The long-
term impact of AI on youth employment is complex and multifaceted.
While AI has the potential to create new opportunities and transform
industries, it also presents challenges that could shape the
employment landscape for young individuals.

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