This post was originally published on this site.
By: Mustafa Akben, Assistant Professor of Management and Director of Artificial Intelligence Integration
According to the World Economic Forum’s Future of Jobs Report 2025, new technologies like AI could lead to 170 million new jobs worldwide by 2030. Exciting, right? But there’s a catch: a significant skills gap still exists. This begs the question for educators and institutions: Are your students truly ready to compete for these roles?
The democratization of AI has completely transformed what it means to be digitally literate. It’s not just about mastering code or obscure programming languages anymore. Today, it’s about understanding and effectively using generative AI—those incredible tools that can create and collaborate almost like a human. With simple prompts, these tools can whip up captivating marketing copy, design eye-catching visuals, and even tackle tough coding or research projects.
But here’s the thing: the quality of AI-generated content is only as good as the human guiding it. Generative AI is like a mirror, reflecting the user’s ability to steer and refine its outputs. This partnership between humans and machines highlights the need for a new core skill: AI literacy.
In this AI Digest article, we’ll give you three hands-on generative AI exercises—an Elevator Pitch Generator, Mock Interview Practice, and Salary Negotiation Training—designed to give your students a real advantage in the job market, all while sharpening their AI literacy skills. Plus, we’ll share practical tips for weaving these exercises into your teaching.
WHY GENERATIVE AI FLUENCY IS NO LONGER OPTIONAL
Generative AI is revolutionizing all types of industries, and the need for AI literacy is no longer an “if” but a “must.” Marketers use generative AI to create hyper-personalized
campaigns on scales never seen before; scientists use generative AI to speed up groundbreaking discoveries, such as in pharmaceutical drug development; and software engineers use generative AI to streamline writing lines and lines of code, greatly reducing software development lead times. We are not talking about the workplace of tomorrow—”we are talking about the workplace of today.
And it’s important to state here that such tools do not replace people; they empower people. Think of generative AI as a capable assistant who can take care of mundane and repeated tasks, freeing students (and workers) to instead use their time on big-picture thinking, creative work, and challenging problems that are best solved by humans with their ingenuity and smarts.
THE AI LITERACY IMPERATIVE
The AI is in full swing, fueled by powerful tools like OpenAI’s ChatGPT and DALL·E 3, Google’s Gemini, and Stability AI’s Stable Diffusion. These large language models (LLMs) can produce remarkably sophisticated text, images, and even code based on simple user prompts, transforming the way we tackle creative and analytical problems. But this power brings with it a crucial responsibility: students need to develop the critical skills to evaluate the accuracy of AI-generated content and to understand the potential ethical and data-privacy risks involved.
AI literacy – and the sharp critical thinking it requires – is rapidly becoming essential for career success. This means understanding not only how to use AI tools effectively, but also how to:
- Evaluate the quality and reliability of AI-generated content
- Recognize potential biases in AI outputs
- Navigate ethical considerations in AI deployment
- Maintain data privacy and security when working with AI systems
- Leverage AI tools to enhance rather than replace human creativity and judgment
As we move forward into this future, the ability to effectively collaborate with AI tools while maintaining human oversight and ethical considerations will be crucial for professional success. In the following section, we present three practical exercises designed to help educators prepare their students for this exciting new frontier.
THREE GENERATIVE AI EXERCISES: FROM CLASSROOM TO CAREER
EXERCISE 1: THE AI-POWERED ELEVATOR PITCH
A concise elevator pitch can open doors in any professional setting. Instead of crafting it solo, students can lean on generative AI (such as ChatGPT) to help them shape and polish their pitch.
PROMPTING FOR SUCCESS
Example Prompt
“Act as a career advisor. I’m a [Major] student at [University] seeking a [Job Type] in [Industry]. I’m skilled in [Skill 1], [Skill 2], and [Skill 3]. Help me create a 30-second elevator pitch that is memorable and highlights my value.”
Example Student Input
“Act as a career advisor. I’m a Computer Science student at Example University seeking a Software Engineering Internship in the Fintech industry. I’m skilled in Python, Java, and Agile Development. Help me create a 30-second elevator pitch that is memorable and highlights my value.”
ITERATIVE REFINEMENT
After receiving the AI’s output, students should review it for overly generic phrasing, unnecessary jargon, or a lack of personal flair. Encourage them to seek peer and career-services feedback, then feed those insights back into the AI for improvements.
PRACTICE & DELIVERY
Remind students that delivery counts. They should rehearse their pitches out loud, aiming for confident body language and a natural tone. This helps them avoid sounding like they’re reading from a script.
LEARNING OUTCOMES
- Sharpens concise communication
- Encourages self-awareness and self-branding
- Develops a clear, confident value proposition
EXERCISE 2: AI-DRIVEN MOCK INTERVIEWS
Job interviews can be nerve-wracking, especially for new graduates. Generative AI provides a risk-free environment to practice both technical and behavioral questions.
GENERATING QUESTIONS
Example Prompt
“Generate 5 interview questions for a [Job Title] at a [Company Type] company. Include at least one behavioral question, one technical question (if relevant), and one situational question.”
Example Student Input
“Generate 5 interview questions for a Marketing Associate position at a Tech Startup. Include at least one behavioral question, one technical question related to social media marketing, and one situational question.”
RESPONSE PRACTICE
Urge students to structure their responses using the STAR method (Situation, Task, Action, Result). This ensures clarity and showcases their problem-solving approach.
FEEDBACK & ANALYSIS
Encourage students to record themselves responding to the questions. They can then analyze their own body language, tone, and clarity, and invite feedback from classmates or instructors for fresh perspectives.
LEARNING OUTCOMES
· Boosts interview confidence
· Improves clarity of responses
· Fosters critical thinking under pressure
EXERCISE 3: MASTERING SALARY NEGOTIATION WITH AI
Negotiating compensation can be intimidating for first-time job seekers. Generative AI can provide data-driven insights and suggested talking points to help them negotiate effectively.
SALARY RESEARCH
Example Prompt
“Provide the average salary range for a [Job Title] in [City, State] with [X] years of experience. Cite reliable sources.”
Example Student Input
“Provide the average salary range for a Data Analyst in New York City with 1 year of experience. Cite reliable sources.”
Encourage students to compare the AI’s data to reputable job-market platforms (e.g., LinkedIn Salary, Glassdoor, Bureau of Labor Statistics) for accuracy.
STRATEGY DEVELOPMENT
Example Prompt
“I received a job offer for [Job Title] with a salary of [Offer Amount]. I was hoping for [Desired Salary]. Help me craft a response that justifies my desired salary, highlighting my skills and experience.”
Example Student Input
“I received a job offer for a Junior Software Engineer at $60,000. I was hoping for $70,000. Help me craft a response that justifies my desired salary, highlighting my skills in Python, my internship experience at a tech company, and my contributions to open-source projects.”
ROLE-PLAYING & PRACTICE
Students can practice mock negotiations using AI-generated counter-offers. This helps them gain confidence and develop strategies to respond to different negotiation tactics.
LEARNING OUTCOMES
- Enhances negotiation and self-advocacy skills
- Fosters an understanding of fair compensation benchmarks
- Builds confidence for real-world salary discussions
CONCLUSION: CULTIVATING AN AI-READY WORKFORCE
These exercises provide a practical path for integrating generative AI into the classroom to give students both conceptual knowledge and practical skills. You can help bridge the gap between academic theory and the demands of today’s competitive job market by leveraging AI tools to help students improve pitches, practice interview skills, and hone negotiation strategies.
Start small—try out one exercise, ask for feedback, and make adjustments. Share what works with your colleagues and collaborate to identify best practices. By embracing generative AI, we can empower students to become active contributors to an AI-driven economy, driving innovation and building a more dynamic and prosperous future for all.
Let’s prepare the next generation to lead the way—and to do so with the confidence and skills they need to thrive, no matter how the job market changes.