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Many tech and business internship postings mention artificial intelligence (AI) use and require some sort of AI competency for applicants. What does that mean for students seeking internships this coming year? You do not need to be an expert in AI to understand these basic principles and skills!
Companies want interns who can use AI tools effectively, think critically about their outputs, and understand when AI adds real business value. Here’s your go-to list in order of what matters most!
Universal Skills: What Every Business & Tech Intern Needs
Prompting Basics
Prompts are “conversation starters,” what you tell AI to give you useful responses (MIT Sloan Teaching & Learning Technologies, 2025). Instead of merely asking questions, you are “programming a machine with words” (MIT Sloan Teaching & Learning Technologies, 2025). The quality of your questions determines the quality of your responses. These three strategies are essential to effective prompting (MIT Sloan Teaching & Learning Technologies, 2025):
I. Provide Proper Context: Instead of “summarize this article,” try:
“You’re a business analyst presenting to executives. Summarize this report’s key findings and business implications in 3 bullets.”
This way, the AI tool can give you better responses based on the guidelines you provided it with.
II. Be More Specific: Instead of asking “explain recursion,” ask “explain recursion using a simple analogy, then show me a basic example in Python with step-by-step comments.” The more you guide the AI, the better it teaches.
III. Iterate in Conversation: AI remembers your chat history. Engaging with the AI and building on the conversation (for example: “explain like I’m new to this concept”) is the approach that professionals use when using these tools.
Fluency with AI Tools
Get comfortable using AI assistants in your daily, mundane tasks. However, be careful not to use AI to completely replace the thinking process. Instead, use AI to guide you and quicken your work progress. For developers, this could look like GitHub Copilot (Aziz & Jundanian, 2025). For students in general, this could look like Claude AI for analysis, Perplexity for research, and ChatGPT for brainstorming (Aziz & Jundanian, 2025). Internship managers know these tools exist and will expect you to work faster with that in mind.
Demonstration of Claude AI’s neutral tone which is helpful for analysis (Aziz & Jundanian, 2025)
Critical Evaluation
Companies need interns who can verify AI outputs, catch errors, and know when to ignore AI suggestions. This is key as AI generates what it thinks is the most likely series of words, not necessarily the truth (Research Guides: Artificial Intelligence (AI) and Information Literacy: What Does AI Get Wrong?, 2025). AI thus cannot fully distinguish between correct and incorrect outputs. Enter, you! When working with AI tools, watch for these types of errors:
I. Misleading and Misinformed Answers:
AI can confidently return wrong information and missing information is just as problematic as wrong information.
II. Made-Up Information:
AI tools can invent sources, citations, facts, people, and even events. Be wary of references to articles or papers that were never written or AI tools mixing real and fake information (for example, real authors and fake titles); URLs can also often lead nowhere or to completely different content (Research Guides: Artificial Intelligence (AI) and Information Literacy: What Does AI Get Wrong?, 2025).
III. Misinterpretation of Prompts:
AI tools can also interpret your prompts and questions in unexpected ways (Research Guides: Artificial Intelligence (AI) and Information Literacy: What Does AI Get Wrong?, 2025). Your assumptions in your prompt get reinforced by AI, even if they are wrong.
An example of ChatGPT making up citations (University of Maryland, 2025)
Proper Attribution
Ensure you know how to document AI assistance in your tasks. Whether it is code comments noting “Copilot-generated, human-reviewed” or acknowledging AI in research, transparency is becoming standard practice. Companies want interns who can handle this professionally and with integrity.
I. When Do I Cite/Acknowledge AI?
(LibGuides: Generative Artificial Intelligence: Citation and Attribution, 2025)
A. Direct quotations and paraphrasing from AI
B. Using AI for editing, translating, idea generation, data processing
C. Any time AI output appears in your work
D. Describing AI use in methods/processes when relevant
Never cite sources that AI provides without reading them yourself! AI can create fake citations and may cite real sources but misrepresent their contents. Remember, companies value honesty and integrity with AI rather than pretending you did not use it.
Role-Specific Skills That Matter
Understanding what AI skills actually look like in real practice is incredibly helpful. Read about these Google interns from this summer who worked on real AI projects and employed these skills accordingly!
Software Engineering Interns
What you need to be able to do (Rowland, 2025):
Working productively with AI tools, not just accepting suggestions blindly, but using them as starting points
Basic understanding of how to call APIs (Application Programming Interfaces) if you are building features
Knowing when AI speeds you up versus when it’s faster to write code yourself
Intern Experience: Lalit Mohanani, a software engineering intern at Google in Pune, India, is “enhancing AI communication security” by building systems that let clients securely verify AI servers (Rowland, 2025). His project addresses the critical question of how do you trust AI in security-sensitive environments (Rowland, 2025)? This solves real problems in finance and healthcare, and he isn’t building the AI itself, he is building around the AI to make it safer and more trustworthy (Rowland, 2025).
Product Management Interns
What you need to be able to do (Rowland, 2025):
Evaluating AI feature ideas: What is technically feasible? What is actually valuable to users? What is the cost?
Competitive analysis: knowing which companies use AI, where and why
User research with AI tools: summarizing feedback for example
Intern Experience: Jonathan Shamwana, an associate product management intern for YouTube Ads, is “experimenting with the latest generative AI models” to improve the viewing experience (Rowland, 2025). He is not coding the models but instead figuring out where AI makes sense in the product and how it improves user experience; product management interns need to understand AI well enough to make product decisions (Rowland, 2025).
Business & Strategy Interns (Consulting, Corporate Strategy)
What you need to be able to do (Rowland, 2025):
Using case identification: where does AI add real business value versus hype?
ROI (Return on Investment) frameworks: how to evaluate if an AI implementation is worth it
Industry-specific applications: knowing AI applications in finance, retail, healthcare, etc.
Intern Experience: HyoJung Han, a research intern for Google Translate in Mountain View, USA, is working on “how multilingual large language models handle cultural nuance” (Rowland, 2025). Her project addresses a business problem: AI can inadvertently dilute cultural context while trying to generalize knowledge (Rowland, 2025). This matters for Google’s global expansion and user trust (Rowland, 2025).
Strategy interns need to be able to catch these kinds of issues, where AI creates business risk, where it creates opportunity, and how to balance both (Rowland, 2025). They use these skills to connect technical capabilities to business outcomes (Rowland, 2025).
The Bottom Line
Companies want interns who can:
Use AI tools productively (not just prompting, but working faster)
Think critically about outputs (catching errors, understanding limitations)
Apply AI to real problems (not just theoretically, but practical implementation)
As the business and technology sector continues to grow with AI implementation, these skills become more and more valuable and set applicants apart. Make sure the save these tips in order to succeed in any internship, and stay tuned for more insights!
References
Aziz, M., & Jundanian, J. (2025, June 3). The 18 Best AI Platforms in 2025 – Tested & Reviewed. Lindy. https://www.lindy.ai/blog/ai-platforms
Google. (2025). [Generated image illustrating AI skills for business and tech internships]. Gemini. Google Docs.
LibGuides: Generative Artificial Intelligence : Citation and Attribution. (2025, October 14). Brown University Library. https://libguides.brown.edu/c.php?g=1338928&p=9868287
MIT Sloan Teaching & Learning Technologies. (2025, May 30). Effective Prompts for AI: The Essentials - MIT Sloan Teaching & Learning Technologies. https://mitsloanedtech.mit.edu/ai/basics/effective-prompts/
Research Guides: Artificial Intelligence (AI) and Information Literacy: What does AI get wrong? (2025, August 25). University of Maryland University Libraries. https://lib.guides.umd.edu/c.php?g=1340355&p=9880574
Rowland, J. (2025, July 31). Meet 3 interns working on AI at Google. Google. https://blog.google/inside-google/googlers/international-intern-day-2025/
