AI is no longer just a buzzword in tech circles—it’s a central part of the tools and platforms you already use for studying, creating, researching, and even job hunting. From writing assistants to design tools, AI is changing how we work, think, and learn.
But using AI effectively isn’t just about getting faster results. At the tertiary level, AI literacy means understanding how these tools work, when (and when not) to use them, and what ethical, academic, and professional responsibilities come with them.
This article outlines the AI tools you should be competent with as a tertiary student, along with the critical thinking needed to use them responsibly and skillfully in academic and real-world settings.
1. Conversational AI and Large Language Models (LLMs)
Examples: ChatGPT, Claude, Microsoft Copilot, Google Gemini
These tools generate human-like responses, answer questions, summarize texts, write code, and even simulate interview responses. LLMs are excellent for brainstorming, drafting, explaining complex topics, and exploring alternate viewpoints.
Competencies to build:
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Prompt engineering: crafting specific, purposeful queries
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Cross-verifying AI output for accuracy and bias
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Using AI to support original thinking, not replace it
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Citing AI use appropriately in academic work
2. AI-Powered Writing and Editing Assistants
Examples: Grammarly, Quillbot, Wordtune, Notion AI
These tools refine grammar, tone, clarity, and structure. They’re useful for improving formal writing and generating variations of text for different audiences.
Competencies to build:
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Maintaining authorial voice while using AI tools
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Understanding when rephrasing becomes paraphrasing or plagiarism
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Leveraging AI for revision, not for idea generation in academic assessments
3. Text-to-Image and Design AI
Examples: Adobe Firefly, DALL·E, Canva Magic Media
These tools allow users to create visuals, illustrations, posters, or even entire slide decks from text prompts—ideal for media, marketing, education, and visual storytelling.
Competencies to build:
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Prompting clearly for artistic or visual intent
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Understanding copyright and ethical issues around AI-generated content
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Using AI visuals appropriately in academic or client-facing work
4. AI Audio and Video Tools
Examples: Runway ML, Pictory, ElevenLabs, Descript
These tools allow you to create videos, voice-overs, podcasts, and even synthetic avatars from text or uploaded content. They’re increasingly used in education, journalism, and content creation industries.
Competencies to build:
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Planning multimedia projects that integrate AI responsibly
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Considering authenticity, consent, and misinformation risks
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Using AI to enhance—but not automate—human storytelling
5. AI Search and Research Assistants
Examples: Perplexity, Elicit, Scite, Consensus
AI is changing how we conduct research by summarizing sources, generating research questions, and synthesizing literature. These tools are especially helpful for navigating academic databases and staying organized.
Competencies to build:
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Distinguishing between peer-reviewed and AI-curated sources
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Verifying citations and evaluating relevance
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Integrating AI research into structured, ethical academic writing
6. AI Coding and Development Tools
Examples: GitHub Copilot, Replit Ghostwriter, Codeium
For students in tech and engineering, these tools can assist in writing and debugging code, suggesting optimizations, and helping understand unfamiliar languages.
Competencies to build:
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Reviewing and editing AI-generated code
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Understanding limitations of AI in logic, security, and efficiency
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Avoiding over-reliance—AI won’t understand design intent or learning outcomes
7. Embedded AI in Everyday Tools
Examples: Google Workspace AI features, Notion AI, Canva Docs, Office 365 with Copilot
AI is now baked into the productivity software students use daily. Understanding how these embedded features work is essential to efficient and intentional usage.
Competencies to build:
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Using AI to speed up workflow while maintaining intentionality
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Knowing what’s generated vs. what’s user-created
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Managing transparency when collaborating with others
8. Ethics, Equity, and AI Awareness
Beyond tools, true AI literacy means understanding the broader impact of artificial intelligence on society.
Topics to explore:
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Algorithmic bias and discrimination
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Data privacy and surveillance
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The future of work and AI’s role in automation
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Deepfakes, misinformation, and the breakdown of trust in media
These are not abstract issues—they affect industries, policies, and communities. As a tertiary student, you are in a prime position to engage critically with these realities and to use AI in a way that’s both effective and ethical.
Final Thought: Your AI Literacy Is Part of Your Professional Identity
As you prepare for life beyond university, your ability to work with AI—not blindly but thoughtfully—will be a defining skill. Whether you’re entering healthcare, law, education, business, media, or the arts, AI will likely be a tool in your future.
By learning how to question AI as much as you use it, you’ll develop deeper insight, stronger critical thinking, and an edge in your field.