What You Should and Shouldn't Use AI for: A Practical Guide

Sinjun AI Blog

What You Should and Shouldn’t Use AI for: A Practical Guide

Let’s talk about AI and where it actually fits into your work and life. The hype around artificial intelligence is everywhere, but somewhere between “AI will solve everything” and “AI will ruin everything” lies the practical reality most of us need to navigate.

I’ve watched countless people struggle with this question: when should I use AI, and when should I just do it myself? The answer isn’t always obvious, but there are some clear patterns worth understanding. This guide will help you make smarter decisions about when to lean on AI and when to trust your own judgment.

When AI Works Well

Writing and Creating Content

First drafts and brainstorming are probably AI’s sweet spot right now. Need to write an email, draft a report, or outline a presentation? AI can get you past that intimidating blank page. It’s like having a colleague who’s always ready to throw ideas at the wall and see what sticks.

Here’s what works particularly well:

Email drafting: Whether you’re writing a professional introduction, a follow-up message, or a tricky response, AI can provide a solid starting point that you can personalize
Social media content: Generate multiple variations of posts to see what resonates, then refine the voice to match your brand
Meeting notes and summaries: Transform rambling conversation notes into organized, actionable summaries
Product descriptions: Create consistent, compelling descriptions for catalogs or e-commerce sites

The key here is that you’ll still need to refine and personalize the output, but that’s much easier than starting from scratch. Think of AI as getting you to the 70% mark, where you then add the final 30% that makes it truly yours.

Learning and Understanding

Explaining complex topics is another genuine strength. Ever tried to understand a technical concept and wished someone could just explain it in plain English? AI excels at breaking down complicated subjects into digestible pieces.

AI can help you with:

Technical concepts: Break down programming languages, scientific theories, or engineering principles into understandable chunks
Language learning: Get explanations of grammar rules, vocabulary in context, and practice conversations
Math and problem-solving: Work through problems step-by-step with explanations of the underlying logic
Historical context: Understand events, movements, or periods with comprehensive yet accessible explanations
Adjustable complexity: Ask for explanations at different levels, from beginner to advanced, based on your background

The conversational nature of AI makes it particularly useful for learning because you can ask follow-up questions, request different analogies, or dive deeper into specific aspects that confuse you.

Research and Information Gathering

Research and information synthesis work particularly well when you need to understand a topic quickly or gather information from multiple angles. AI can accelerate that initial research process significantly.

Effective uses include:

Literature reviews: Get an overview of key themes, important papers, or major debates in a field
Competitive analysis: Compile information about market trends, competitor strategies, or industry developments
Topic exploration: Quickly understand the landscape of an unfamiliar subject before diving deeper
Summarizing long documents: Extract key points from lengthy reports, articles, or transcripts
Connecting disparate ideas: Identify relationships between concepts from different domains

It won’t replace deep, careful research with primary sources, but it’s excellent for getting oriented or finding relevant threads to pull on. Think of it as your research assistant who helps you identify what’s worth your time to investigate thoroughly.

Programming and Technical Tasks

Code assistance and debugging have become legitimate use cases for developers at all levels. AI can suggest solutions, explain error messages, and help you learn new programming concepts.

Developers are using AI for:

Boilerplate code generation: Quickly create standard structures, configurations, or templates
Bug identification: Get suggestions for why the code isn’t working and potential fixes
Code explanation: Understand what unfamiliar code does, line by line
Documentation writing: Generate clear documentation for functions, classes, or APIs
Learning new frameworks: Get up to speed faster with examples and explanations tailored to your existing knowledge
Refactoring suggestions: Identify ways to improve code structure, efficiency, or readability

It’s like pair programming with someone who’s seen a lot of code but might occasionally suggest something that doesn’t quite work. You still need to review, test, and understand what the AI produces.

Routine and Repetitive Work

Repetitive writing tasks are perfect candidates for automation. If you’re doing the same type of task over and over with minor variations, AI can handle the heavy lifting while you focus on customization and quality control.

Great applications include:

Data entry formatting: Convert unstructured data into organized formats
Template creation: Build templates for common documents that you can then customize
Scheduling and planning: Draft agendas, create timelines, or outline project phases
Routine correspondence: Handle standard responses to common questions or requests
Report generation: Create regular reports from data, which you then verify and contextualize

When You Should Do It Yourself

Important Decisions

Critical decisions should never be outsourced to AI. Whether it’s hiring someone, making medical choices, or deciding on major business strategies, these require human judgment, accountability, and ethical consideration that AI simply can’t provide.

Keep humans in charge of:

Hiring and firing decisions: These affect people’s livelihoods and require assessment of cultural fit, potential, and nuanced interpersonal factors
Medical diagnoses and treatment plans: Your health is too important for algorithmic guesses that can’t account for your full medical history and individual circumstances
Financial investments: Major financial decisions need to account for your specific risk tolerance, goals, and life circumstances
Legal strategy: Legal situations involve complex precedents, jurisdictional nuances, and ethical considerations
Business strategy: Direction-setting decisions require vision, understanding of organizational culture, and accountability that AI can’t provide
Disciplinary actions: These require careful judgment about intent, context, and proportional response

You need skin in the game for important decisions. When something goes wrong, there needs to be a human who’s accountable and who made the call based on a comprehensive understanding and ethical reasoning.

Personal and Emotional Situations

Anything requiring emotional intelligence remains firmly in human territory. Consoling a grieving friend, mediating a workplace conflict, or providing genuine mentorship, these need an authentic human connection.

Don’t use AI for:

Comforting someone in distress: Grief, crisis, or emotional pain requires genuine empathy and presence
Relationship advice: The nuances of personal relationships need someone who truly understands human connection
Conflict mediation: Resolving disputes requires reading body language, understanding underlying emotions, and building trust
Mentorship and coaching: Real guidance comes from shared experience, vulnerability, and genuine investment in someone’s growth
Performance reviews: Feedback about someone’s work requires understanding their potential, challenges, and how to motivate them
Apologies: When you’ve hurt someone, they deserve your authentic acknowledgment, not AI-generated words

AI can suggest what to say, but it can’t replace actually caring about another person. The warmth, presence, and genuine concern that humans bring to emotional situations can’t be faked or automated effectively.

Creative and Original Work

Creative work that needs to be truly original is tricky with AI. Sure, AI can generate creative content, but if you’re trying to create something genuinely novel or establish your unique voice as an artist or writer, over-relying on AI will make your work feel generic.

Be cautious about using AI for:

Developing your unique artistic voice: Your authentic perspective is what makes creative work valuable
Original storytelling: While AI can help with structure, truly compelling narratives come from human experience and insight
Personal essays and memoirs: Your life story needs your voice, not an algorithmic approximation
Innovative design work: Breakthrough creative work comes from human intuition and risk-taking
Emotional or vulnerable writing: Authenticity in personal expression can’t be delegated
Building your creative portfolio: If you’re using AI-generated work to represent your abilities, you’re misrepresenting yourself

The creative process itself, struggling with ideas, making unexpected connections, expressing something from deep within, is often as valuable as the final product. AI can be a tool in that process, but shouldn’t replace the essential human core of creativity.

Professional and Specialized Advice

Legal and medical advice should come from qualified professionals, not AI. While AI can provide general information, it can’t account for the specific nuances of your situation, local regulations, or the ethical obligations that licensed professionals carry.

Avoid using AI as a substitute for:

Legal counsel: Laws vary by jurisdiction, cases have unique factors, and legal strategy requires expert judgment
Medical diagnosis: Symptoms can indicate many conditions, and a proper diagnosis requires examination and expertise
Tax advice: Tax situations are complex, rules change frequently, and errors can be costly
Licensed therapy: Mental health treatment requires a therapeutic relationship and professional training
Financial planning: Comprehensive financial advice needs to account for your complete financial picture and goals
Architectural or engineering plans: These require professional certification because safety is on the line

The stakes are too high for algorithmic guesses. Professionals bring years of training, ethical guidelines, liability insurance, and the ability to adapt to your specific circumstances in ways that AI can’t match.

Private and Sensitive Information

Sensitive personal information doesn’t belong in AI tools. Don’t input confidential business data, personal identifying information, or anything you wouldn’t want potentially exposed.

Keep out of AI systems:

Personal identification numbers: Social security numbers, passport details, driver’s license information
Financial account details: Bank account numbers, credit card information, passwords
Proprietary business information: Trade secrets, unreleased product details, confidential strategies
Private health information: Detailed medical records, diagnoses, treatment information
Others’ personal data: Information about clients, colleagues, or anyone else who hasn’t consented
Attorney-client privileged information: Legal communications that need to remain confidential

Even with privacy protections, it’s better to be cautious about what information you share. Once data enters an AI system, you’ve lost control over it. Many AI systems explicitly state in their terms that inputs may be used for training or improvement purposes.

Situations That Could Go Either Way

Customer Service

Customer service sits in an interesting middle ground. AI chatbots can handle routine questions efficiently, freeing up human agents for more complex issues. But they shouldn’t be your only option.

Consider this balanced approach:

Use AI for: FAQs, order status checks, basic troubleshooting, routing to the right department, and providing immediate responses outside business hours
Keep humans for: Complex problems, frustrated or upset customers, situations requiring judgment calls, cases where empathy is crucial, complaints, or escalations

The key is knowing when to escalate. An AI system that recognizes its limitations and smoothly hands off to a human creates a better experience than one that frustrates customers by failing to address their actual needs.

Best practices include:

Being transparent that customers are interacting with AI
Making it easy to reach a human when needed
Using AI to give human agents context and suggestions, not replace them
Regularly reviewing AI interactions to improve both the AI and your processes

Editing and Proofreading

Content editing and feedback can be augmented by AI, but shouldn’t be replaced by it. AI can catch grammar issues and suggest improvements, but it can’t truly evaluate whether your argument is persuasive or your story is compelling.

Here’s how to use AI effectively in editing:

Grammar and style checking: Let AI catch typos, awkward phrasing, and technical errors
Consistency checking: Ensure terminology, tone, and formatting are consistent throughout
Readability analysis: Get objective metrics on sentence length, complexity, and flow
Alternative phrasings: Generate options when you’re stuck on how to express something

But rely on humans for:

Evaluating whether the content achieves its purpose
Assessing emotional impact and persuasiveness
Judging whether the voice matches your brand or style
Determining if the logic and argumentation are sound
Making final calls on creative or strategic choices

Use AI as one tool in your editing toolkit, alongside human editors, beta readers, and your own critical judgment.

Education and Homework

Learning and education benefit from AI in some ways but suffer in others. This is perhaps the most nuanced area because the line between helpful assistance and harmful shortcut is so thin.

Beneficial uses of AI in learning:

Getting unstuck when you’re genuinely confused about a concept
Exploring topics from multiple angles to deepen understanding
Practicing skills with immediate feedback
Generating practice problems to test your knowledge
Learning at your own pace without judgment
Accessing explanations when a teacher isn’t available

Problematic uses that undermine learning:

Having AI complete assignments, you’re supposed to do yourself
Using AI to avoid engaging with difficult material
Substituting AI explanations for developing your own critical thinking
Relying on AI instead of learning to research and evaluate sources
Getting answers without understanding the process

The fundamental question is: are you using AI to enhance your understanding, or to bypass the learning process? If students use AI to complete assignments without actually learning, they’re just cheating themselves out of knowledge and skills they’ll need later.

For educators and students, consider:

The goal of most assignments is learning, not just producing output
Struggling with problems is often where real learning happens
Understanding how to get to an answer is more valuable than the answer itself
Skills you don’t practice, you won’t develop
AI can be a tutor, but shouldn’t be your brain’s substitute

Content Moderation

Content moderation is an area where AI both helps and creates new problems. AI can process vast amounts of content quickly, catching obvious violations, but struggles with context, nuance, and cultural differences.

Where AI moderation works:

Flagging clearly prohibited content for human review
Detecting spam and obvious bot activity
Identifying content that violates clear, objective rules
Processing volume that would be impossible for humans alone
Providing first-pass filtering to protect human moderators from the most disturbing content

Where human judgment is essential:

Context-dependent situations (satire vs. hate speech, news vs. glorification)
Cultural and linguistic nuances
Appeals and edge cases
Setting and refining moderation policies
Understanding evolving language and behavior patterns

The most effective systems combine AI efficiency with human judgment, using AI to scale and humans to handle complexity.

How to Decide What’s Right

When you’re wondering whether to use AI for something, work through these questions systematically. They’ll help you make a thoughtful decision rather than defaulting to either always or never using AI.

Does Someone Need to Be Accountable?

If someone needs to answer for the outcome, a human should be making the call. AI can’t be held responsible when things go wrong.

Ask yourself:

Could this decision significantly impact someone’s life or livelihood?
If something goes wrong, who would be held responsible?
Does this decision require someone to “own” the outcome?
Are there legal or regulatory requirements for human oversight?

If accountability matters, keep a human in the decision-making seat. AI can provide information and suggestions, but the final call should be yours.

Does This Need to Feel Personal?

Personal messages, creative expression, and relationship-building usually need your genuine voice. People can often tell when they’re getting generic, AI-generated content, and it affects how they perceive you.

Consider:

Will the recipient know or care if this came from AI?
Does this represent me or my organization in a meaningful way?
Is the personal touch part of the value I’m providing?
Am I building a relationship or just exchanging information?

If authenticity matters, use AI as a tool, but make sure your voice comes through clearly.

What Happens If It’s Wrong?

High-stakes situations deserve human judgment and expertise. The potential consequences of AI mistakes should guide how much you rely on it.

Evaluate:

What happens if the AI provides incorrect information?
Could an error cause financial loss, legal problems, or physical harm?
How easily can mistakes be caught and corrected?
What’s the cost of being cautious versus the cost of an error?

For low-stakes situations, AI mistakes might just be annoying. For high-stakes ones, they could be catastrophic. Match your level of AI reliance to the risk level.

Are You Trying to Learn?

If skill development is the goal, AI might rob you of valuable practice. The struggle of figuring things out is often where growth happens.

Reflect on:

Is the process of doing this task part of my learning?
Will I need this skill in the future?
Am I building competence or just getting something done?
Would using AI here prevent me from developing important abilities?

If you’re learning, use AI strategically to get unstuck or check your work, not to bypass the learning process entirely.

Is This the Same Thing You’ve Done Before?

These tasks are often perfect for AI assistance. If you’re doing something formulaic that you’ve done many times before, AI can save you time and mental energy.

Identify:

Have I done essentially this same task many times before?
Is there a clear pattern or template to follow?
Is the value in getting it done rather than in how it’s done?
Would automating this free me up for more important work?

Routine tasks are where AI often provides the clearest benefit without a significant downside.

Working with AI Effectively

The most useful way to think about AI isn’t as a replacement for human effort, but as a collaborator that excels at certain tasks while being completely inadequate at others. The people who use AI most effectively treat it like a capable but inexperienced assistant, useful for specific tasks, requiring oversight, and occasionally brilliant but often needing correction.

Treat AI Like a Junior Assistant

Think of AI as your junior colleague:

You wouldn’t let a new intern make executive decisions or represent your company without supervision
You would delegate routine tasks and use their work as a starting point
You’d review their output carefully and expect to make corrections
You’d appreciate their speed while recognizing their limitations
You’d give clear instructions and provide context

Apply the same logic to AI. It’s a tool that amplifies your capabilities, not a replacement for your judgment.

Know Who Does What

The most productive relationship with AI involves a clear role division:

AI handles:

Initial research and information gathering
First drafts and basic structure
Repetitive formatting and processing
Pattern recognition in large datasets
Routine responses and standard procedures
Brainstorming and generating options

Humans handle:

Final decision-making and accountability
Quality control and verification
Strategic thinking and planning
Emotional intelligence and relationships
Ethical considerations and values
Creative vision and originality
Adapting to novel situations

The magic happens when you combine AI’s speed and processing power with human judgment, creativity, and emotional intelligence.

Developing Good Habits

As you integrate AI into your workflow, develop habits that keep you in control while maximizing the benefits.

Always Verify Important Information

Never trust AI output blindly:

Fact-check important claims, especially statistics or specific details
Test code before deploying it
Read through written content before sending it
Verify that advice aligns with current best practices
Cross-reference with authoritative sources when it matters

Be Transparent About AI Use

Keep track of how you’re using AI:

Note when AI contributed to the work you’re sharing
Be transparent with colleagues and clients about AI usage
Document your process so others can learn from it
Keep records of AI-assisted decisions in case you need to explain them

Keep Learning and Improving

Stay engaged with what AI is producing:

Try to understand AI suggestions rather than just accepting them
Notice patterns in where AI succeeds and fails
Experiment with different approaches and prompts
Keep developing your own skills alongside using AI

Planning for Change

AI capabilities are evolving rapidly, which means the boundaries of what’s appropriate to use it for will shift over time. What’s a bad idea today might be perfectly reasonable tomorrow, and vice versa.

Stay flexible by:

Regularly reassessing your AI usage patterns
Staying informed about new capabilities and limitations
Listening to feedback from others about AI-assisted work
Being willing to adjust your practices as technology and norms evolve
Maintaining your own skills so you’re not overly dependent on any tool

Final Thoughts

AI works best when it handles the grunt work while you handle the judgment calls, the creative vision, the emotional intelligence, and the accountability. Keep those boundaries clear, and you’ll find AI genuinely useful without falling into the trap of either over-reliance or stubborn resistance.

The goal isn’t to use AI for everything or to avoid it entirely. It’s to be thoughtful and strategic about where it adds value and where it creates problems. Use it where it makes you more efficient and effective. Skip it where human qualities, judgment, creativity, empathy, accountability, are what actually matter.

In the end, AI is just a tool. A powerful, versatile, sometimes surprising tool, but still a tool. And like any tool, its value depends entirely on how skillfully and appropriately you use it.

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