How many skills should I list on my resume?

List 8 to 15 skills on your resume, depending on the format and available space. Focus on quality over quantity. Every skill should be relevant to the job you are applying for. A targeted list of 10 highly relevant skills is more effective than a generic list of 25 that includes everything you have ever learned. Organize them into categories (Technical Skills, Tools, Soft Skills) for easy scanning.

Should I include soft skills on my resume?

Yes, but present them differently than hard skills. Instead of simply listing 'leadership' or 'communication,' demonstrate them through your experience bullet points. For example, 'Led a cross-functional team of 8 to deliver a product launch 2 weeks ahead of schedule' demonstrates both leadership and project management without just listing them as words. If you do include soft skills in your skills section, choose only those most relevant to the role.

What AI skills should I add to my resume in 2026?

The most valuable AI skills for resumes in 2026 include prompt engineering for large language models, experience with AI tools like ChatGPT, Claude, or Copilot in professional workflows, understanding of machine learning concepts, data analysis with AI-powered tools, and AI ethics awareness. For technical roles, add specific frameworks like TensorFlow, PyTorch, LangChain, or experience with fine-tuning models. For non-technical roles, focus on how you use AI tools to improve productivity, analysis, or decision-making in your field.

How do I list skills I am still learning?

Only list skills you can confidently discuss and demonstrate in an interview. If you are actively learning a skill and have applied it in at least one project or course, you can include it. Use honest descriptions if your resume format allows it, such as listing it under a 'Currently Developing' subsection. Never list a skill at a proficiency level you cannot back up. Misrepresenting your skill level will become apparent during technical interviews or on the job.

Do I need different skills sections for different jobs?

Yes. Your skills section should be tailored for each application, just like the rest of your resume. Review the job description and prioritize skills that appear in the requirements. A data analyst applying to a marketing analytics role should emphasize SQL, Tableau, and A/B testing, while the same person applying to a financial analytics role should lead with Excel modeling, financial reporting, and Python for data analysis.

Skills to Put on Your Resume in 2026: Hard Skills, Soft Skills & AI Skills

Published January 30, 2026

The skills section of your resume is one of the first places recruiters look. It takes up only a few lines of space, but it carries enormous weight. Your skills tell employers what you can do, signal whether you are current with industry trends, and directly influence whether your resume passes through Applicant Tracking Systems. In 2026, the skills landscape has shifted meaningfully, especially with the rise of AI tools that have transformed how work gets done across every industry.

This guide breaks down the most important hard skills, soft skills, and AI-related skills to include on your resume this year, with practical advice on how to present them effectively.

Understanding the Three Categories of Resume Skills

Hard skills

Hard skills are specific, teachable, and measurable abilities that you acquire through education, training, or practice. Examples include programming in Python, financial modeling in Excel, operating specific machinery, or fluency in a foreign language. Hard skills are typically listed explicitly in job descriptions and are the primary keywords ATS software searches for.

Soft skills

Soft skills are interpersonal and behavioral qualities that affect how you work with others and approach problems. Communication, leadership, adaptability, and critical thinking are classic examples. While harder to quantify, soft skills are consistently ranked by employers as critical for workplace success, especially for leadership and client-facing roles.

AI and emerging technology skills

This is the category that has evolved most dramatically. In 2026, AI literacy is no longer optional for knowledge workers. From using generative AI for content creation and coding assistance to understanding machine learning outputs and implementing AI-powered workflows, these skills now appear in job descriptions across industries far beyond tech.

Most In-Demand Hard Skills in 2026

Data analysis and visualization

The ability to collect, interpret, and present data remains one of the most sought-after skills across all industries. Employers want candidates who can turn raw data into actionable insights. Key tools and skills include:

SQL: The foundation of data querying, relevant to virtually every data-related role
Python and R: For statistical analysis, data manipulation, and building analytical pipelines
Tableau, Power BI, and Looker: For creating dashboards and visual reports that stakeholders can understand
Excel (advanced): Pivot tables, VLOOKUP/XLOOKUP, macros, and data modeling remain essential
A/B testing and statistical methods: For evidence-based decision-making

Cloud computing and DevOps

As organizations continue migrating to cloud infrastructure, cloud skills command premium salaries:

AWS, Azure, Google Cloud Platform: At minimum, familiarity with one major cloud provider
Docker and Kubernetes: Container orchestration for scalable applications
CI/CD pipelines: Jenkins, GitHub Actions, GitLab CI for automated deployment
Infrastructure as Code: Terraform, CloudFormation, Ansible

Software development

Programming skills remain in high demand, with some shifts in which languages and frameworks are most valued:

JavaScript/TypeScript and React/Next.js: Dominant in web development
Python: Versatile across web development, data science, AI, and automation
Rust and Go: Growing rapidly for systems programming and backend services
Mobile development: Swift, Kotlin, React Native, Flutter

Cybersecurity

With increasing digital threats, cybersecurity skills are critical beyond just IT departments:

Security assessment and penetration testing
Identity and access management (IAM)
Incident response and forensics
Compliance frameworks (SOC 2, ISO 27001, GDPR)

Digital marketing and SEO

For marketing and business roles, the technical component has grown substantially:

Search engine optimization (SEO) and SEM
Marketing automation (HubSpot, Marketo, Salesforce Marketing Cloud)
Analytics (Google Analytics 4, attribution modeling)
Content strategy and conversion rate optimization

Financial and business skills

Financial modeling and forecasting
Business intelligence tools
ERP systems (SAP, Oracle)
Risk assessment and management

Most Valued Soft Skills in 2026

Soft skills have not been displaced by AI; they have become more valuable. As AI handles more routine tasks, human skills that AI cannot replicate become increasingly differentiated.

Critical thinking and problem-solving

The ability to analyze complex situations, question assumptions, and develop effective solutions is consistently ranked as the top soft skill by employers globally. In an era of AI-generated content and analysis, the ability to critically evaluate outputs is essential.

Communication

Clear written and verbal communication, especially the ability to explain complex concepts to non-technical stakeholders, is invaluable. This includes presentation skills, technical writing, and cross-cultural communication for global teams.

Adaptability and continuous learning

The pace of change in tools, processes, and technologies makes adaptability a survival skill. Employers want people who learn new tools quickly, embrace change, and proactively develop new competencies. The fact that you are reading this article to update your skills knowledge is itself a signal of this quality.

Collaboration and cross-functional teamwork

Remote and hybrid work has made collaboration more intentional and more valued. The ability to work effectively across departments, time zones, and disciplines is critical for modern organizations.

Emotional intelligence

Understanding and managing your own emotions while being attuned to others is especially important for leadership roles. Emotional intelligence encompasses empathy, self-awareness, conflict resolution, and the ability to give and receive constructive feedback.

Leadership and mentoring

Even for non-management roles, the ability to take initiative, guide others, and drive outcomes without formal authority is highly valued. Include leadership examples in your experience bullets, not just in your skills list.

AI Skills That Belong on Your Resume in 2026

AI has moved from a niche technical specialty to a mainstream workplace competency. Here are the AI-related skills that employers are actively looking for, categorized by technical depth:

For everyone (regardless of role)

AI-assisted productivity: Using tools like ChatGPT, Claude, Copilot, or Gemini to enhance writing, analysis, brainstorming, and workflow automation
Prompt engineering: The skill of crafting effective prompts to get useful outputs from large language models. This is now relevant for writers, marketers, analysts, project managers, and virtually every knowledge worker
AI-powered tool proficiency: Notion AI, Canva AI, Grammarly, AI-enhanced Excel features, and similar tools that have integrated AI into everyday workflows
AI output evaluation: The ability to critically assess AI-generated content for accuracy, bias, and quality before using it in professional work

For technical roles

Machine learning frameworks: TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers
Natural Language Processing (NLP): Text classification, sentiment analysis, named entity recognition, and working with LLM APIs
Computer vision: Image classification, object detection, OCR
MLOps: Model deployment, monitoring, versioning (MLflow, Weights & Biases, SageMaker)
LLM application development: Building applications using LLM APIs, RAG (Retrieval-Augmented Generation), LangChain, vector databases
AI coding assistants: Proficient use of GitHub Copilot, Cursor, and similar AI pair-programming tools to accelerate development

For data and analytics roles

Automated machine learning (AutoML) platforms
AI-enhanced data analysis and visualization
Predictive analytics and forecasting models
Data pipeline automation with AI components

For business and strategy roles

AI strategy and implementation planning
AI vendor evaluation and selection
AI ethics, governance, and responsible AI frameworks
Change management for AI adoption

How to Present Skills Effectively on Your Resume

Knowing which skills to include is only half the challenge. How you present them matters equally. Follow these principles:

Use a dedicated skills section

Create a clearly labeled "Skills" or "Technical Skills" section near the top of your resume, organized by category. This gives both ATS software and human readers a quick scan of your capabilities. For detailed formatting guidance, see our comprehensive guide on how to list skills on a resume.

Demonstrate skills through experience

Listing "Data Analysis" as a skill is necessary for ATS purposes, but demonstrating it through your experience is what convinces humans. "Analyzed customer acquisition data using SQL and Python, identifying a segment that improved campaign ROI by 35%" proves your data analysis ability in a way that a single keyword cannot.

Match skills to the job description

This is critical and worth repeating: your skills section should be tailored for each application. Use the exact terminology from the job description. If they say "stakeholder management," do not write "client relations" even if it means the same thing. ATS systems and recruiters respond to exact matches. Our step-by-step guide on tailoring your resume for every job application covers this process in detail.

Avoid outdated or generic skills

Remove skills that no longer differentiate you. In 2026, listing "Microsoft Office" or "Internet research" is like listing "can use a telephone." These are assumed baseline competencies. Instead, specify advanced proficiency: "Advanced Excel (Power Query, DAX, macros)" or "Salesforce CRM administration" adds real value.

Do not rate your own proficiency

Avoid star ratings, progress bars, or percentage-based skill evaluations. They are subjective, they waste space, and they are invisible to ATS parsers. If you want to indicate proficiency levels, use descriptive terms like "Expert," "Proficient," or "Working Knowledge" alongside each skill, though even this is optional.

Industry-Specific Skill Recommendations

Software Engineering: TypeScript, React, Node.js, cloud platforms, system design, CI/CD, AI coding tools

Data Science: Python, SQL, machine learning, deep learning, statistical modeling, data storytelling

Product Management: User research, A/B testing, roadmap planning, SQL, analytics tools, stakeholder management

Marketing: SEO, content strategy, marketing automation, GA4, CRO, AI content tools

Finance: Financial modeling, valuation, risk analysis, Bloomberg/Reuters, Python for finance, regulatory compliance

Design: Figma, user research, interaction design, design systems, accessibility (WCAG), prototyping

Healthcare: EHR systems, clinical data management, HIPAA compliance, medical coding, telehealth platforms

Building Your Skills Over Time

Your skills section is not static. The professionals who advance fastest are those who intentionally develop new skills each year. Some practical approaches:

Take online courses: Platforms like Coursera, Udemy, NPTEL, and LinkedIn Learning offer courses on every skill mentioned in this article
Build projects: The best way to learn a skill is to use it. Personal projects, open-source contributions, and volunteer work all build demonstrable skills
Get certified: Industry-recognized certifications (AWS, Google, PMP, CFA) validate your skills to employers
Stay current: Follow industry leaders, read relevant publications, and attend conferences or webinars in your field

Once you have identified the right skills for your target roles, use EasyResume's free resume builder to create a professionally formatted resume that presents them effectively. The builder's templates are designed to give your skills section the prominence and clarity it deserves while maintaining ATS compatibility.

Final Thoughts

The skills you put on your resume in 2026 should reflect three things: what you genuinely know and can do, what your target employers are looking for, and where your industry is heading. The rise of AI has not made human skills less important; it has shifted which human skills matter most. Technical proficiency with AI tools, combined with critical thinking, communication, and adaptability, creates a skill profile that is valuable across virtually every industry. Invest in developing these skills, present them strategically on your resume, and keep updating both as your career evolves.