Hiring in the AI Era: Which Skills to Look For

With AI handling many routine tasks, the skills HR should look for have changed. A map of the skills that still hold value and those that are losing it.

In Thailand's 2026 job market, AI has taken over routine work in many functions, from data entry and resume screening to writing first drafts of documents. The skills HR needs to look for when hiring have clearly changed from 5 years ago. Skills that once made candidates stand out, such as advanced Excel or writing good reports, are becoming the baseline. Most of the new skills the market values highly are things AI finds hard to do.

Skills AI Still Finds Hard

Skills that earn premium pay in the 2026 market

Skills that still command high value

• Judgment in situations with multiple trade-offs and no single answer
• Framing ambiguous problems so AI can work on them
• Evaluating AI output and knowing what is right and what is wrong
• Talking with people in ways that require empathy and trust
• Strategic thinking that connects signals from multiple sources
• Managing conflict and high-stakes negotiations
• Creativity that goes beyond existing patterns

These skills are hard to teach, slow to develop, and require real on-the-job experience. In a candidate-short market, people with these skills earn a premium of 20 to 40 percent above baseline.

New Skills Born From Working With AI

Skills that did not appear in any 2020 textbook are now in market demand.

New skills we see

1. Prompt engineering that gets good results from LLMs
2. AI evaluation that judges output quality
3. Workflow design that combines humans and AI at the right steps
4. Data interpretation that reads insights from AI-generated dashboards
5. AI ethics and bias detection
6. Debugging pipelines that include AI in the process

These skills are not in university curricula. People acquire them by using tools, experimenting, and learning from communities. Hiring accurately means looking at portfolios and work samples more than degrees.

Assessing New Skills in the Hiring Process

Measuring AI-era skills uses different methods from measuring traditional skills.

Assessment methods

• Live exercises using AI tools, observing how the candidate uses them
• Case studies where the AI output is wrong, to see whether the candidate catches it
• Take-home assignments using real AI, looking at the workflow and the overall result
• Portfolio reviews of work that combines human and AI
• Behavioral interviews asking about trade-offs decided in real work

Banning AI during assessment means missing important signals. People who use AI well in real life will use it at work every day. Testing in realistic conditions gives more accurate information.

Hiring in the AI era is not about finding people who do not use AI, but finding people who use AI well and know when not to.

Skills Losing Value

Skills that once commanded a premium are becoming baseline or below.

Skills declining in value

• Excel at the level of pivot tables and basic formulas, which AI can already do
• Writing first drafts of documents, which AI can help with
• Summarizing meeting notes, which AI does instantly
• First-round resume screening, which ATS can do
• Analyzing straightforward trends in data
• Translating general documents

These skills are not suddenly worthless, but they are no longer differentiators. Candidates who sell themselves on these skills need to add others that AI cannot yet do.

Designing JDs for the AI Era

JDs that attract the right candidates use updated language.

JD adjustments

• Stop asking for advanced Excel or detailed Word skills
• Emphasize critical thinking and judgment
• Specify the AI tools the team uses and wants candidates to be proficient in
• Ask for a portfolio of work that uses AI intelligently
• Open up to non-traditional backgrounds with matching skills

Writing JDs this way attracts candidates who can adapt to AI and filters out people who still think AI is a tool only for engineers.

Reskilling Current Staff for AI

New hiring is not enough. Current staff need reskilling too.

Programs that work

1. A 2 to 3 day AI literacy program everyone goes through
2. Tool-specific training for the AI the team uses
3. Use case workshops where teams experiment with real work
4. A community of practice for AI champions in each team
5. Measuring AI proficiency in the skills inventory

This reskilling investment reduces resistance to AI in the organization and keeps current staff from fearing replacement. Read Reskilling employees in your organization for a deep dive.

Connecting to the Bigger Strategy

Hiring in the AI era connects to the entire workforce strategy.

Connect it with Agentic AI in HR, where HR is the first team to use AI in real work, and Responsible AI in HR, which sets guardrails.

Building a Skills Inventory that covers AI skills is the foundation for people decisions, and Workforce Planning maps where teams need AI skills.

For HR who want to learn, explore the AI for HR courses in Plants.work Learn or browse new roles the market wants on the Jobs page. In short, hiring in the AI era is not about fearing AI will replace people, but about finding people who use AI intelligently and know when not to. Those who understand this difference hire accurately and economically.