Skills Over Tenure: How SCG Chemicals Is Hiring for 2026
The hiring market is changing fast. Tech, shifting employee expectations, and global economics are forcing leaders to rethink how they find and grow talent. Napit Teparak, People and Organizations Director at SCG Chemicals, puts it plainly: in 2026, skills, learning agility, and AI readiness beat traditional experience.
This shift is clear on the ground. Degrees matter less than proof of capability. Years in a seat matter less than the ability to learn and adapt. And AI literacy is no longer a bonus - it's the baseline.
What this means for HR
SCG Chemicals is rebuilding its hiring approach around capability and outcomes. "Role profiles are being redesigned around skills and outcomes, and digital and AI literacy are now baseline expectations," says Napit. The goal: hire people who can learn fast, work with AI confidently, and drive compounding impact over time.
- Faster AI adoption since COVID
- Agile hiring strategies that work across geographies and functions
- Balance GenAI tools with in-person interviews to keep the human connection
- Automation and smarter tech to cut time-to-hire - speed now matters
- Efficiency without losing a personal, human candidate experience
- Shift from role-centric to people-focused hiring tied to purpose and values
- Diversity and inclusion as a core pillar
- Structured interviews for technical depth and culture fit
- Streamlined, end-to-end candidate experience
- From transactional recruiting to relationship-led talent attraction
- Skills-based selection matched to values like integrity, respect, teamwork, innovation
- Use AI to streamline process and surface the right talent faster
Leaders also stress rigor. Treat every hire like a major investment: tighter interview rubrics, deeper due diligence, and a clear read on mindset. Culture fit isn't a buzzword - it's a performance driver.
Build Before You Buy: The Case for Internal Mobility
SCG Chemicals is betting on its own people. "We deliberately build AI capability from within, because we believe that employees who understand our processes can scale AI impact faster."
How they do it: "Through structured pilot projects, we test, learn, and then build fast and scale successful practices across the business." The aim is simple: "Empower our people, lift productivity, and create sustainable momentum for AI-enabled ways of working."
This matches a wider regional view. Internal mobility increases retention, boosts morale, and helps companies adapt as roles change faster than external markets can supply skills.
Workforce Models Are Shifting
It's not just what you hire for - it's how teams are set up to work. Leaders are embracing:
- Hybrid and remote-first structures
- Fractional, project-based, and gig models
- Flexible arrangements built on autonomy and accountability
Companies like Primer show that remote-first success comes from deliberate flexibility, culture by design, and distributed teams that stay connected and accountable.
AI in Hiring: Benefits and Risks
AI now supports sourcing, ranking CVs, writing job ads, transcribing interviews, and predicting time-to-hire. It speeds up work and improves signal - when used well.
But leaders remain cautious. As one people leader noted earlier, "AI is only as good as the data it learns from," and it can reinforce bias if left unchecked. Human judgment is still essential for mindset, potential, and culture fit - areas models can't fully read yet. For compliance and fairness, see the EEOC's guidance on AI in employment.
The Skills That Will Matter Most in 2026
- Strong technical capability
- Adaptability and confidence with ambiguity
- Commercial awareness
- Cloud and DevOps fluency
- APAC language proficiency
- Domain depth in payments, commerce, or other verticals
- Thought leadership and community engagement
- Real-world problem solving with AI
The leaders out front treat "people experience" like product work: test, listen, iterate, improve. Trust and flexibility matter - so do clarity, accountability, and fair reward. And yes, networks still open doors long before roles go public.
Your 90-Day Hiring Playbook
- Rewrite role profiles: list skills, outcomes, and must-have AI literacy. Drop degree and tenure as hard gates unless legally required.
- Add a skills screen: short work samples or take-home tasks that mirror the job. Score with a rubric.
- Standardize interviews: structured questions for both capability and values. Calibrate interviewers with shadowing and scoring guides.
- Mix AI and human touch: use tools for sourcing, screening, and scheduling; keep humans for motivation, mindset, and team fit.
- Bias checks: review job ads, scoring criteria, and AI outputs. Track pass-through rates across demographics and adjust.
- Candidate UX: shorten steps, set clear timelines, and communicate proactively. Measure candidate NPS.
- Internal-first: post roles internally, map skills across teams, and create short sprints for internal candidates to prove fit.
- Speed with discipline: set SLA targets (e.g., 7 days to slate, 21 days to offer) without lowering the bar.
- Upskill your team: run AI literacy sessions for recruiters and hiring managers. Build repeatable playbooks and update monthly.
If your team needs structured upskilling on AI tools and workflows, explore practical programs here: Latest AI courses.
Bottom Line
Hire for skills, learning speed, and AI readiness. Build from within. Keep the process fast, fair, and human. Do this well, and you'll fill today's roles while building tomorrow's capability - without guessing what the market will throw at you next.
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