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Radical's APAC-framework: the KPIs of the future.

A human-centric selection model for AI professionals

Why human qualities become the new hard requirements for AI professionals, and how APAC measures them against recent scientific research.

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The KPIs of the future

In this era of AI, technical skills have a shorter shelf life than ever. That makes the traditional CV check outdated for recruitment. At Radical, we don't just select on what you can do with code, but on who you are as a person and professional. Our methodology, the APAC-framework, is based on recent scientific research and labour market data from 2025 and 2026.

Radical Recruitment is building a selective community of AI professionals who make a difference through scientifically grounded qualities. The four pillars below summarise what we measure, and why.

“Now that AI takes over the 'hard' tasks, the 'soft' qualities become the new hard requirements.”
The Radical thesis
< 2.5years
Half-life of a technical skill in tech. In AI, likely months.
0%
More innovative AI teams that score high on empathy and psychological safety (MIT Sloan, 2024).
0pillars
Adaptability, Personality, Awareness, Connection. The APAC framework.
0sources
Peer-reviewed research and industry studies underpin our selection model.
01·Adaptability & Curiosity

Adaptability & Curiosity

The science. According to the World Economic Forum (2025), 'Analytical Thinking & Agility' is the most important skill group. We assess using the Career Adapt-Abilities Scale (Savickas) to ensure our people don't just follow the hype, they outlast it.

Radical's focus. Intellectual curiosity and the ability to 'unlearn'.

02·Values over Volume

Values over Volume

The science. Daniel Pink's research on motivation (Drive) shows that autonomy, mastery, and purpose are the real drivers of innovation.

Radical's focus. We look for people motivated by the impact of their work, where salary is a result of success, not the sole objective.

03·Awareness & Connection

Awareness & Connection

The science. The Stanford AI Index Report (2025) shows that ethical risks are the biggest barrier to AI adoption. We select on Ethical Courage, based on the work of Treviño, and on Empathic Capacity (Goleman).

Radical's focus. AI is a tool for people. We seek the builders who never lose sight of the human dimension.

04·Agency & Accountability

Agency & Accountability

The science. Bandura's Self-Efficacy Theory demonstrates that professionals with a high degree of agency perform better in unstructured environments. We look for active participants rather than passive executors.

Radical's focus. Ownership over the outcome, not just the task.

Our APAC-framework (Adaptability, Personality, Awareness, Connection) aligns with the shift visible in 2025 and 2026 across the global recruitment market: from technical fit to human-centric fit.

Methodology
APAC is a validation framework, not a personality quiz.

Every pillar maps to published research (Career Construction Theory, Self-Efficacy Theory, the WEF skills reports and Isabelle Hau at Stanford). We select for the qualities that science identifies as AI-proof, and we re-validate the model every year.

Scientific foundation

Four human qualities, four bodies of research. Below we summarise the studies that underpin each APAC pillar and the practical implication for hiring AI professionals.

Adaptability

Research shows that the half-life of a technical skill in the tech sector is now less than 2.5 years. For AI, this is likely a matter of months.

The Radical philosophy: adaptability is not just about learning a new tool. It is about cognitive flexibility, the ability to let go of old mental models. Radical trains candidates to be comfortable with uncertainty and to switch quickly between different levels of abstraction. This is the only insurance against technological obsolescence.

  • World Economic Forum, Future of Jobs Report 2023 & 2025. Consistently identifies 'Analytical Thinking' and 'Resilience, Flexibility and Agility' among the top 3 skills for the AI era. Adaptability is more important than domain knowledge.
  • Savickas, M. L., & Porfeli, E. J. (2012), Career Adapt-Abilities Scale. The definitive work on career adaptability. Professionals who score highly on 'concern, control, curiosity, and confidence' perform better in volatile markets such as AI.
  • HBR (2024), The New Science of Adaptability. In high-growth tech companies, the Adaptability Quotient (AQ) is a better predictor of success than IQ.

Personality

Traditionally, IT recruitment has focused on introverted, analytical profiles. However, in the era of generative AI, where AI writes the code, value is shifting toward creativity and curiosity.

The Radical philosophy: Radicals are 'prompt engineers of the soul'. They must be able to ask the right questions of the AI. Analytical ability is the foundation, but creativity is the differentiator that determines whether an AI solution is innovative or merely iterative.

  • Carol Dweck, Mindset: The New Psychology of Success. The foundation of the focus on intrinsic motivation to improve. In AI, a growth mindset is essential to avoid being paralysed by the pace of change.
  • Kashdan, T. B., et al. (2018/2023), Five-Dimensional Curiosity Scale Revised. Distinguishes different types of curiosity. For our community, 'Stress Tolerance' and 'Joyous Exploration' are particularly relevant.
  • Pink, D. H., Drive. For complex, cognitive roles such as AI development, autonomy, mastery, and purpose are far stronger motivators than money.

Awareness

This touches on leadership qualities. It is about emotional intelligence and ethical awareness.

The Radical philosophy: awareness means understanding the impact of technology on the end user and society. A Radical dares to say 'no' to a technically feasible but ethically undesirable solution. This requires courage and strong communication skills, something rarely trained in standard CS programmes.

  • Stanford University, AI Index Report 2025. Highlights the enormous gap between technical capability and ethical implementation. Supports the focus on ethical awareness as a scarce commodity.
  • Treviño, L. K., & Nelson, K. A., Managing Business Ethics. Draws the link between moral courage and leadership in tech organisations. Validates the question of whether professionals dare to say 'no' to unethical projects.
  • IEEE (2023), Ethically Aligned Design. The reference text for ethics in AI systems. The maker, the human, must maintain an active awareness of the impact on society.

Connection

Traditional tech recruitment often treats the professional as an isolated resource judged purely on technical output. However, as AI systems become more autonomous, the critical value of the expert shifts toward the ability to remain anchored in human context and ethics.

The Radical philosophy: Radicals are architects of the human dimension. They possess the ability to look inward, through self-reflection, and from there build connection with their team and community around collective human values. This connection is the real 'human in the loop' and provides inherent risk management.

  • Daniel Goleman, Emotional Intelligence & Social Intelligence. Self-awareness (connection with oneself) is the first step toward effective collaboration.
  • MIT Sloan Management Review (2024), The Empathy Advantage in AI. AI teams scoring highly on psychological safety and human connection are 40% more innovative.
  • Brené Brown, Dare to Lead. Research on vulnerability and connection. Supports awake connection as the basis for trust in high-performance teams.
  • Albert Bandura, Self-Efficacy: The Exercise of Control. The scientific foundation for agency. People who believe they can influence their environment perform significantly better in unstructured AI environments.
  • Patrick Lencioni, The Five Dysfunctions of a Team. Crucial for accountability and ownership. The best teams consist of people who hold both themselves and each other uncompromisingly accountable.

Sources

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