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In the past, the criteria for selecting executives mainly revolved aroundstrategic vision, people leadership, and management experience. But today, asartificial intelligence (AI) permeates every business activity—from dataanalytics and supply chain optimization to personalized customer experiences—therole of executives has also "upgraded” its requirements.
A question many hiring committees are now asking: Should businesses prioritizean inspiring leader, or a "tech-savvy leader” who understands AI ?
1. The executive hiring landscape in the AI era
AI is no longer experimental. According to McKinsey, by 2030, AI couldcontribute over USD 15.7 trillion to the global economy. This means:
- Executives who lack AI knowledge will struggle to make quick, data-driven,automated decisions.
- Executives who are only strong in technology but lack leadership skills willfind it hard to inspire and align teams.
Three major pressures are reshaping executive recruitment:
- Rapid technological innovation – cycles measured in months,not years.
- Agile business models – from hybrid work to digitalplatforms.
- Managing volatility – balancing stability while stayingopen to experimentation.
AI is becoming a strategic driverin business planning.
2. Leadership skills – the irreplaceable foundation
Leadership remains the core of any executive role. An AI-era leader mustpossess:
- Strategic vision: Not just understanding what AIis, but where AI can take the business.
- Inspiration: Employees don’t always adapt quickly to newtech; leaders must help them see value and opportunity.
- Change management: AI adoption often transforms processes,KPIs, and even organizational structures.
- Decision-making in uncertainty: Data is essential, but itcannot replace leadership judgment.
Case in point: In 2023, a Southeast Asian retail group adoptedAI for demand forecasting. The CEO had to persuade regional managers, who wereused to manual methods. It took six months of consensus building and trainingbefore full adoption.
Leaders in the AI era don’t just make decisions—they guide people throughchange.
3. Tech skills – the key to driving innovation
On the other hand, in this era, a "tech-blind” executive is unlikely to makeaccurate strategic choices. Critical tech skills include:
- Understanding AI fundamentals: Concepts like machinelearning, natural language processing, and computer vision.
- Data literacy: Ability to read analysis reports, ask theright questions, and validate AI outputs.
- Risk awareness: Knowledge of data security, AI ethics, andregulatory compliance.
- Digital transformation roadmap: Integrating AI into areassuch as marketing, production, HR, and R&D.
Many financial institutions now hire Chief Digital Officers (CDOs) or add techcompetencies to CEO requirements to ensure AI strategies align withinfrastructure and company culture.
4. A practical answer: the "hybrid” leadership model
Hiring committees often face a dilemma:
- Candidate A: An outstanding leader but with only basic AIknowledge.
- Candidate B: A tech expert with successful AIimplementation experience, but limited people management at scale.
Global recruitment experience shows the ideal is a blend of both—but suchcandidates are rare. Practical solutions include:
- Hiring a strong leader and pairing them with a CTO/CDO with deep techexpertise.
- Hiring a tech leader and investing in leadership and people managementtraining.
A study by Harvard Business Review found that companies applying a"hybrid leadership” model—combining business experience with techknowledge—achieved revenue growth 20% higher than the industry average.
This model balances human strategywith technological strategy.
5. Building a balanced hiring framework
To avoid the "either/or” trap, hiring committees can design criteria across fourdimensions:
- Strategy & Vision
- Ability to define AI goals linked to business growth.
- Skill in quantifying costs and benefits of AI adoption.
- People Management
- Experience leading across departments and generations.
- Internal communication skills around tech-driven change.
- Technology Competence
- Understanding AI principles and industry-specific tech trends.
- Ability to select and oversee AI solution providers.
- Innovation & Risk Management
- Controlled experimentation mindset.
- Awareness and management of AI risks (legal, security, ethics).
Tip: During interviews, use real case studies instead oftheoretical questions to assess both leadership and tech skills.
6. The rise of the "hybrid leader”
The AI era demands executives who are not only strategic navigators but alsotechnology enablers. Businesses must seek—or develop—hybridleaders: strong in leadership, fluent in AI.
With over 20 years of experience in executive recruitment, HR2B has helped manycorporations in Vietnam identify next-generation leaders who meet bothleadership and technology requirements.
If your business is debating between leadership and tech skills, let HR2B helpyou find candidates who bring both to the table.
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