How to Hire AI Talent in 2026: Assessing AI Skills, Fluency & Leadership
Artificial intelligence is changing not only how businesses operate, but also how they hire.
For employers, the challenge is no longer simply finding candidates who have worked with AI tools. Companies increasingly need professionals who can apply AI to real business problems, understand its limitations, work effectively with emerging technologies and, at leadership level, make informed decisions about AI strategy, governance and implementation.
This is creating a new challenge for recruitment teams: how do you identify genuine AI capability rather than simply matching AI keywords on a CV?
In the UAE, the shift is already visible. PwC's 2026 AI Jobs Barometer found that the share of UAE job postings requiring AI skills increased from 1.0% in 2021 to 3.2% in 2025, more than tripling in four years. AI hiring is also expanding beyond traditional technology roles into sectors including financial services, professional services, manufacturing, energy, consumer markets and healthcare.
For employers building an AI-ready workforce, the answer lies in moving beyond traditional recruitment criteria and assessing AI skills, practical experience, adaptability and leadership capability together.
What Is AI Talent?
AI talent is no longer limited to machine learning engineers or data scientists.
As AI becomes embedded across business functions, organizations may need different levels of AI capability across their workforce.
This can include:
Artificial intelligence and machine learning engineers
Generative AI specialists
Data scientists
AI architects
Machine learning engineers
MLOps professionals
AI cybersecurity specialists
Data engineers
Software engineers with AI integration experience
AI product managers
Digital transformation leaders
Heads of AI
CTOs and CIOs with AI transformation experience
At the same time, many non-technical roles increasingly require some level of AI fluency.
A finance professional may use AI for analysis. A marketing leader may use generative AI for content and research. A recruiter may use AI for sourcing and workflow automation. A senior executive may need to evaluate AI investments and understand their operational and governance implications.
This means companies increasingly need to distinguish between AI expertise and AI fluency.
AI Fluency vs AI Expertise: What's the Difference?
AI expertise and AI fluency are not the same thing.
AI expertise generally refers to advanced technical capability. It may involve developing, deploying, integrating or managing AI systems.
AI fluency is broader. It refers to the ability to understand how AI can be used, evaluate its outputs, recognize its limitations and apply it appropriately within a particular role.
For example, a CTO does not necessarily need to build a machine-learning model. However, the CTO may need to understand:
Where AI can create business value
Which AI technologies are relevant
How AI projects should be evaluated
Data and cybersecurity considerations
AI governance and responsible use
How AI changes technology teams and workflows
What specialist talent the organization needs
This distinction is becoming increasingly important as AI changes the skills employers look for.
PwC's 2026 Global AI Jobs Barometer, based on more than one billion job advertisements across 27 countries, found that jobs requiring specific AI skills were growing much faster than the overall jobs market. It also found increasing demand for human skills such as judgement, leadership and creativity alongside AI capabilities.
Why Hiring AI Talent Is Different From Traditional Recruitment
Traditional recruitment often begins with a job description, a list of qualifications and a search for candidates whose CVs contain the required keywords.
That approach can be insufficient for AI roles.
A candidate may list:
Python
Machine learning
Generative AI
LLMs
Cloud
TensorFlow
OpenAI
Data Science
But keywords alone do not establish how effectively that person has applied those skills.
Employers need to understand what the candidate actually built, implemented, managed or improved.
For example:
Instead of asking:
Do you have experience with generative AI?
Ask:
Tell us about a generative AI solution you implemented. What business problem did it address, what technology did you use, and how did you measure the result?
The second question provides a much better opportunity to assess practical capability.
How to Assess AI Skills During an Interview
A strong AI recruitment process should combine technical assessment, practical experience and business understanding.
1. Ask About Real AI Projects
Ask candidates to explain a project they have personally worked on.
Explore:
The business problem
Their specific contribution
Technologies used
Data involved
Implementation challenges
Security or governance considerations
Business outcome
Lessons learned
The goal is not simply to determine whether the candidate has used AI.
It is to understand how they used it and what they achieved with it.
2. Test Practical Problem-Solving
Use a realistic business scenario relevant to the position.
For example:
Your company wants to introduce an AI-powered customer service solution. How would you approach the project?
A strong assessment can explore how the candidate thinks about:
Data
Technology selection
Integration
Security
User adoption
Testing
AI output quality
Human oversight
Measurement
This can reveal more than a list of certifications.
3. Assess AI Tool Knowledge
The specific tools a candidate has used can be relevant, but tools should not become the entire assessment.
AI technologies change quickly.
A candidate who understands how to evaluate and adopt new tools may have a more transferable skill set than someone whose experience is limited to a specific platform.
4. Evaluate Critical Thinking
AI can produce inaccurate, incomplete or misleading outputs.
Candidates should therefore understand when AI should be trusted, when it should be verified and when it should not be used.
For relevant roles, interviewers can explore the candidate's understanding of:
AI limitations
Hallucinations
Data quality
Bias
Privacy
Security
Human oversight
Responsible AI use
5. Assess Communication
AI professionals increasingly work across technology, operations and business teams.
Technical capability therefore needs to be combined with the ability to explain complex concepts to non-technical stakeholders.
This is particularly important for AI managers, architects, product leaders and executives.
How to Assess AI Fluency in Leadership Candidates
AI leadership hiring requires a different approach.
A CTO, CIO, Chief AI Officer or Head of AI may not need to be the strongest technical specialist in the organization.
Instead, employers may need to assess whether the candidate can connect AI capabilities to business strategy.
Key areas to explore include:
AI Strategy
Can the candidate identify where AI can create meaningful business value?
Governance
Does the candidate understand the importance of data governance, security, privacy, risk management and responsible AI?
Transformation
Can the candidate move AI initiatives from experimentation and pilots toward practical implementation?
Leadership
Can they build, lead and retain multidisciplinary AI teams?
Commercial Thinking
Can they explain how AI investment can support measurable business outcomes?
Change Management
Can they help employees and business leaders adopt AI effectively?
These capabilities can be particularly important when recruiting senior technology and digital transformation leaders.
The AI Skills Employers Should Look For in 2026
AI hiring is becoming broader than simply looking for machine learning experience.
Depending on the position, employers may need a combination of technical and human capabilities.
AI Capability | What Employers Should Assess |
Machine Learning | Model development, evaluation and deployment |
Generative AI | LLMs, prompting, applications and implementation |
Data Science | Analytics, modelling and data interpretation |
AI Architecture | Enterprise integration and scalability |
MLOps | Deployment, monitoring and operationalization |
AI Security | Security, privacy and risk |
AI Product Management | Business use cases, product development and adoption |
AI Governance | Policies, controls, risk and responsible AI |
AI Leadership | Strategy, transformation and team building |
AI Fluency | Practical understanding and effective AI use |
The exact combination should depend on the role rather than applying the same AI checklist to every candidate.
Why Human Skills Still Matter in AI Hiring
The growth of AI does not eliminate the importance of human capabilities.
In fact, current labour-market research points in the opposite direction.
PwC's 2026 AI Jobs Barometer found that AI-exposed roles are increasingly associated with skills such as judgement, creativity and leadership. Its analysis of US entry-level roles also found that AI-exposed positions were significantly more likely to require traditionally senior-level human skills.
The World Economic Forum similarly highlights learning agility, emotional intelligence and other human capabilities as important skills as AI changes the workplace.
For employers, this means the strongest AI hiring strategy is not necessarily:
AI skills OR human skills
It is:
AI capability + business understanding + human judgement.
How Companies Can Attract AI Talent
Finding AI talent is only one part of the challenge.
Employers also need to consider why highly skilled professionals would choose to join and remain with the organization.
A competitive AI talent strategy can include:
Access to Modern Technology
AI professionals are likely to consider the technology environment when evaluating opportunities.
Meaningful Projects
Candidates may be attracted to opportunities where they can solve substantial business or technical problems rather than simply maintain existing systems.
Continuous Learning
AI is evolving rapidly. Learning opportunities can therefore become an important part of the employee proposition.
Career Development
Clear progression can help organizations develop and retain scarce technical and leadership capabilities.
Leadership Support
AI teams need organizational support to experiment, implement and scale appropriate solutions.
A Clear AI Strategy
Candidates may want to understand how AI fits into the company's broader business strategy.
This does not mean every company needs to become an AI-first organization. It means employers should be able to explain how technology and talent fit into their future direction.
Building an AI-Ready Workforce: Hire, Upskill and Integrate
Recruiting external AI specialists is only one part of building an AI-ready workforce.
A sustainable strategy can combine three approaches:
1. Hire
Bring in specialist AI capabilities where internal expertise is limited.
2. Upskill
Develop AI fluency among existing employees and managers.
3. Integrate
Embed AI capabilities into relevant business processes, technology environments and teams.
The World Economic Forum's 2026 work on AI and the workforce also highlights the importance of redesigning work, strengthening talent pipelines and aligning education and workforce development as AI changes early-career pathways.
For many employers, the future workforce will therefore include a combination of dedicated AI specialists and professionals in traditional functions who can work effectively with AI.
AI Talent Hiring in the UAE
The UAE is becoming an increasingly important market for AI talent.
PwC's 2026 UAE AI Jobs Barometer describes the country as one of the world's fastest-growing AI talent markets. AI-related job postings increased from 1.0% of UAE postings in 2021 to 3.2% in 2025, while demand has expanded across multiple industries.
For UAE employers, this creates opportunities as well as recruitment challenges.
Companies competing for AI professionals may need access to both local and international talent pools, particularly for highly specialized positions.
This is where a broader workforce strategy becomes important.
Rather than treating AI recruitment as a standalone hiring exercise, employers can consider:
Executive search for AI leadership
Contract AI specialists
Workforce solutions for technology teams
How a Specialist Recruitment Partner Can Help
AI recruitment requires more than finding candidates who mention AI on their CV.
A specialist recruitment partner can help employers define the role, identify the required skill set, source relevant candidates and assess experience against the actual requirements of the position.
At Leira Consulting, we support organizations with technology and workforce requirements across the UAE, GCC and international markets.
Our technology recruitment capabilities cover areas including:
Artificial Intelligence & Machine Learning
Generative AI
Data & Analytics
Cloud & Infrastructure
Cybersecurity
Software Engineering
Digital Transformation
IT Leadership
We also support organizations through Permanent Hiring, Executive Search, Contract Staffing, RPO, EOR and global workforce solutions, depending on their hiring requirements.
The Future of AI Hiring Is Skills-Based
AI is changing the skills employers need, but it is also changing how those skills should be assessed.
A strong AI candidate is not defined only by the technologies listed on a CV.
Employers increasingly need to understand:
What can the candidate actually do?
How have they applied AI in real situations?
Can they adapt as the technology changes?
Can they combine AI capability with sound judgement?
Can they create business value from AI?
For leadership roles, the questions become even broader: Can the candidate guide AI adoption responsibly, build the right teams and connect technology investment to business strategy?
As AI becomes more deeply embedded across industries, organizations that build structured, skills-based approaches to AI hiring will be better positioned to identify the capabilities they actually need.
Looking to Hire AI Talent?
Leira Consulting helps companies identify and recruit technology and AI professionals across the UAE, GCC and international markets.
Whether you are hiring an AI engineer, data scientist, technology leader or building an entire AI-focused team, our recruitment specialists can help you identify the right talent for your requirements.
Talk to Leira Consulting about your next AI hiring requirement.
