Maryam Alrajei, Marketing Manager, Code DXB
Organisations can turn AI hype into everyday workplace habits by moving from general awareness to structured, repeatable use of AI in real workflows. This requires practical training, human oversight and clear business objectives.
For HR, talent, L&D and technology leaders, the challenge is no longer simply explaining what is AI. It is making AI useful, responsible and repeatable within the organisation.
AI has quickly moved from an emerging technology topic to a strategic workforce issue. Organisations are evaluating AI tools, redesigning workflows and considering how artificial intelligence could affect productivity, skills and the future of work. This is particularly relevant as artificial intelligence in UAE organisations becomes increasingly connected to digital transformation, workforce development and business innovation.
However, access to AI does not automatically create AI capability.
Why Is There a Gap Between AI Hype and AI Habits?
The gap exists because awareness and application are different capabilities.
A leader may understand the potential of generative AI and have an AI strategy under development, but that does not necessarily mean employees know how to incorporate AI into everyday work.
Practical adoption requires employees to understand the task, identify where AI can assist, provide relevant context, assess the output and decide what should happen next.
A useful working principle is:
Ask → Review → Check → Improve → Decide
AI can accelerate parts of a workflow, but people remain responsible for judgement and final decisions.
This is particularly important because AI-generated information can appear convincing even when it requires further verification. Employees therefore need to know how to question outputs, check important information and recognise when AI should or should not be used.
AI capability should consequently be measured by how effectively people use AI at work, not simply by tool access or attendance at an introductory training session.
What Does Practical AI Adoption Look Like?
Practical AI adoption starts with existing workflows rather than technology for its own sake.
An HR team might use AI to support research, organise information or create an initial draft. An L&D team could explore AI for learning-content development. A technology team might apply AI to coding, testing or documentation.
The important question is not which tool employees use. It is how AI improves a real workflow.
A practical process is:
Identify a real task. Start with work employees already understand.
Find where AI can assist. Identify a specific step where AI could reduce repetitive work or improve an initial output.
Review the result. Check accuracy, relevance and suitability.
Refine the workflow. Improve the instructions, context or process.
Decide whether to scale. Turn successful experiments into repeatable practices.
This is more effective than encouraging employees to experiment with AI without a clear business purpose.
Microsoft and LinkedIn's 2024 Work Trend Index, based on 31,000 people across 31 countries, found that 75% of knowledge workers were using AI at work. The research also highlighted the emergence of AI power users who are more likely to rethink business processes, receive leadership encouragement and receive role-specific training.
The lesson is clear: AI habits develop when employees receive practical guidance and opportunities to redesign workflows.
What AI Skills Do Organisations Need?
Organisations do not need every employee to become an AI specialist. They need people who can use AI with appropriate judgement.
Core capabilities include:
Identifying suitable AI use cases
Providing effective instructions and context
Evaluating AI-generated output
Verifying important information
Recognising when human judgement is essential
Using AI responsibly within organisational guidelines
The World Economic Forum's Future of Jobs Report 2025 identifies AI and big data among the fastest-growing skills through 2030, alongside capabilities such as creative thinking, resilience, flexibility and lifelong learning.
AI capability is therefore not simply about learning to operate a tool. It combines technological literacy with human skills such as analytical thinking, creativity, adaptability and judgement.
How Can HR and L&D Leaders Build AI Habits?
HR and L&D leaders can close the gap by connecting AI learning directly to the work employees perform.
Instead of asking only, "What is AI?", practical learning should ask:
"How can AI change the way we work?"
Teams can use real organisational workflows as learning exercises, test AI against familiar tasks and discuss where the technology succeeds or fails.
Responsible use should also be part of the learning process. An AI-generated result is not automatically a finished result. Employees still need to review information, check important claims and apply professional judgement.
This is increasingly important as workforce skills evolve. The World Economic Forum estimates that 39% of workers' existing skill sets are expected to be transformed or become outdated between 2025 and 2030.
For corporate academies and L&D teams, the objective should therefore be to build repeatable capability, not simply increase AI awareness.
How Should Organisations Measure AI Adoption?
AI adoption should be measured through behaviour and business relevance rather than participation alone.
Organisations should ask:
Are employees using AI in real workflows?
Which tasks are producing meaningful improvements?
Are employees recognising unsuitable AI use cases?
Are outputs being consistently reviewed?
Which AI practices are becoming repeatable?
Where is additional training required?
Organisations can also measure whether AI is helping teams save time, reduce repetitive work, improve initial outputs or support better decision-making.
The goal is not to create the appearance of AI adoption. It is to create useful, sustainable capability.
Why Does AI Strategy Need Workforce and Training Leaders?
AI implementation is often treated as a technology decision, but successful adoption depends heavily on people.
CIOs and CTOs may lead technology evaluation and deployment. CHROs, HR directors, talent leaders and L&D teams have an equally important role in understanding how work, skills and behaviours need to change.
That makes collaboration between technology, HR, talent and learning leaders essential.
The conversation should therefore move beyond which AI tools are available and focus on how AI changes workflows, what skills employees need, how training should evolve and where human judgement remains critical.
From AI Awareness to AI Capability
Organisations should stop treating AI adoption as a single technology project.
A more sustainable progression is:
Awareness → Experimentation → Practical Use → Repeatable Habits → Organisational Capability
The transition happens when employees repeatedly use AI in appropriate situations and understand how to evaluate its output.
For senior leaders, the workforce question is therefore central to AI strategy. Organisations seeking value from AI need to consider technology alongside skills, training, workflow redesign, governance and human decision-making.
Where Can Workforce and Training Leaders Explore This in Practice?
These questions sit at the centre of Workforce Live and Training Live in Dubai.
Be part of CODE DXB and experience two powerful live tracks shaping the future of work and learning. Join us on 1–2 April 2027, from 9:00 AM to 6:00 PM at The Agenda, Dubai Media City.
Explore how AI is reshaping the workforce, transforming corporate training, and bringing bold ideas to life through interactive experiences and live sessions on stage.
For HR, talent, L&D and technology leaders, the opportunity is to engage with the practical questions behind AI adoption: what changes in the workforce, what skills need to be developed, how training should evolve and what responsible AI use looks like inside a real organisation.
The challenge is no longer whether employees will encounter AI at work. It is whether organisations can turn that usage into safe, productive and repeatable habits.
The real opportunity is not adding more AI hype to the workplace. It is building the skills, workflows and organisational behaviours that make AI genuinely useful every day.
FAQs
What is the difference between AI awareness and AI capability?
AI awareness means understanding what artificial intelligence can do. AI capability goes further by enabling people to apply AI to real work, evaluate its output and make appropriate decisions about its use.
How can organisations encourage employees to develop AI habits?
Start with real workflows rather than abstract AI training. Give teams opportunities to test AI against specific tasks, review the results and refine the process until useful practices become repeatable.
Do all employees need advanced AI skills?
No. The skills required depend on the role and the tasks involved. Organisations should focus on giving people the level of AI capability they need to use the technology appropriately within their work.
Why is human judgement still important when using AI?
AI can generate useful outputs but can also produce incorrect or incomplete information. People therefore need to review important outputs, apply professional judgement and remain accountable for decisions.
How should HR and L&D leaders approach AI training?
AI training should be connected to the organisation's actual workflows and priorities. The focus should be on developing practical capability, not simply increasing awareness of AI tools.
If your organisation is ready to move beyond AI experimentation and build AI capability that changes how your workforce actually works, be part of the conversation at CODE DXB 2027, featuring Workforce Live and Training Live. Join the leaders shaping the future, see AI in action, and take home ideas that make an impact.
Sources:
Microsoft and LinkedIn's 2024 Work Trend Index
World Economic Forum's Future of Jobs Report 2025
