This article first appeared in Digital Edge, The Edge Malaysia Weekly on October 12, 2026 - October 18, 2026

Human resources (HR) launches an artificial intelligence (AI) tool to analyse employee engagement. The AI reads 15,000 comments and produces three recommendations: “Reduce unnecessary meetings, slash unnecessary approvals and cut unnecessary surveys.”

HR is shocked. “But how can we understand employee needs and sentiment without surveys?”

The AI replies: “Exactly 98.9% of employees voted for fewer surveys.”

HR schedules a workshop to discuss the findings. The AI emails the CEO and suggests cancelling it. The CEO agrees with the AI.

HR had said AI would free it from routine administration. AI now says the same thing about HR.

If that corny corporate anecdote made you laugh, digest this: according to a report by the World Economic Forum (WEF), AI and related technological changes will displace 92 million job positions by 2030. But it may create 170 million new roles as well, resulting in a net increase of 78 million jobs. The WEF says about 40% of all jobs are now exposed to AI, a figure that jumps to 60% in advanced economies.

As for Malaysia, it is nearing the peak of its demographic dividend with the share of the working age population set to decline after 2030. According to the Department of Statistics Malaysia, the working-age cohort (ages 15 to 64) is likely to max out at 70.8% of the total population in 2030 before steadily contracting.

The demographic window of opportunity — defined by having a highly productive workforce relative to fewer dependants — is rapidly closing as well. Bank Negara Malaysia warns that the total dependency ratio will bottom out around 2034. Beyond this pivot point, the number of elderly dependants will rise faster than the working-age population can replenish them.

AI might exacerbate the problem. According to a World Bank analysis published in May, skills-related underemployment is a symptom of the challenges faced in the labour market.

“While unemployment remains low and labour force participation is historically high in Malaysia, many workers — particularly tertiary graduates — are employed in jobs below their qualification level,” the study notes. “This points to persistent skills mismatches and limited absorption of high-skilled talent. Skill-related underemployment has a significant impact on wages. Tertiary graduates who are underemployed face a wage penalty of 49.3%.”

Which jobs should you bet on?

“Tech-related roles are the fastest growing jobs in percentage terms, including big data specialists, fintech engineers, AI/machine learning (ML) specialists and software and application developers,” says the WEF Future of Jobs Report 2025. “Green and energy transition roles, including autonomous and electric vehicle specialists, environmental engineers and renewable energy engineers are also in the top fastest-growing roles.”

The Future of Jobs report polled 1,000 organisations representing 14 million workers across 22 industry clusters and 55 economies. Two demographic shifts seem to stand out: ageing and declining working age populations in higher-income economies — and expanding working age populations in lower-income ones.

“Ageing populations drive growth in healthcare jobs such as nursing professionals, while growing working-age populations fuel growth in education-related professions such as higher education teachers,” the WEF reports.

Will AI render most human skills obsolete? No. But it will transform how we apply them. In fact, more than 70% of today’s skills remain valuable across both automated and manual tasks.

“With AI handling more common tasks, people will apply their skills in new contexts,” McKinsey says. “Workers will spend less time preparing documents and doing basic research, for example, and more time framing questions and interpreting results. Employers will increasingly prize skills that add value to AI.”

To figure out how our jobs might change, McKinsey created the Skill Change Index (SCI) to track how automation impacts different workplace skills. Here is the breakdown: technical skills like accounting and coding may see the biggest shake-up. People skills like negotiation and coaching will be the most secure. Most other everyday skills, like problem-solving and communication, will simply evolve as we learn to work side by side with AI agents and robots.

Everything seems fine — until you look at the numbers. McKinsey Global Institute reveals a massive shift ahead: AI-driven agents and robots are set to inject roughly US$2.9 trillion (RM11.8 trillion) annually into the US economy by 2030.

“Capturing this may depend less on new technological breakthroughs than on how organisations redesign workflows — especially complex, high-value ones that rely on unstructured data — and how quickly human skills adapt,” McKinsey notes. “Integrating AI will not be a simple tech rollout but a reimagining of work itself — redesigning processes, roles, skills, culture, metrics. People, agents, robots could create more value together.”

It is not just corporations embracing AI agents — public institutions worldwide are keen to adopt them too. Gartner says more than 80% of government agencies plan to roll out AI agents by 2028. These autonomous tools will be tasked with handling everyday administrative decisions, driving organisational efficiency and delivering better services to citizens.

“Government CIOs (chief information officers) are under growing pressure to embed AI into decision-making capabilities rapidly and responsibly,” says Daniel Nieto, a Gartner director. “The rise of multimodal AI, alongside conversational and agentic systems, has expanded what public organisations can automate, understand and anticipate.”

What is holding back the realisation of AI value? Fragmentation. In Gartner’s global survey of 138 government officials, 41% identified siloed strategies and 31% pointed to legacy systems as major obstacles to digital implementation. As AI shifts from an experimental tool to a core component of decision-making, governance frameworks must mature beyond simply managing models, data and algorithms.

A likely solution?

“Decision intelligence (DI) could shift this focus towards the governance of decisions themselves,” Gartner says. “For example, on how they are designed, executed, monitored and audited. This shift in governance is especially critical in government, where public legitimacy relies on transparency and fairness.”

Another moot point? Govern decisions, not just isolated AI components.

“Governing decisions can help governments better balance automation with human judgement, particularly in high-stakes or rights-impacting contexts,” Nieto says. “Regulated industries and governments cannot rely on opaque black box systems for consequential decisions. DI elevates explainability from a technical requirement to a governance imperative.”

Do you really need a massive toolkit of skills to win in the AI era? Maybe not. As it turns out, the real rewards are heavily concentrated. A report by PwC reveals that 75% of all financial gains from AI are being captured by a mere 20% of businesses. The secret? These top performers aren’t just using AI to speed up old tasks — they are pointing the tech directly at growth and business model innovation.

“Many companies are busy rolling out AI pilots, but only a minority are converting that activity into measurable financial returns,” says Joe Atkinson, PwC’s chief AI officer. “The leaders stand out because they point AI at growth, not just cost reduction. They back it up with the foundations that make AI scaleable and reliable.”

The bottom line: AI is here. Which skills matter more now? Here is my set of seven — in alphabetical order — for you to consider cultivating to get and retain a job in the AI era:

Adaptability: Develop the capacity to continuously learn, pivot and master new workflows as technology shifts. This demands fluency with AI tools, a high tolerance for ambiguity and agility to upskill rapidly in the face of ongoing disruption.

Business: Get a strong grasp of how your organisation generates value, rather than just how individual tasks are completed. Take time to understand business models, financials and customer needs so you can leverage AI for strategic growth and smarter decision-making, not simply basic automation.

Collaboration: Learn to work seamlessly across combined human and AI workflows. This requires communication, trust-building and knowing when to defer to human judgement versus machine intelligence. Use AI as a collaborative teammate rather than a standalone tool.

Domain: Specialised, deep expertise in a specific sectors like healthcare, finance or engineering is of immense value. That’s because AI exponentially increases the worth of subject-matter expertise, as domain experts are uniquely qualified to write better prompts, critique machine outputs and apply insights ethically.

Engagement: Hone your inner drive to remain curious, resilient and purpose-led during rapid tech changes. Focus on emotional intelligence and authentic human connection with colleagues and clients — core strengths where humans will always outpace technology.

Focus: Build discipline of cognitive attention in an information-heavy world. This means cutting through data noise, prioritising high-value objectives and allocating time for deep analytical thinking while AI manages the administrative heavy lifting.

Government: Be aware of laws, ethics, compliance and public policy related to AI. This includes data privacy, AI governance, risk management and responsible use — critical for trust and leadership roles.

Since we started with a corny corporate joke, let’s end with another: the leadership team asks the smartest AI system to identify top talent in the organisation. After a week of intense analysis of output across the company, the algorithm spits out the results: “Found one talent with zero complaints, 99% uptime, supports all departments without questioning and has never requested a salary increase.”

The leadership team is amazed and votes to promote this hyper-efficient employee. “Please identify the name and location of this talented asset,” the CEO prompts the AI.

The AI replies: “The highest-performing asset is laser printer #13 on the third floor in HQ.”

Raju Chellam is a former editor of Dataquest currently based in Singapore, where he is editor-in-chief of the AI Ethics & Governance Body of Knowledge, and chair of Cloud & Data Standards

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