How AI can reshape Saudi’s workforce: Deloitte’s Gautam Motwani on what comes next
Saudi Arabia’s transformation is intensifying demand for specialised skills while companies work to meet Saudisation goals. Deloitte’s Gautam Motwani explains how AI is reshaping HR and workforce planning, and why human judgement remains critical
09 September, 2026
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Saudi Arabia’s Vision 2030 is ambitious: diversify the economy, build new industries, drive technological advancement. Getting there means one thing: a growing pool of specialised talent, deployed strategically, with Saudisation targets met.
But here’s the challenge. It’s not just about headcount. It’s finding the right skills at the right time, as new industries and technologies rapidly reshape the roles companies need to fill.
That’s where artificial intelligence (AI) comes in, not to replace HR, but to transform how it works. AI isn’t simply automating forms and approvals. It’s shifting HR’s focus from administration to strategy, workforce planning, skills development, and organisational design.
“AI is moving HR from a service and process function towards an orchestrator of work, skills and workforce decisions,” explains Gautam Motwani, partner – HR Strategy & Technology at Deloitte Middle East. “While today’s gains are mostly in productivity and efficiency, administration, employee queries, recruitment support and faster transactions, the longer-term gains are often seen in building flatter, leaner, cross-functional and horizontally integrated organisations.”
For Saudi Arabia specifically, this shift carries real weight. The kingdom’s biggest projects need significant volumes of skilled talent. Companies simultaneously must meet nationalisation targets, which means developing Saudi talent at speed while maintaining competitive capability.
“The question is not only about the quantity of Saudi talent, but also: which skills do we need to build in Saudi talent, by when, and how do we accelerate that journey?” Motwani asks.
This is where AI’s potential becomes clear. AI can broaden that approach by helping organisations understand the capabilities they already have and the skills they will need in the future. It maps current capabilities across an organisation, forecasts future skill needs based on strategic direction, and matches people to opportunities based on skills rather than title or degree.
But mapping and matching are just the beginning. AI can also identify which employees are candidates for reskilling — people whose current roles may not align with where the business is heading, but whose underlying capabilities could translate to critical future needs. Where specialised talent is in demand, developing existing employees can complement external recruitment and help companies address emerging skills requirements.
Motwani connects this directly to Saudi Arabia’s initiatives. “AI can be a significant enabler in building our national workforce’s capability to be future-ready,” he notes. “Deloitte links this shift to national programmes such as Saudi Arabia’s Human Capability Development Program and to Deloitte’s own Kiyadat initiative.”
Both initiatives place an emphasis on developing human capabilities and preparing talent for changing workforce requirements.
The skills problem isn’t really about numbers
With giga-projects and new industries competing fiercely for talent, HR leaders often frame the challenge in terms of availability: we can’t find enough people. But the real constraint, according to Motwani, is more subtle.
“The biggest shortage is not necessarily people; it is specialised capability,” he says. “Because those capabilities are changing so quickly, recruitment alone will never solve the problem.”
This matters because it reframes the entire HR strategy. If the constraint is specialised capability rather than simply headcount, recruitment alone may not be enough. Skills mapping, capability building, reskilling and internal talent mobility become increasingly important.
“AI helps by predicting future skills demand, building a skills inventory, spotting reskilling candidates and dynamically matching people to work,” Motwani explains.
In practical terms, that means an organisation can use AI to look at its current workforce, understand what capabilities exist today, forecast future requirements based on its strategic priorities, and identify which current employees could be developed into those roles. It’s capability planning rather than just recruitment.
For Saudisation specifically, this could change how companies approach workforce planning. Instead of asking “how many Saudis do we need to hire,” companies can ask “which Saudi talent currently in our organisation can we develop into strategic roles, and how quickly can we do that?”
The bias and accountability question
As AI becomes more embedded in hiring decisions, performance management and workforce planning, a critical question emerges: how do organisations prevent bias and ensure decisions remain fair?
AI systems trained on historical data can reproduce or amplify biases contained in that data. A system trained on historically biased recruitment or promotion decisions, for example, could reproduce some of those patterns unless appropriate safeguards, testing and oversight are put in place.
But Motwani argues the solution isn’t to ban AI from workforce decisions. It’s to use AI with explicit guardrails.
“AI can inform a business decision, but accountability for consequential decisions cannot be ignored,” he says. Deloitte’s approach centres on what it calls the Trustworthy AI framework, built to ensure AI systems are “fair and impartial, transparent and explainable, respectful of privacy, safe and secure, robust and reliable, and responsible and accountable.”
The key principle: “The objective should not be to remove humans from the loop. In high-impact workforce decisions, it should be AI-supported human judgement, with transparency, testing and clear accountability.”
For Saudisation specifically, this could change how companies approach workforce planning. Instead of asking “how many Saudis do we need to hire,” companies can ask “which Saudi talent currently in our organisation can we develop into strategic roles, and how quickly can we do that?”
Data privacy: The infrastructure question
But there’s a layer most companies aren’t thinking about: HR holds some of the most sensitive data in the organisation. When you’re adding AI to the mix, that becomes a real problem. Employee data includes compensation, performance history, health information, family status, and increasingly, information about how people work and interact. Before companies start rolling out AI systems with access to that data, they need to think hard about what they’re actually enabling.
“HR holds some of the most sensitive information in an organisation,” Motwani says. “AI access should follow a need-to-know principle, not an ‘AI can access everything’ principle.”
This isn’t just about security, though that matters. Saudi Arabia’s Personal Data Protection Law (PDPL) regulates the processing of personal data and includes requirements covering areas such as cross-border data transfers, retention and individuals’ rights in relation to their personal data.
“Data governance must come before scale,” Motwani says. “It must be built to align with applicable personal data protection laws and regulations, such as Saudi Arabia’s Personal Data Protection Law (PDPL), covering lawful processing, cross-border transfer requirements, data retention and individuals’ rights in relation to their personal data.”
Companies that scale AI without appropriate data governance could expose themselves to greater privacy, compliance and regulatory risks. Establishing governance early can provide a stronger foundation for responsible AI adoption.
The future HR function
Over the next three to five years, Motwani expects the HR function to undergo significant change.
“The future HR function will probably have fewer people administering HR and many more people shaping work, skills, leadership and the human-AI relationship,” Motwani predicts. “Expect a fundamental redesign of HR, not incremental automation; agentic AI is increasingly capable of executing complete workflows end-to-end.”
If that transformation unfolds as Motwani expects, HR teams could devote fewer resources to routine administration and transactions while placing greater emphasis on strategy, capability building, organisational design and managing AI-integrated work.
It also means HR leaders themselves may need to evolve. Process management could increasingly give way to workforce strategy, while recruitment expertise will need to be complemented by a greater focus on reskilling, capability development and managing how people and AI work together.
But Motwani sees HR leaders not just as subjects of transformation, but as drivers of it.
“It’s important to highlight that HR also has a role in helping transform the wider organisation for AI, not just being transformed by it. We expect HR leaders will drive this transformation from the front.”
In other words, HR isn’t just adapting to AI. It could play a central role in helping the wider organisation adapt, from managing change and developing new skills to determining how people and AI work together.
For Saudi Arabia, where economic diversification and workforce development are progressing in parallel, that could make HR an increasingly important part of delivering the kingdom’s broader transformation ambitions.
