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    Home»Technology»AI reshapes workforce planning across Middle East, says Workday official
    Technology

    AI reshapes workforce planning across Middle East, says Workday official

    Editorial teamBy Editorial teamSeptember 9, 2026
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    Zakaria Haltout, Group Vice President for the Middle East, Turkey and Africa, Workday.

    Workday highlights how connected data, agile operating models and responsible AI can help organisations build future-ready workforces

    AI is reshaping how Middle East organisations manage talent, develop skills and prepare for future workforce demands. With GCC adoption accelerating, businesses face growing pressure to move beyond isolated pilots and embed AI into core workflows to deliver measurable value.

    In an interview with CNME, Zakaria Haltout, Group Vice President for the Middle East, Turkey and Africa at Workday, discusses the importance of connected data, agile operating models and responsible governance in scaling AI-led transformation.

    Interview excerpts

    How is AI changing the way Middle East organisations manage people, skills and workforce planning?
    Across the Middle East, organisations are moving beyond using technology solely to automate administrative processes and are beginning to use AI to augment day-to-day work, strengthen skills development and help people contribute more strategically to growth and innovation. 

    When people, financial and operational data are brought together with AI-driven insights, organisations can better understand the skills they have, anticipate the capabilities they will need and make more informed workforce decisions at speed. This helps leaders move from reacting to talent gaps after they emerge to taking proactive action – whether that means developing skills internally, redeploying talent or planning for future demand. 

    What separates organisations that succeed in digital transformation from those that struggle to move beyond pilot projects?
    The organisations that succeed understand that transformation is not simply about access to new technology. Many organisations can launch an AI pilot. But the challenge is moving from experimentation to AI-powered execution. That requires a clear business case, trusted data, leadership commitment and an operating model that enables new capabilities to be adopted at scale. AI initiatives need to be connected to the workflows where work is actually done, not positioned as a separate experiment or another assistant layered on top of disconnected systems. 

    In the GCC, businesses are operating against some of the world’s most ambitious transformation agendas, and adoption is accelerating rapidly.

    GCC AI adoption has moved from 62% to 84% in two years. The next differentiator will be how effectively organisations turn that momentum into sustainable value. Those that do will combine advanced AI capabilities with the governance, transparency and control needed to move quickly and responsibly. 

    How can regional business leaders build operating models that are more agile, data-driven and future-ready?
    Agile operating models are built on the ability to make informed decisions at speed. That begins with connecting people, finance and operational data so leaders have a shared, trusted understanding of business performance, workforce capacity and the choices available to them. 

    When data is fragmented, organisations spend too much time reconciling information and responding to issues after the fact. When data is connected and paired with AI-driven insights, leaders can identify patterns earlier, model different scenarios and act with greater confidence. This supports a shift from reactive decision-making to proactive action, creating greater agility, resilience and business impact. 

    As work changes, organisations need the flexibility to understand emerging skills needs, develop internal talent and deploy people where they can create the greatest value. Equally important is building governance, accountability and data literacy that allow teams to use AI responsibly.  The result is an organisation that can respond faster to change while maintaining the control and confidence required to scale transformation. 

    What role can cloud-based platforms such as Workday play in supporting the Middle East’s AI and digital transformation ambitions?
    Workday provides the foundation for organisations to turn transformation ambitions into action at the pace the region demands. By bringing together trusted people, financial and operational data, Workday helps leaders make more informed decisions and act on them more quickly. 

    The future of enterprise AI is not about introducing another assistant into the workplace. It is about embedding AI directly into business processes, enabling organisations to automate work, streamline operations and make better decisions in real time. Workday helps customers move beyond isolated AI experimentation and into AI-powered execution, where technology is connected to enterprise data, guardrails and real-world workflows.  This is particularly relevant for organisations across the GCC, where the imperative is not only to innovate but to implement faster, accelerate adoption and realise value sooner.

    Workday can help customers create a more agile and resilient organisation by providing a unified platform for people, finance and operations, with AI-driven insights built into the flow of work. 

    What practical steps should organisations take now to prepare their workforce for the next phase of AI-led business change?
    First, organisations should establish a trusted view of their people, skills and work. They need to understand which activities can be automated or augmented, where skills gaps are emerging and how workforce needs are likely to change. This creates a practical basis for moving from broad AI ambition to focused action. 

    Second, leaders should identify where AI can be embedded into priority workflows to remove routine work, improve decision-making and create capacity for higher-value contribution. The most effective initiatives are anchored in tangible business outcomes, such as improving productivity, accelerating planning or strengthening the employee experience. 

    Third, organisations must invest in skills. Technical capability is important, but so are the human skills that help employees work effectively alongside AI: critical thinking, collaboration, creativity, judgement and adaptability. Learning must be continuous, relevant to the work people do and connected to the organisation’s strategic priorities. 

    Finally, organisations should put responsible AI principles into practice from the start. That means clear governance, transparency, appropriate controls and accountability for how AI is used. When innovation operates within trusted data, enterprise guardrails and real-world workflows, leaders can scale AI with greater confidence. 

    The organisations best prepared for the next phase of AI-led change will be those that treat AI as a catalyst for better work, better decisions and stronger business performance, not simply as a technology deployment. 


    Source: Tahawul Tech

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