Vishu Singhal, Data & Consulting Partner at Artefact, explains how trusted data, responsible AI and strong governance are enabling governments across the GCC to deliver measurable economic impact, resilient public services and long-term competitiveness.
Artificial intelligence and data have become central to the GCC’s long-term economic transformation, enabling governments to strengthen competitiveness, accelerate digital innovation and deliver more responsive public services. Across the region, the focus has shifted from developing AI strategies to executing large-scale programmes built on trusted data, robust governance and measurable outcomes.
In this interview, Vishu Singhal, Data & Consulting Partner at Artefact, shares his insights on how governments are turning ambitious digital agendas into tangible economic and policy impact. Drawing on his experience advising sovereign wealth funds, ministries, prime minister offices and giga projects, he explains why strong data foundations, responsible AI governance, citizen-centric digital services and investment in talent are critical to building resilient, future-ready public institutions.
Interview Excerpts
How are governments across the GCC embedding data and AI into national strategies to drive economic resilience and long-term competitiveness?
Governments across the GCC have moved beyond defining AI strategies and are now focused on large-scale execution. Significant investments across the UAE, Saudi Arabia and Qatar demonstrate that AI is no longer viewed solely as a technology initiative but as a national economic priority that supports diversification, productivity and global competitiveness.
One of the most important lessons emerging from these programmes is that AI success depends on strong data foundations. Establishing a unified data platform or a trusted single source of truth enables AI applications to scale across government entities and deliver long-term value.
Another defining trend is the growing emphasis on sovereign digital infrastructure. Investments in sovereign cloud, domestic data centres and national AI ecosystems reflect a broader objective of ensuring that critical data, computing capacity and AI capabilities remain securely within national borders while supporting economic resilience.
In large-scale public sector transformations, how do you translate complex data initiatives into measurable economic impact and policy outcomes?
Successful transformation programmes begin by linking every initiative to clearly defined policy objectives and measurable outcomes. Whether the focus is improving operational efficiency, strengthening public services or enhancing resource allocation, each use case should demonstrate tangible value from the outset.
Transparency is equally important. AI systems used in the public sector must be explainable, auditable and capable of producing outcomes that regulators and policymakers can confidently defend. Equally critical is investment in the underlying data foundation.
Strong governance, data quality, lineage and compliance often determine whether an AI programme succeeds.
Delivering measurable outcomes through phased milestones over six to twelve months also helps maintain momentum while ensuring programmes remain aligned with evolving policy priorities.
What role do advanced analytics and AI play in strengthening decision-making and business continuity within sovereign entities and giga projects?
Advanced analytics and AI are transforming decision-making from retrospective reporting to predictive intelligence. Rather than simply understanding what has happened, organisations can now anticipate emerging risks, identify potential disruptions and make proactive decisions before issues escalate.
Unified data platforms also reduce reliance on fragmented systems and institutional knowledge by bringing operational, financial and risk data together into a single trusted environment. This enables more consistent and informed decision-making across complex organisations.
AI also strengthens business continuity through rapid scenario modelling. Leaders can evaluate multiple economic, operational or geopolitical scenarios in real time, allowing them to respond faster and make more resilient decisions in an increasingly uncertain environment.
How are emerging technologies such as generative AI and data platforms reshaping governance models and citizen-centric digital services?
Generative AI is transforming citizen services by enabling more personalised, multilingual and context-aware interactions across government platforms. Citizens increasingly expect digital services that are intuitive, responsive and capable of addressing their needs without navigating multiple agencies.
Delivering this experience depends on integrated data platforms that connect information across government entities and create a unified view of citizens and services. This enables AI-powered automation of processes such as case management, eligibility assessment, document processing and approvals.
Governments are increasingly using real-time data to improve policy outcomes rather than simply measuring compliance.
Built-in governance, explainability, privacy and regulatory compliance have also become essential requirements, ensuring innovation is delivered responsibly while maintaining public trust.
What organisational and talent shifts are critical for building a data-driven culture that balances innovation with trust, security and long-term sustainability?
Building a sustainable data-driven organisation requires more than technology investment. Developing skilled talent that combines expertise in data, AI, regulation and domain knowledge has become one of the most important success factors across the region.
Organisations are also recognising data as a strategic enterprise asset. Clear ownership, executive accountability and dedicated data governance functions create the structure needed to support scalable AI adoption while maintaining consistent standards across departments.
Innovation must be balanced with strong governance from the beginning. Embedding privacy, security, explainability and compliance into every initiative enables organisations to innovate confidently while managing risk. Equally important is adopting long-term operating models built around product teams, continuous capability development and executive sponsorship, ensuring AI programmes continue to evolve well beyond their initial deployment.
Source: Tahawul Tech