Rahat Khan

5 Ways Project Managers Can Lead in Saudi Arabia’s Year of AI

5 Ways Project Managers Can Lead in Saudi Arabia’s Year of AI Artificial Intelligence (AI) is no longer a side experiment. In 2026, the Saudi Cabinet declared the Kingdom’s Year of Artificial Intelligence, placing AI at the heart of Vision 2030, Saudi Arabia’s national transformation program. For project managers (PMs), that shift raises an urgent question: as AI changes how work gets delivered, will you lead the change or simply react to it? The pressure is real, and the numbers show why. According to Gartner, by 2030 around 80% of routine project management tasks, such as data collection, tracking, and reporting, will be handled by AI. But automation is not the same as replacement. In a 2025 Gartner survey of more than 700 chief information officers (CIOs), leaders expected that by 2030, 75% of technology work will be done by people working alongside AI, and only 25% by AI on its own. The message for PMs is clear. AI will take on more of the busywork, but leading the outcome stays firmly human. Here are five practical ways to step into that role. 1. Start with the data, not the tool The most useful mindset shift is simple: AI projects are not software projects, they are data projects. The Project Management Institute (PMI) has made this point for years, and teams learn it the hard way when a promising model fails because the data feeding it was messy or incomplete. Before choosing a tool, get clear on what data you have, what shape it is in, and whether it can actually support the outcome you want. 2. Close the gap between the demo and the deployment Most AI initiatives don’t fail because the model was weak. They stall in the gap between an impressive demo and a working deployment, where scope drifts, data isn’t ready, and stakeholders never quite align. That gap is exactly where good project managers earn their keep, by turning a promising prototype into something that ships and holds up in the real world. 3. Scope every initiative around a measurable outcome AI is easy to get excited about and easy to waste money on. The fix is discipline: tie every initiative to a clear, measurable business outcome before the build begins. This is where a strong Project Management Office (PMO), the team that sets delivery standards across an organization, adds real value, by keeping projects honest about the results they promised. 4. Double down on the skills AI can’t replace Here is what surprises people: the difference between a PM getting a little value from AI and one getting enormous value is rarely the tool. It’s communication, critical thinking, collaboration, and creativity. As routine tasks get automated, these human skills become the real differentiator, because AI rewards the leaders who ask sharper questions and frame better problems. 5. Stay accountable for what ships When AI drafts the plan or flags the risk, someone still has to own the decision. Keeping a human clearly accountable isn’t a brake on speed, it’s what lets you ship with confidence and keep the trust of clients and stakeholders. The best PMs treat accountability as part of good delivery, not paperwork added at the end. The bottom line The Year of AI won’t be won by the teams that adopt the most tools. It will be won by the people who can turn AI into real, delivered results, on time and on outcome. This is exactly where SOLGulf’s Agentic AI Delivery & Operations practice helps: we move organizations from AI readiness to production, bringing the delivery discipline that makes results stick. If you’re ready to turn AI ambition into working outcomes, reach out to the SOLGulf team, and we’ll show you what it looks like in practice. About the Author Syed Tufail Ahmed,AI & Digital Program Manager, SOLGulf Syed Tufail Ahmed is an AI governance strategist and program leader with around 25 years of enterprise experience across digital banking, healthcare analytics, and technology. At SOLGulf, he serves as AI & Digital Program Manager and heads the Project Management Centre of Excellence (PMCoE) for a Saudi government client, leading the delivery of AI and digital transformation initiatives. He is the author of Human in the Loop: Reclaiming Human Authority in an Age of Intelligent Systems (2026) and a Global Ambassador for the Global Council for Responsible AI (GCRAI). His work centers on helping organizations adopt AI in ways that scale human judgment rather than replace it. He has been recognized by Thinkers360 among the top global voices in AI governance, ethics, and safety, and holds a Certified Expert credential in AI Governance. Syed writes and speaks regularly on responsible AI, project delivery, and the evolving role of the project manager. He holds a Bachelor of Engineering in Instrumentation and Electronics and is based in Riyadh, Saudi Arabia. Connect with him on LinkedIn: linkedin.com/in/tufailsa

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Cloud Migrations: A Roadmap for Success

Why Digital Transformation Fails—And How to Avoid It Despite massive investment in digital transformation, many organizations still fail to see measurable results. According to McKinsey, over 70% of transformation initiatives fall short. The reasons are rarely technical—they’re strategic and organizational. This post outlines why transformations stall and how to avoid those pitfalls using a structured, people-centered approach. Common Pitfalls in Digital Transformation Lack of Strategic Alignment Without clearly defined goals and KPIs, teams focus on tools rather than outcomes. Insufficient Leadership Commitment Transformation is a cultural change. It must be visibly supported from the top down. Departmental Silos Disconnected business and IT teams lead to fragmented efforts and redundant systems. Neglecting Change Management Tools are only effective if people know how and why to use them. Adoption requires enablement. Legacy System Constraints Overlaying modern solutions onto outdated infrastructure creates bottlenecks and fragility. A Strategic Framework for Success Start with Business Outcomes Define success up front. What should change? How will it be measured? Design for the End User Solutions must align with how people work—not just how systems function. Break Down Silos Early Involve stakeholders from business, IT, and operations to co-create the solution. Enable Continuous Change Support doesn’t stop at go-live. Ongoing feedback and iteration are critical. Build for Long-Term Agility Today’s needs shouldn’t limit tomorrow’s growth. Design scalable, adaptable systems. A Real-World Example: Enabling Scalable Digital Maturity A large logistics provider approached SOL Systems after a failed ERP rollout. Despite the platform’s power, poor adoption stemmed from unclear goals, untrained staff, and outdated processes. SOL Systems reoriented the initiative by running executive workshops, redesigning key workflows, and launching phased rollouts supported by hands-on training. Within six months, the company saw a 40% drop in operational delays and a marked increase in user satisfaction. Impact at Scale: Ministry of Culture SOL Systems deployed its IT Service Hub at the Ministry of Culture to consolidate ITSM operations across more than 100 projects. The result: SLA compliance 0 % reduction in high-priority incidents 0 % reduction in security vulnerabilities 0 % Success came not from a flashy platform, but from aligning people, governance, and process under a shared strategy. Final Takeaway Digital transformation is not a tech challenge—it’s a business evolution. Organizations that lead with strategy, design for people, and support change over time achieve results that scale.

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