Hadi Kobeissi, Partner – Digital & Technology Consulting at PwC Middle East, emphasizes a balanced approach to AI, combining innovation with responsibility, robust governance, and human-centric design, to help Middle East businesses move from hype to sustainable, scalable transformation.
Are Middle East businesses investing in the right AI systems — or are many still chasing the hype without a clear strategy or ROI?
In a space evolving as fast as AI, it’s hard to say what the “right” systems even are as they’re constantly changing. What really matters is not chasing the latest tool, but building the culture, skills, and agility to keep adapting as AI advances. A strong AI strategy is not just about technology choices; it’s about aligning innovation with business outcomes and measuring success beyond direct or short-term ROI, through long-term value, adaptability, and impact. We’re seeing more Middle Eastern businesses take this approach, focusing less on hype and more on purpose-driven adoption, using AI to power specialized offerings, sector-wide and even national transformations. At PwC, we help clients put that strategy into action, ensuring their AI investments are both relevant today and resilient tomorrow.
What are the biggest blind spots companies face when adopting AI, particularly around data readiness, governance, and talent alignment?
One of the biggest blind spots is underestimating the impact of foundations like data quality and governance are to AI success. Many organisations still operate in silos where data is inconsistent, inaccessible, or lacks a unified governance model. Without this foundation, even advanced AI systems fail to scale. Another challenge lies in human capability, bridging the gap between technical understanding and strategic application. Companies often overlook the need to upskill or reskill employees and embed cross functional collaboration. As a firm, we advise clients to treat AI readiness as a business transformation, not a technology implementation. This means assessing data maturity, governance frameworks, and workforce readiness simultaneously to ensure sustainable value creation.
How does PwC view the balance between innovation and responsibility — especially as AI rapidly evolves beyond traditional business use cases?
Balancing innovation with responsibility is at the heart of PwC’s approach to AI. We believe that rapid progress must be matched with ethical foresight and sound governance. As AI extends into decision making and citizen facing services, organisations must ensure that innovation is transparent, fair, and explainable. Our Responsible AI framework helps clients embed these principles from the outset, assessing potential risks, addressing bias, and ensuring accountability across every stage of the AI lifecycle. Responsible innovation is not about slowing progress; it is about building systems that people can trust and depend on for years to come.
What happens when people, processes, and technology aren’t aligned for AI integration? How can organizations correct course?
When alignment is missing, AI projects tend to stay in pilot mode or fail to demonstrate tangible real-world outcomes. We often see strong technologies being deployed without sufficient process reengineering or cultural readiness. Correcting course requires leadership focus on three dimensions: purpose, process, and people. Leaders need to define a clear problem statement for AI to solve, redesign workflows to support the transformation, and upskill people to operate in AI augmented environments.
What practical steps can businesses take to move from AI experimentation to responsible, secure, and scalable implementation?
To move from AI experimentation to responsible, secure, and scalable implementation, organizations need to start with clarity and intent. That means defining the opportunity or problem statement, setting measurable outcomes, and knowing what success looks like, as well as when a pivot is needed. Additionally, responsibility must be built in from the start, not added later. Embedding governance, safety, and security features, such as human oversight, bias auditing, and explainability, early in the design ensures that AI solutions can scale without compromising trust or compliance. Equally important is designing with humans at the center. Even automation-focused AI impacts people, whether employees, customers, or decision-makers. Systems that ignore human experience and context rarely succeed in real-world environments. Finally, organizations must design for agility and continuous evolution. In a field where today’s innovation becomes tomorrow’s legacy, scalable AI requires adaptable architectures and a culture of ongoing learning.
How can leaders build governance and trust frameworks that ensure AI innovation remains sustainable and ethical?
Building sustainable and ethical AI starts with trust by design. Leaders need to establish governance frameworks that are not separate from innovation but embedded into every stage, from solution design to deployment and ongoing monitoring. Effective AI governance blends clear accountability, transparency, and human oversight. This means defining who is responsible for outcomes, ensuring AI decisions can be explained, and continuously auditing for bias, security, and compliance. Governance should enable innovation, not restrict it, by giving teams the confidence and structure to experiment responsibly. Equally important is creating a culture of ethical awareness. Policies alone are not enough; leaders must foster cross-functional collaboration between technologists, risk managers, and business strategists, so that ethical considerations are built into decision-making early on.
From PwC’s perspective, what does “responsible reinvention” truly mean — and how can organizations use AI to create real business value, not just headlines?
Responsible reinvention means leveraging technology to create enduring value, not short-term visibility. It is about embedding technology, such as AI, into the DNA of the business, aligning it with strategy, performance, and purpose. Building on our regional experience, we view responsible reinvention as a journey that redefines how organisations think, operate, and deliver value. This involves using AI to solve real business problems such as improving public services, optimising supply chains, and enhancing citizen experiences, while ensuring decisions remain explainable and outcomes equitable. In essence, responsible reinvention ensures innovation contributes to both economic growth and societal progress.
What trends or priorities do you see shaping AI investment and transformation strategies across the Middle East in the next 12 to 18 months?
The next 12 to 18 months will be a defining period for AI in the Middle East. We expect increased investment in national AI infrastructure, sovereign data platforms, and Generative AI use cases across government and other sectors. Countries are focusing on building local capabilities, leveraging and building on global advancements, and strengthening their data ecosystems. The Middle East is not just adopting AI; it is shaping up to be a global player in the AI dialogue on how to innovate responsibly and at scale. PwC is proud to be part of this transformation, helping clients design strategies and implementing solutions that are both ambitious and grounded in long term value.