Nidal Azba, Managing Director of Kyndryl in Saudi Arabia, discusses the results of their recent KSA Readiness Report in regards to business momentum, AI adoption and early returns in this exclusive Q&A.
What types of returns are businesses experiencing, and what is driving this momentum?
According to the Kyndryl 2025 Readiness Report, Saudi organisations are beginning to see measurable returns from their AI investments, particularly in operational efficiency, faster decision-making, and improved customer experiences. These early gains are fuelled by growing leadership commitment, increased experimentation, and alignment with national digital transformation priorities. As Vision 2030 accelerates modernisation across sectors, companies are integrating AI to streamline workflows, reduce costs, and strengthen competitiveness.
However, these returns remain at an early stage — not just in Saudi Arabia, but across the world —with many enterprises recognising that sustained value will require stronger digital foundations, more resilient infrastructure, and a workforce equipped with the skills needed to scale AI beyond pilot deployments.
Given the Saudi government’s continued focus on digital transformation, there is a clear opportunity to build on this momentum and accelerate progress.
Why do AI initiatives stall after proof-of-concept, and how can businesses overcome this bottleneck?
More than half of C-level executives representing Saudi organisations report that innovation often stalls after the proof-of-concept stage because foundational technology issues surface once AI moves toward production, as per the findings of our Readiness Report. Legacy systems, fragmented environments, and limited integration readiness create barriers that prevent scaling. Additionally, skills gaps and pressures to demonstrate ROI amplify hesitation.
To overcome this, businesses must modernise their core infrastructure, strengthen cloud and data environments, and invest in workforce capabilities. Moving from experimentation to enterprise-wide deployment requires adopting scalable architectures, implementing resilient cybersecurity frameworks, and aligning business and technology teams to ensure AI solutions are practical, secure, and value-driven long term.
Taken together, this creates a strong opening for organisations to pull ahead. With national momentum behind digital transformation, businesses that act now can turn today’s challenges into a competitive advantage, accelerating deployment, capturing early value, and shaping industry standards. By prioritising readiness and moving decisively, Saudi organisations can position themselves as leaders in scaling practical, secure, and high-impact AI solutions.
What foundational gaps are most common in Saudi organisations?
The report shows that 53% of C-level executives representing Saudi organisations face foundational technology issues that hinder progress. Common gaps include legacy IT systems that are difficult to modernise, complex and fragmented environments that slow integration, and insufficient data readiness for advanced AI applications.
Many companies continue to face difficulties unifying systems across cloud and on-premise environments, which can slow down innovation. As technology advances rapidly, 94% report challenges keeping pace, highlighting the complexity of ongoing infrastructure upgrades. Addressing these gaps requires investment in modern architectures, stronger cybersecurity foundations, and cloud strategies aligned with regulatory and sovereignty requirements emerging across the Kingdom.
Why does confidence outweigh capability, and how can organisations assess whether their infrastructure is future-ready?
Many leaders believe their environments are strong based on current performance, yet fewer assess future readiness in the context of AI, cybersecurity threats, or regulatory shifts. The rapid pace of technological advancement, acknowledged by 94% of Saudi respondents, creates blind spots in long-term planning. To realistically examine readiness, organisations must evaluate their infrastructure against resilience standards, integration capabilities, and compliance expectations. Independent assessments, modernisation roadmaps, and benchmarking against global best practices help highlight gaps early. Future-ready environments are agile, secure, sovereign-aligned, and capable of supporting AI innovation at scale, not just isolated deployments.
What changes should employees and employers expect as AI transforms jobs within 12 months?
With 91% of leaders expecting AI to transform jobs within a year, employees can anticipate shifts toward more analytical, strategic, and oversight-focused roles as repetitive tasks become automated. AI will augment work and act as a collaborative partner, making people readiness essential to capturing its full value.
Employers will need to redesign job functions, introduce new AI-enabled workflows, and adapt performance expectations. Workforces will interact more frequently with AI tools, requiring stronger digital literacy and human-machine collaboration skills. This means organisations must place greater emphasis on preparing employees to work effectively and responsibly alongside these systems.
Organisations must also prepare for reskilling at scale, ensuring employees can transition into new roles created by AI adoption. Ultimately, AI will reshape organisations by elevating productivity while demanding continuous learning and more flexible workforce models.
Which skill gaps pose the greatest risk to scaling AI?
Technical and cognitive skills gaps both pose significant risks, but the most critical challenges relate to the shortage of core digital skills and the advanced capabilities required to operate and govern AI. According to the report, 35% of Saudi leaders cite deficits in technical skills needed to harness AI’s potential, including data engineering, cybersecurity, and AI model management. Another 35% highlight concerns around cognitive skills such as problem-solving, critical thinking, and adaptability, abilities essential for navigating rapid technological change. Without closing these gaps, organisations will struggle to scale AI safely, effectively, and in alignment with business goals.
How can organisations balance automation with workforce upskilling?
Balancing automation with workforce development requires a proactive and people-centred approach. Organisations must anticipate which roles will evolve or disappear and invest early in upskilling and reskilling programs that align employees with emerging opportunities. With 31% concerned about how to reskill workers affected by AI, companies should integrate continuous learning, establish AI literacy programs, and create pathways into new technical and hybrid roles. As mentioned earlier, automation should be framed as augmentation, not replacement, enabling employees to shift toward higher-value tasks. Transparent communication, structured capability-building, and collaboration with educational partners will be essential for ensuring employees transition confidently into the AI-enabled workplace.
Image Credit: Kyndryl
