Engineering Tomorrow: How SoftServe is Powering AI-Driven Transformation in the Middle East

As Middle East enterprises accelerate their digital journeys, the demand for intelligent, agile, and secure technology solutions continues to grow. From cloud transformation to AI adoption and digital engineering, businesses across sectors seek partners who can deliver innovation with impact. In this exclusive conversation, we spoke to Fadi Kanafani, General Manager – Middle East at SoftServe, a global IT consulting and digital services firm, to explore how the company is helping regional clients harness cutting-edge technologies such as generative AI, digital twins, and cloud-native platforms to future-proof operations and drive meaningful transformation.

What are the most in-demand digital engineering services among Middle East enterprises today?

Technology advancement is driving businesses to rethink their investments to enhance scalability, resilience, and operational agility. Which is why digital engineering services such as automation, data analytics, artificial intelligence (AI), digital twin technology, and machine learning are gaining favour. Cloud transformation, AI and data science integration, cybersecurity modernization, and intelligent automation are currently in high demand. There’s a significant regional push toward real-time analytics, digital twins, and generative AI for decision-making and enterprise performance optimization. Additionally, sectors like healthcare, BFSI, and retail are showing strong interest in cloud-native development, AI-powered tools, and secure data architecture to future-proof their operations.

How is SoftServe helping regional clients fast-track their AI and data science adoption journeys?

SoftServe supports AI and data science adoption by embedding advanced tools like generative AI into enterprise systems to improve decision-making, enhance threat detection, and streamline performance analytics. In cybersecurity, SoftServe enables real-time threat anticipation and response by integrating AI-driven behaviour analysis and anomaly detection. The company also assists clients through co-development of AI solutions, upskilling programs, and partnerships with NVIDIA, Google, Azure and AWS, ensuring that AI capabilities align with regional business demands and regulatory expectations.

Can you share insights into how SoftServe tailors its cloud transformation strategies across industries like healthcare, BFSI, and retail?

SoftServe adapts cloud transformation strategies by aligning them with sector-specific needs. In healthcare, for example, our solutions enable cloud-based patient data systems and AI-powered diagnostics to reduce physical resource demands and enhance service efficiency. In BFSI, our focus is on secure, compliant AI-driven platforms that minimize environmental impact and improve digital infrastructure. Retail clients can benefit from scalable, cloud-native solutions that enhance customer experiences and support rapid procurement via cloud marketplaces. Across industries, SoftServe emphasizes hybrid and multi-cloud architectures combined with AI for dynamic workload management and cost optimization.

What innovation trends are you observing in enterprise performance management and decision intelligence?

Enterprise performance management is rapidly evolving with the integration of AI, digital twins, predictive maintenance, and behavioral analytics. Generative AI co-pilots are being used to assist in real-time decision-making, while GPU-as-a-service models support heavy computational tasks without requiring major infrastructure investments. These technologies enable CIOs to anticipate issues, reduce latency, and maintain business continuity. The emphasis is shifting toward proactive, data-driven enterprise strategies that turn operational data into a strategic business asset.

How do you strike the right balance between human expertise and AI automation in delivering impactful outcomes?

The key to balance lies in human-AI collaboration. At SoftServe, AI is positioned as an enabler rather than a replacement. AI handles tasks like threat prediction, anomaly detection, and data processing, while humans oversee strategic decisions, provide contextual interpretation, and ensure ethical compliance. Governance frameworks and transparency checkpoints are built into workflows to maintain accountability and trust. This balanced approach ensures that automation amplifies human expertise while preserving decision integrity and regulatory alignment.