
Azaz Rasool
Director - AI & Data Strategy
From his early days of building telecom billing software to client facing roles in Switzerland, delivering product consulting at Microsoft, and service expertise at Wipro, he has built a multifaceted career spanning banking, telecom, transportation and other domains. A renowned keynote speaker and thought leader in AI, Big Data, and Digital Transformation, he seamlessly integrates technology in multiple industries, playing a critical role in Saudi Arabia’s emergence as a FinTech powerhouse.
In a personal interview, Azaz shared his incredible journey and gave insights into his plans.
How have your past experiences helped you develop the ability to translate business needs into actionable data and AI strategies?
As I think back on my experience in a variety of fields and industries, I've developed a profound awareness of what companies require. Real value extraction from data is more important than merely creating enormous data platforms or combining data from multiple sources. Creating systems that convert unprocessed data into useful insights is crucial.
For instance, I have built systems which allow monetizing data in real-time and agents which automate human tasks. We can forecast purchasing trends and send tailored offers at the appropriate time by combining client demographics, purchase history, and geographical data. What truly makes an impact is the capacity to transform data into a strategic advantage. Data isn't sufficient on its own; its real value comes from how we use it to propel company expansion.
How do you evaluate and identify opportunities for AI and other technologies to create meaningful value for customers?
As the Director of AI and Data
Strategy, I evaluate and rank AI-driven use cases to make sure they produce measurable ROI and commercial value. I'm concentrating on finding use cases that employ technologies like generative AI to provide quantifiable benefits out of many possible use cases across different domains. For example: In Telco, we have built an Artificial intelligence (AI)- powered Digital Twin which increases the efficiency of Network operations and decision-making, reduces operational costs and increases customer experience.
In Banking, we have built Graph-based Customer 360, AI-powered Credit decision models, and AI-powered Virtual assistants, which are available around the clock at much lower prices and are multilingual. We make sure AI solutions increase productivity and generate a 3x to 5x return on investment over time by weighing investment against possible rewards, such as cost savings and scalability.
What are the most intriguing challenges you face today, and how are you working to solve them?
I have experienced three major challenges in delivering my Data & AI projects: Availability of reliable data, AI explain ability and User Adoption. Assuring reliable, high-quality data is the first step, as it is essential to efficient analytics. The second challenge is explaining 'what and how' of AI solution and its outcomes.
This is also important for compliance, governance and stakeholder approvals for AI, machine learning, and generative AI solutions. The last significant obstacle is user adoption; even the best software, consultants, and processes are useless if people are not ready or willing to utilize them. The success of new procedures and technology depends on raising awareness, empowering teams, and cultivating an accepting culture.
What emerging technological advancements do you foresee shaping the future of this industry?
With Agentic AI, you can now operate most of your business functions with agents. Beyond automation, Gen AI will evolve into industry-specific co-pilots (e.g., hyper-personalized banking advisors and predictive healthcare diagnostics). My current Doctoral (DBA) research focuses on fine-tuning open-source LLMs for SME scalability, reducing dependency on proprietary models like GPT-4.
The future isn’t just about adopting tools; it’s about strategizing and building systems where techno- logy, ethics, and business outcomes converge
In Banking, we have built Graph-based Customer 360, AI-powered Credit decision models, and AI-powered Virtual assistants, which are available around the clock at much lower prices and are multilingual. We make sure AI solutions increase productivity and generate a 3x to 5x return on investment over time by weighing investment against possible rewards, such as cost savings and scalability.
What are the most intriguing challenges you face today, and how are you working to solve them?
I have experienced three major challenges in delivering my Data & AI projects: Availability of reliable data, AI explain ability and User Adoption. Assuring reliable, high-quality data is the first step, as it is essential to efficient analytics. The second challenge is explaining 'what and how' of AI solution and its outcomes.
This is also important for compliance, governance and stakeholder approvals for AI, machine learning, and generative AI solutions. The last significant obstacle is user adoption; even the best software, consultants, and processes are useless if people are not ready or willing to utilize them. The success of new procedures and technology depends on raising awareness, empowering teams, and cultivating an accepting culture.
What emerging technological advancements do you foresee shaping the future of this industry?
With Agentic AI, you can now operate most of your business functions with agents. Beyond automation, Gen AI will evolve into industry-specific co-pilots (e.g., hyper-personalized banking advisors and predictive healthcare diagnostics). My current Doctoral (DBA) research focuses on fine-tuning open-source LLMs for SME scalability, reducing dependency on proprietary models like GPT-4.
Industries are evolving rapidly, with disruptions occurring in months, not years. AI is revolutionizing healthcare with advanced imaging, diagnostics, and single-pass whole-body scans. Telecom leverages digital twin technology and geospatial analytics to optimize 5G antenna placement, enhancing coverage while reducing costs. Finance integrates AI for fraud detection, customer service, reg tech, and credit decisions.
With regulations like NDMO- /PDPL, tools for explainable AI (XAI) and synthetic data generation are now essential. My DBA course’s 'Ethical AI' module deepened my understanding of AI privacy, ethics, and safety, enabling me to integrate ethical principles into AI lifecycle management for clients.
Mean while, cross-industry innovation is accelerating - like stc Group, a telecom giant, first launched stcpay as a fintech subsidiary, which later evolved into stcbank. Technologies like AI, multimodal LLMs, Agentic AI, geospatial analytics, and knowledge graphs are converging to create ground-breaking solutions across industries such as supply chain and retail. This fusion is driving demand for cross-domain expertise, reshaping industries at an unprecedented pace.
To stay competitive in this fast tech evolution and domain fusion, we as leaders must understand what’s happening under the hood and how to strategically use it to generate business value. My recent courses, Chief Strategy Officer from INSEAD (2024) and Doctor of Business Administration (DBA) in Generative AI from Golden Gate University (2026) have equipped me to stay competitive and relevant in the market.
What are your aspirations for the next few years?
In the next few years, I aim to build strategies for ethical AI and Generative AI solutions across industries and inspire and mentor the next generation of data leaders. Completing my DBA in Generative AI (2026) will further my mission to democratize AI-driven innovation, making it accessible for SMEs while advancing Saudi Arabia’s Vision 2030 in AI-driven economic diversification.
Azaz Rasool, Director - AI & Data Strategy
Azaz Rasool is a seasoned leader in technology, banking and telecom. He brings a comprehensive viewpoint to telecom and financial innovations, having held positions in multinational behemoths like Microsoft (product development and consulting) and Wipro (system integration and services), he is an expert at the nexus of business strategy and technology.
With regulations like NDMO- /PDPL, tools for explainable AI (XAI) and synthetic data generation are now essential. My DBA course’s 'Ethical AI' module deepened my understanding of AI privacy, ethics, and safety, enabling me to integrate ethical principles into AI lifecycle management for clients.
Mean while, cross-industry innovation is accelerating - like stc Group, a telecom giant, first launched stcpay as a fintech subsidiary, which later evolved into stcbank. Technologies like AI, multimodal LLMs, Agentic AI, geospatial analytics, and knowledge graphs are converging to create ground-breaking solutions across industries such as supply chain and retail. This fusion is driving demand for cross-domain expertise, reshaping industries at an unprecedented pace.
To stay competitive in this fast tech evolution and domain fusion, we as leaders must understand what’s happening under the hood and how to strategically use it to generate business value. My recent courses, Chief Strategy Officer from INSEAD (2024) and Doctor of Business Administration (DBA) in Generative AI from Golden Gate University (2026) have equipped me to stay competitive and relevant in the market.
What are your aspirations for the next few years?
In the next few years, I aim to build strategies for ethical AI and Generative AI solutions across industries and inspire and mentor the next generation of data leaders. Completing my DBA in Generative AI (2026) will further my mission to democratize AI-driven innovation, making it accessible for SMEs while advancing Saudi Arabia’s Vision 2030 in AI-driven economic diversification.
Azaz Rasool, Director - AI & Data Strategy
Azaz Rasool is a seasoned leader in technology, banking and telecom. He brings a comprehensive viewpoint to telecom and financial innovations, having held positions in multinational behemoths like Microsoft (product development and consulting) and Wipro (system integration and services), he is an expert at the nexus of business strategy and technology.