The opening day of the Data Innovation Summit MEA 2026 set the tone for the entire event, navigating the conversation away from speculative AI experiments and toward building production-grade data foundations and enterprise scale. Across five dedicated stages, speakers explored how organizations in the Middle East and Africa can establish accountable governance, streamline architectures, and embed intelligent systems into core operations.
Plenary Keynotes (Stage P1)
Summit Chairman Armin Kech, Group Data Governance Director at Swiss Re, opened the conference by welcoming delegates and highlighting the critical need for operational value creation and governance across modern data management programs.
The main stage continued with the Future Outlook discussion. Hyperight AB Founder Goran Cvetanovski, AI Governance Evangelist Giovanni Leoni, and Women in AI Strategic AI Lead Alexis Jean Baptiste convened for a “Beyond the AI Race: Where Will Real Enterprise Value Be Created Next?” The 20-minute conversational session explored the contrasting Enterprise AI maturity curves across Europe and the Middle East, examining how differing approaches to regulation, digital sovereignty, infrastructure, and speed of adoption shape real-world transformation.
The plenary sessions started with Nizar Hneini, Senior Partner and Managing Director at Roland Berger, who presented “From AI Strategy to AI at Scale: Closing the Execution Gap in the GCC”.
Following Hneini, Waqas Hashmi, Area Vice President for GCC & Pakistan at Teradata, delivered his keynote “Responsible Autonomy: Governing the Age of Agentic and Generative AI.” Hashmi addressed how regional boards across banking, telecom, and aviation are going from question-answering tools to autonomous AI agents.
Closing the plenary stage for Day 1, Vanessa Eriksson, AI & Cybersecurity Strategy Advisor at Vanessa Eriksson Ab., delivered “Beyond the AI Boom: The Real Economies of AI.” Eriksson analyzed compute budgets, token economics, and workforce adaptation, urging C-suite executives to prepare for an AI-mediated market where brands must actively compete for “share of model”. 
Track Highlights
The four stages were packed with applicable examples and presentations.
AI Strategy & Governance Stage (Stage M1)
Aleksandras Tkacenko, AI Industry Specialist for Banking at Teradata, started the day with a talk on transforming fragmented customer data into reusable data products for financial services. Jawad Saleemi, Head of AI & Data at Sparebank1 and Assistant Professor at Oslo Metropolitan University, presented “The AI Execution Gap: What the Top 5% Actually Do”, detailing how leading companies bridge product management and AI engineering to achieve measurable impact.
In the afternoon, Brent Pienaar, Head of Digital Transformation & Automation at Qiddiya Investment Company, outlined strategies for building an AI-enabled workforce using structured training paired with organic experimentation. Hajar El Hanafi, AI & Data Transformation Lead at Electrolux Group, shared practical learnings from Electrolux’s S&OP AI Lighthouse initiative, detailing how cross-functional teams apply AI to demand forecasting while preparing for EU AI Act compliance. Closing the stage, Shashank Sridharan, Group Head of Enterprise Analytics & Intelligence at Allianz Partners, presented privacy-first architectures designed to balance chronic-risk healthcare personalization with strict regulatory compliance.
Data Strategy & Governance Stage (Stage M2)
The day began with Mike Burke, Senior Manager of Solutions Architecture at Fivetran and dbt Labs, who demonstrated how to build open context layers for AI agents using structured transformation workflows. Concurrently, Siddharth Dwivedi, Senior Solutions Architect at ClickHouse, introduced “The Agentic Data Stack: Conversing with Your Data,” illustrating how real-time OLAP databases power conversational interfaces. Ibrahim Colak, Chief Data & Analytics Officer at InsuranceMarket.ae and Alfred Holdings, followed with “One Definition, One Number: Fixing Trust in Our Data Before We Let AI Near It,” focusing on resolving core data quality and trust issues.
Later in the day, Chris Unwin, Field CTO for Data Governance at Collibra, advocated for engineering-led data governance that moves past theoretical frameworks to solve practical lineage and compliance challenges. Ramachandra Yermal, Head of Solution Architecture at ENEC, discussed safety guardrails for adopting agentic AI within critical energy infrastructure. Olga Ilunga, Head of Data Analytics at MetLife Gulf, detailed strategies for embedding scalable data products into insurance operations across five Gulf markets. Lakshmi Krishnamurthy, Head of Data Governance at AW Rostamani, wrapped up the track by explaining how treating data as a product fosters decentralized value creation across business units.
Partner of this stage was Fivetran, and the stage programme was moderated by Mohamed Adil Elsayed Elmaki, Senior Manager of Data Analytics & AI at EY.
Analytics & Decision Intelligence Stage (Stage M3)
The track opened with Altaf Patel, VP of AI Reinvent & Engineering at Novo Nordisk, who shared how the organization shifted from scattered AI experiments to strategic “big bets” across its global value chain. Will Martin, EMEA Data & AI Evangelist at Dremio, then presented on low-ETL architectures, open file formats, and the resurgence of semantic layers in modern enterprise data stacks.
In the afternoon, Shehla Tanveer, Head of Data and Analytics at Al Futtaim Real Estate, showcased how advanced analytics and RPA use cases drive operational efficiency across engineering, construction, and facilities management. Louis Karam, Head of Analytics and BI at C1 Network, shared frameworks for producing commercial analytics that executive teams actually act upon. Closing the stage, Jad Kachmar (Head of Operations) and Juan Ignacio Colombo (Senior Operations Manager) from PRYPCO co-presented on using AI and granular data signals to evaluate and unlock fractional real estate investment opportunities.
Partner of this stage was ClickHouse and was moderated by Gopi Maren, Global AI Delegate – UAE at the Global Alliance for Artificial Intelligence.
Machine Learning, Gen. & Agentic AI Stage (Stage M4)
The track opened with Steyn van Zyl, BI Director at Aujan Coca-Cola Beverages Company, who explored how humans and AI couple into functioning working systems within multi-market FMCG operations. Usman Arshad, Senior AI Engineer at Imdaad, then delivered a technical session on engineering trustworthy AI, covering document intelligence, evaluation pipelines, and fallback mechanisms when models make incorrect decisions in production.
Later, Sreeram Ramesh, Senior Manager of Data Science at Adidas, presented “Unlocking AI Value: Engineering What You Control,” focusing on supply chain infrastructure and data readiness. Arockiaraj Arockiam, Head of Data & AI Platforms at MultiBank Group, evaluated deployment trade-offs across cloud, hybrid, and on-premise architectures for generative AI services. Closing Day 1, Harikrishna Jiju, AI Engineer at Standard Chartered Bank, presented a detailed case study on designing a multi-agent GraphRAG compliance engine that reduced manual policy assessment time by 90% across 40+ countries.
Partner of this stage was Snowflake, and the stage was moderated by Michael Malek Director of Data Management.
About DIS MEA & The Organizers
- What is DIS MEA?
The Data Innovation Summit MEA (Middle East & Africa) is the region’s leading annual conference dedicated to data-driven and AI-ready enterprise transformation. Constructed to address the core pillars of modern digital business: Data, People, Processes, and Technology, the summit bridges technical execution with executive strategy across plenary keynotes, track presentations, live showcases, and hands-on workshops.
- Who Organizes It?
The summit is organized by Hyperight AB, an international media and event production company specializing in data management, advanced analytics, and artificial intelligence content. Hyperight designs practitioner-led knowledge platforms worldwide to help enterprise decision-makers and technical leaders accelerate digital innovation and scale responsible AI adoption.
