Enterprise AI Strategy
Building AI operating models that move organizations from pilot to production — at scale, with governance, and with measurable business impact.
The Executive
25 years turning complexity into competitive advantage
Kader Sakkaria is a global Data & AI executive who led a 300+ person team delivering AI-powered solutions at enterprise scale. His work sits at the intersection of strategy, technology, and organizational change — guided by proprietary frameworks including the AI Maturity Spectrum, AIQ Scorecard, and the GAIOC Framework for building lasting organizational AI capability.
Over a career spanning Fortune 500 companies — including BMO Harris Bank, Deloitte, Accenture, TransUnion, and State Farm — Kader has built a reputation for translating AI from boardroom aspiration into operational reality. He doesn't just advise on transformation; he leads it.
A published author with Simon & Schuster and a board trustee for the Teachers' Retirement System of the State of Illinois (TRS Illinois), Kader brings both practitioner depth and governance perspective to every conversation about AI's role in the enterprise.
Credentials & Education
- MBA — Kellogg School of ManagementNorthwestern University
- MS — Computer ScienceGraduate studies in technology
- DBA in Artificial IntelligenceSSBM Switzerland — In Progress
- 2022 Chicago CIO ORBIE FinalistTechnology leadership recognition
- Board Trustee — TRS IllinoisTeachers' Retirement System of Illinois
Holds a patent for a Method and System for Estimating Relocation Costs (US11455559B2).
25+Years leading transformation
4Continents — Led Global Data & AI Teams at Enterprise Scale
6Proprietary frameworks
2Books published / forthcoming
Career
A career built at the frontier of enterprise technology
2022 – Present
Global Head of Data & AI
Enterprise AI Leadership
Led a 300+ person team building enterprise AI capabilities at scale across 4 continents. Responsible for AI strategy, data modernization, and platform delivery across a global organization.
2019 – 2022
Chief Digital & Technology Officer
Ruffalo Noel Levitz (RNL)
Led strategic technology and digital transformation initiatives across the organization. Recognized as a 2022 Chicago CIO ORBIE Finalist for technology leadership excellence.
Prior Roles
Senior Technology Leadership
Cartus · Realogy Leads Group
Oversaw strategic technology and digital transformation initiatives, building the organizational and technical foundations for AI-ready enterprises.
Earlier Career
Technology & Consulting Leadership
BMO Harris Bank · Deloitte · Accenture · TransUnion · State Farm · HighMark · US Foods · Ryder Logistics
25+ years of enterprise technology leadership across financial services, insurance, logistics, and professional services — building the cross-industry perspective that informs his AI frameworks today.
Areas of Expertise
Where strategy meets execution
Data Modernization
Transforming legacy data architectures into AI-ready platforms. The foundation that determines whether AI investments deliver or disappoint.
Digital Transformation
Leading the organizational, cultural, and technical change required for enterprises to compete in an AI-first world.
AI Governance & Risk
Designing responsible AI frameworks that balance innovation velocity with enterprise risk management and regulatory compliance.
Technology Leadership
Building and scaling high-performance technology organizations — from team design to talent strategy to executive alignment.
Board & Advisory
Bringing practitioner depth to board-level conversations about technology risk, AI investment, and digital strategy.
Affiliations & Recognition
Global Data & AI Executive
Simon & Schuster Author
TRS Illinois Board Trustee
Kellogg MBA — Northwestern
MS Computer Science
2022 Chicago CIO ORBIE Finalist
Patent Holder
Intellectual Property
Patented innovation in AI-driven estimation
Kader holds a granted United States patent for a novel method and system that applies machine learning and data modeling to estimate relocation costs with greater accuracy — an innovation that reflects his career-long commitment to turning data into practical, real-world solutions.
United States PatentUS11455559B2
Method and System for Estimating Relocation Costs
A machine learning–driven approach to modeling and estimating the cost of employee relocations, applying data science to a domain historically reliant on manual estimation and rule-based heuristics.
Continue exploring
Published worksChaos by Design & moreKader's books with Simon & Schuster bring the frameworks and philosophy behind his executive practice into a practitioner's guide for AI-era leaders.The frameworksSeven proprietary modelsThe AI Maturity Spectrum, AIQ Scorecard, Human + AI Operating Model, and three more — the intellectual architecture Kader has built over 25+ years of enterprise AI leadership.
Invite Kader to speak, advise, or collaborate
Whether you're building an AI strategy, planning a keynote, or looking for board-level technology perspective — let's talk.