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Strategic Digital Transformation Leadership Program

In-Person

|

BHD 800 | SAR 8,000 *excl. VAT

A powerful, multi-institutional program that equips leaders with the strategic direction needed to drive digital transformation, while maintaining strong governance and identifying the right tools to support the journey with confidence and impact.

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Duration

5 Days

Dates

5 Apr - 9 Apr, 2026

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Location

Innovate for Bahrain, A'ali

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Earn a Certificate of Achievement

About the Course

The Strategic Digital Transformation Leadership Program is designed for leaders seeking to accelerate their digital transformation journeys. It brings together global academic leaders, technology innovators, and regulatory experts to deliver a holistic, high-impact learning experience.

The program combines strategic frameworks, real-world case studies, and applied learning to build capabilities in digital leadership, AI integration, organizational resilience, and governance. Through expert-led sessions from leading institutions, participants gain global best practices alongside regionally relevant insights to navigate today’s evolving technology landscape. A collaborative, multi-institutional design integrates expertise from academia, industry, and emerging technology providers.

Learning Outcomes

Develop leadership capabilities to drive innovation, culture change, and digital adoption

Apply human-centered and design-thinking approaches to improve products, services, and internal processes

Define a clear strategic direction for digital transformation while balancing innovation, governance, and tool selection

Foster collaboration between business teams, technology providers, and innovation enablers

Gain practical insight into real-world AI applications across operations, decision-making, customer experience, and risk management

Understand how advanced technologies, such as machine learning, automation, and on-chain security tools, enhance threat detection and operational efficiency

Strengthen knowledge of data governance and organizational resilience frameworks

Who is This Course for?

 The course is designed for leaders in mid-to-senior-level managers responsible for digital initiatives:

  • Managers seeking to strengthen digital leadership capability

  • Innovation, product, strategy, technology, and operations leaders

  • Change management and transformation leaders

  • Leaders seeking practical and structured tools to guide digital transformation

Modules

  • Session 1: Overview of AI and its Role in Fintech

    • Definition of AI, machine learning, and generative AI

    • AI applications in financial services: payments, lending, insurance, wealth management

    • The transformative potential of AI in fintech

    • Case studies of AI in finance

     

    Session 2: Fundamentals of AI: Key Concepts

    • Introduction to data-driven decision-making

    • Key AI technologies: machine learning, natural language processing, and computer vision

    • Overview of AI lifecycle: data collection, model building, and deployment

  • Session 3: Machine Learning Fundamentals for Fintech

    • Supervised vs. unsupervised learning

    • Application of machine learning models in financial forecasting and risk assessment

    • Understanding credit scoring models and fraud detection

     

    Session 4: Hands-On Introduction to Machine Learning

    • Basic hands-on exercises in data analysis and model training (simplified using no-code/low-code tools)

    • Demo of a machine learning tool in the financial context

  • Session 5: Introduction to Generative AI

    • What is generative AI and its core components

    • Use cases of generative AI in fintech: personalized financial services,= chatbot development, and automated content generation

     

    Session 6: Generative AI and Chatbots in Financial Services

    • Exploring AI chatbots for customer service and financial advice

    • Case studies of chatbot deployment in fintech companies

  • Session 7: The Role of Data in AI and Fintech

    • Importance of data quality and data governance in AI applications

    • Introduction to data analytics tools in fintech

    • Compliance and privacy concerns related to financial data

    Session 8: Data-Driven Insights for Financial Decision-Making

    • Practical example: building basic financial dashboards using data analytics tools

    • Real-world case study: leveraging AI for personalized financial product recommendations

  • Session 9: AI for Fraud Detection in Fintech

    • Machine learning algorithms for detecting fraudulent transactions

    • AI-driven risk-scoring models

    • Case study: AI tools used by banks and payment processors

     

    Session 10: Implementing AI for Risk Management

    • Identifying risks using predictive modeling

    • AI applications for credit risk, operational risk, and liquidity risk management

    • Demo: Basic predictive risk model using AI tools

  • Session 11: AI in Payments

    • How AI optimizes payment processing systems

    • Use cases: AI-driven payment gateways and fraud prevention

    • Case studies: PayPal, Stripe, and AI-driven payment solutions

     

    Session 12: AI for Lending and Credit Scoring

    • AI’s impact on peer-to-peer lending and microfinance

    • Credit scoring models powered by AI

    • Case studies on AI in digital lending platforms

  • Session 13: Regulatory Landscape for AI in Finance

    • Overview of financial regulations impacting AI adoption

    • Compliance with data protection laws (e.g., GDPR, PSD2)

    • Addressing algorithmic bias and fairness in AI models

     

    Session 14: Ethical AI and Responsible Innovation in Fintech

    • Importance of transparency, fairness, and accountability in AI models

    • Ethical considerations in customer data usage

    • Best practices for deploying ethical AI in fintech

  • Session 15: Future Trends in AI for Fintech

    • Trends shaping the future of AI in finance: decentralized finance (DeFi), blockchain, AI-driven asset management

    • How AI and fintech will evolve in the coming years

     

    Session 16: Capstone Project Presentation and Course Wrap-Up

    • Team-based or individual capstone projects

    • Presentations and feedback ○ Course review and next steps

Modules

    • Understanding Digital Transformation in Financial Services

    • Human-Centered Digital Design for Financial Services

    • Enabling Innovation within Governance Structures

    • Global Case Studies: Digital Transformation in Financial Services

    • Design Thinking for Financial Innovation

    • Aligning Digital Initiatives with Business Objectives

    • Interactive Group Exercise: Building Your Organization’s Digital Vision

    • Setting the Stage – AI’s Global Inflection Point

    • AI in Financial Operations and Compliance

    • Understanding AI Models for Business Decision-Making

    • Building Strategic AI Frameworks for Financial Organizations

    • Data Governance and AI Readiness

    • AI Infrastructure for Regulators

    • The Future of AI in Financial Services

    • Interactive Group Exercise – Designing the AI-Ready Organization

    • Governance Foundations for Digital Transformation in Banks

    • AI Governance in Banking: From Risk to Responsibility

    • Integrated Governance: Digital, AI, Risk & Compliance

    • Capstone Group Exercise: Designing a Governance Framework for a Digital AI Bank

    • Governance Foundations for Digital Transformation in Banks

Instructors

Dr. James Angel

Lead Professor, Georgetown University

Dr. Tanya Roosta

Fellow and Lecturer at UC Berkeley  |  Senior Research Science Manager at Amazon AI

Olena Clayton

Strategic Programs Leader, Google

Yulia Serebriannikova

Program Manager, QubStudio

Hussain Haji

Chief Growth Officer, DOO

Chris Dos Santos

Account Executive – Financial Services, Central Banks, Exchanges (ME), Chainalysis

Zeeshan Idris

Senior Partner - Financial Services, Kearney Consultancy

Alharith Alatawi

Co-founder and CEO, Shaffra

Steven Meyer

CTO & Co-Founder, Zendata

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