Overview

As enterprises transition from Generative AI experimentation to scaled production, they encounter the “GenAI Value Paradox”: massive investment with inconsistent ROI. This masterclass, guided by the principles outlined in “AI Success Beyond Perfect Data”, dispels the common misconception that perfect data is a prerequisite for AI success. Participants will learn how to architect a “second mind” for their organisation by treating GenAI as talent to be cultivated rather than just software to be installed.

This intensive program provides a comprehensive roadmap for navigating the complexities of Enterprise AI, from bridging the gap between messy data and actionable insights to establishing robust governance frameworks. We will move beyond the hype around Large Language Models (LLMs) to explore hybrid and agentic AI architectures, ensuring deployment is not only technically sound but also ethically grounded and strategically aligned with core business objectives. By the end of this masterclass, leaders will possess a clear, actionable strategy to drive measurable outcomes and foster a culture of data-driven innovation, regardless of their current data maturity level.

Learning Objectives

• Deconstruct the “Perfect Data” Myth: Learn to extract high-value insights and deploy AI successfully even within messy or evolving data landscapes.
• Master AI Governance: Establish a robust framework for ethical AI, including decision boundaries, bias mitigation, and transparency.
• Implement Agentic AI Workflows: Understand how to move from simple chatbots to autonomous agentic pipelines that handle complex business logic.
• Bridge the Strategy-Execution Gap: Develop a value-first roadmap that aligns AI initiatives with specific P&L goals and success metrics.
• Navigate Procurement & Integration: Evaluate the strategic dilemma of “buy vs. build” and how to integrate GenAI into existing enterprise stacks.
• Architect for Trust: Build “guardrails” and RAG (Retrieval-Augmented Generation) systems to ensure reliable, factual, and sovereign AI outputs.
• Cultivate AI Talent: Shift organisational culture from a “Big Data” mindset to an “AI Apprenticeship” model, fostering human-AI collaboration.
• Scale with Operational Readiness: Apply the D-A-D (Data-Analysis-Deployment) framework to move projects from pilot to enterprise-wide adoption

Featuring Our Speakers

 

 

 

 

 

Dr M Maruf Hossain, PhD, GAICD
Founder & Chief AI Strategist
42 Consulting.AI

Named Global Top 100 Innovators in Data & Analytics (2024)

Chief AI Strategist

Dr M Maruf Hossain is Australia’s premier Fractional CAIO, delivering enterprise-grade AI leadership to boards, consultancies, and product firms. With a PhD in Artificial Intelligence from the University of Melbourne (plus a Master’s in Software Engineering and Honours in Mathematics), he combines deep technical mastery with GAICD corporate governance credentials.

Proven C-Suite Track Record: With extensive leadership experience across major organisations, he served as VP of Data Science at ANZ Bank where he led the scaling of AI initiatives across banking operations. He has also helped build Data and AI Centres of Excellence for organisations ranging from startups to large enterprises, including Credit Clear, Telstra, IBM Global Business Services, and Infosys Consulting. His work also extends to government and highly regulated sectors, supporting the development of trustworthy AI governance across telecommunications, fintech, and public agencies.

Trusted AI Authority Co-author of seminal data mining/ML papers, industry whitepapers, and AI Success Beyond Perfect Data—his bestselling guide to pragmatic AI deployment in real-world enterprises. His strategic interventions generate measurable ROI—typically delivering approved AI roadmaps and live pilots within 90 days. Enterprises hire him as a Fractional CAIO for immediate strategy ownership. Consultancies and product firms engage him as their white-label AI partner to build credible offerings that win enterprise deals.

Who should attend?

• C-Suite Executives (CDO, CDAO, CTO, CIO) seeking to define the strategic foundation and ROI for AI investments.
• Enterprise Architects & IT Leaders responsible for building the technical infrastructure and sovereign cloud environments for AI.
• Data Science Directors & Managers looking to operationalise LLMs and bridge the gap between technical teams and business units.
• Governance & Compliance Officers tasked with managing the ethical, legal, and security risks of generative technologies.
• Digital Transformation Leads focused on scaling AI initiatives and managing organisational change.

Topics Covered

• The Strategic Foundation: Beyond the Big Data Mindset
• Architecting the Enterprise AI Platform
• Governance, Ethics, and Trustworthy AI
• Operationalising and Scaling for Impact