Hina Waseem
Enterprise Solution Architect | Microsoft Certified Trainer | Connecting AI Education to Opportunity
New York City, New York, United States
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Hina Waseem is an Enterprise Solution Architect and Microsoft Certified Trainer (MCT) experienced in enterprise architecture, cloud modernization, AI adoption, and digital transformation. Beyond her enterprise role, she is passionate about expanding AI education by connecting industry, universities, governments, nonprofits, and communities to create meaningful opportunities. She has led AI skills initiatives introducing Microsoft learning resources to university students and educators. She also founded the Future Leaders Academy to help students move beyond AI awareness through continuous learning, leadership development, and real-world application.
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Teaching AI for the Real World
Microsoft Learn, AI Skills initiatives, and certifications provide learners with an excellent technical foundation, yet many still struggle when they encounter real organizational challenges. Drawing on more than 18 years of experience delivering enterprise technology solutions and her current role as an Enterprise Architect and Microsoft Certified Trainer, this session shares practical techniques for helping learners connect AI knowledge with business value, stakeholder needs, responsible AI, governance, and real-world decision-making. Attendees will leave with immediately applicable teaching strategies that transform technical labs into realistic enterprise scenarios and better prepare learners for success beyond the classroom.
Building an AI Agent That Knows Its Limits
What happens when an AI agent is asked to support an important enterprise decision but the information it receives is incomplete or inconsistent?
In this practical, demo-first session, we'll use Microsoft Copilot Studio to build and progressively improve an enterprise decision-support agent. Through a realistic production-change scenario, we'll explore how agent instructions, document evidence, and organizational knowledge influence the quality of its analysis.
You'll see how an agent can identify missing information, surface conflicting evidence, and prepare useful insights while keeping final decisions with people.
AI Meets eDiscovery: Governing Data, Human Review and Accountability
AI can help organizations search, analyze, summarize, and work with large volumes of enterprise information. In eDiscovery, however, introducing AI is not simply a productivity decision. The data may be sensitive, context matters, and AI-generated conclusions can influence consequential human decisions.
This session examines AI in eDiscovery from an enterprise architecture and governance perspective. Using the eDiscovery workflow as a practical model, we will explore where AI can assist, where human review remains essential, and how organizations can establish clear boundaries for data access, validation, decision rights, and accountability.
Attendees will learn a practical framework for asking critical questions before introducing AI into an eDiscovery workflow: What data should AI be allowed to access? What can it analyze or infer? Which outputs require human validation? Where should AI assistance end and human judgment begin? And ultimately, who is accountable for the outcome?
The session connects eDiscovery, AI governance, data security, and enterprise architecture to help organizations adopt AI while maintaining appropriate human oversight and accountability for sensitive enterprise information.
Before You Scale AI: Is Your Enterprise Ready?
AI pilots are easy to start. Scaling them responsibly across an enterprise is much harder.
As organizations move from experimenting with Microsoft Copilot, AI agents, and other AI capabilities toward broader adoption, a critical question often gets overlooked: Is the enterprise actually ready to scale AI?
This session explores AI readiness from an Enterprise Architecture perspective. Rather than focusing on a specific product or another governance framework, we will examine the practical organizational conditions that need to come together before AI can scale successfully—including architecture, governance, security, data, decision ownership, workforce readiness, and operations.
We will also explore an increasingly important question: who owns what when humans and AI participate in the same business workflows? Where should accountability remain with people, where can AI operate with greater autonomy, and how should organizations define the boundaries?
Through practical scenarios and audience discussion, attendees will learn how to identify readiness gaps, ask better questions across technology and business teams, and determine who needs to be involved before moving AI initiatives from experimentation toward enterprise-scale adoption.
Attendees will leave with a practical set of questions they can use to start an AI readiness conversation within their own organizations.
Beyond Chatbots: Building a Governed Enterprise Decision-Support Agent
Building an AI agent is becoming easier. Deciding what an enterprise agent should be allowed to reason about, recommend, and ultimately decide is much harder.
In this practical session, we’ll build an Enterprise Change Readiness Advisor using Microsoft Copilot Studio that analyzes a production change package against organizational Change Advisory Board (CAB) standards.
Through a live enterprise scenario, you’ll see the agent reason across multiple documents, identify conflicting evidence and dependencies, distinguish verified facts from inference, apply organizational policy, surface missing evidence, and produce a structured decision-readiness assessment—without allowing AI to approve or reject the change.
Along the way, we’ll examine a critical agentic AI architecture principle: use AI where reasoning is valuable while preserving deterministic controls and accountable human decision-making where they matter.
Attendees will leave with a reusable architecture pattern for governed decision-support agents that can extend beyond change management to architecture review, risk, compliance, operations, and other enterprise workflows.
Beyond AI Awareness
Artificial Intelligence is opening new opportunities for learners worldwide, yet many leave AI training asking the same question: "What do I do next?" This session was inspired by a student's question at the conclusion of a Microsoft AI initiative that engaged learners across twelve public universities. It explores how Microsoft Certified Trainers can help learners move beyond awareness toward sustained learning, real-world application, and meaningful opportunities. Attendees will leave with practical approaches they can immediately apply to help learners continue their AI journey long after the classroom experience ends.
AI Maitri Global Summit 2026 Sessionize Event
Hina Waseem
Enterprise Solution Architect | Microsoft Certified Trainer | Connecting AI Education to Opportunity
New York City, New York, United States
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