Mohammad Bapu
Systems & Functional Lead - D365, Power Platform & Copilot | AI Enablement & Adoption | Speaker | Creator
Toronto, Canada
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Mohammad is a Functional Consultant at Hypertec Group, specializing in Dynamics 365, Power Platform and Microsoft 365 Copilot. He helps organizations drive digital transformation - AI adoption, streamline business processes, and implement governance frameworks that balance innovation with compliance. With hands-on experience building AI-powered solutions, automations, and copilots, Mohammad is passionate about making Microsoft AI tools accessible, practical, and impactful for diverse teams. A community mentor & technology advocate, he enjoys sharing his knowledge to empower users and organizations to innovate responsibly.
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Scaling Public Services with GenAI: City of Montréal's Copilot Studio
As a Functional Lead at Hypertec Group specializing in Dynamics 365, Power Platform, and Microsoft 365 Copilot, I'll share how the City of Montréal revolutionized citizen engagement with a Copilot Studio virtual agent.
This generative AI solution processes natural language queries across 40,000+ web pages and APIs, delivering personalized text responses for services, events, regulations, and real-time schedules like waste collection, achieving 90% efficiency gains and 4+/5 satisfaction ratings.
Drawing from my hands-on experience building AI-powered automations and governance frameworks, I'll show how this public-sector success translates to enterprise digital transformation.
You'll learn practical strategies to enable compliant conversational AI agents that make Microsoft tools accessible and impactful for diverse teams while streamlining business processes.
Shadow AI: The Governance Blind Spot Putting Your Data at Risk
Generative AI tools are being widely used inside organizations, often without approval or visibility from IT and governance teams. This “Shadow AI” creates hidden risks where sensitive data can be shared with external tools, leading to potential data leaks, compliance issues, and loss of control over critical information.
This talk explores why traditional governance models are not enough to manage this new reality. Instead of blocking AI usage, organizations need practical ways to detect, manage, and guide how AI tools are used across teams. The focus is on balancing innovation with control, so employees can use AI safely without exposing the organization to unnecessary risk.
The session will share practical approaches to building lightweight governance guardrails that support responsible AI adoption. Attendees will learn how organizations can reduce risk while still enabling productivity and innovation with AI tools.
Where Enterprise AI Actually Breaks - 5 Lessons from Real Implementations
Most enterprise AI initiatives don’t fail at the idea stage; they fail during implementation. In this session, I’ll share 5 key lessons from real-world AI adoption inside organizations, focusing on what happens after rollout.
We’ll explore common breakdown points, including low user adoption, unclear data ownership, and AI tools that don’t align with daily workflows. I’ll walk through real scenarios where initial approaches didn’t work, the constraints we faced, and the adjustments that delivered measurable results.
Attendees will leave with practical guidance on how to avoid common pitfalls, integrate AI effectively, and drive adoption across teams. This session is about decisions, trade-offs, and actionable strategies not theory/generic tool demos.
Why Enterprise AI Projects Fail and the Data Strategy Mistakes Behind It
Enterprise AI initiatives often fail not because of the technology, but due to misaligned data strategies, weak governance, and poor integration with business processes. Many organizations invest in AI tools expecting quick results, but without a strong data foundation and clear direction, these efforts struggle to deliver real value.
In this session, I will share practical insights from helping organizations adopt AI, improve workflows, and implement governance frameworks that balance innovation with compliance. The focus will be on common data strategy mistakes, including fragmented data, unclear ownership, and lack of alignment between business and technology teams.
The session will also explore how to integrate AI into everyday workflows to improve adoption and ensure it supports real business needs. In addition, attendees will learn simple ways to measure success through outcomes such as efficiency, productivity, and return on investment.
By the end of this session, participants will gain a clear understanding of why enterprise AI projects fail and how to design data strategies that enable successful, responsible, and scalable AI adoption across teams.
AI Adoption with Microsoft 365 Copilot
Microsoft 365 Copilot is transforming productivity, but successful adoption requires more than just enabling the feature, it requires strategy, enablement, and trust. In this session, we’ll walk through practical approaches to introducing Copilot into organizations, from running small pilots to scaling company-wide. Attendees will learn how to engage early adopters, create champions, and address concerns around security, compliance, and change management. Real-world examples will illustrate how IT teams and business leaders can measure Copilot’s impact on productivity while building confidence in AI-powered work.
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