Maria Andrade
MCA Connect, Dynamics 365 Finance & Supply Chain Functional Consultant
Montréal, Canada
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Maria Andrade is a Dynamics 365 Finance & Operations Functional Consultant at MCA Connect with hands-on experience across finance, supply chain, and several automation initiatives. She focuses on designing practical D365 solutions that bridge system capabilities, real-world operations, and how users actually work.
Area of Expertise
The Quiet Identity Shift of D365 Consultants in the AI Era
For years, we built our confidence the hard way. We learned by breaking things. We stayed up fixing posting errors. We wrote documentation from scratch and slowly earned the title “expert.”
Now the work is faster. Cleaner. Assisted.
But quietly, something shifts.
If AI handles the first draft…
If it writes the test cases…
If it suggests the configuration…
What exactly are we responsible for?
In this session, Maria will share her own internal tension as a consultant navigating this shift. The pride. The discomfort. The efficiency. The doubt.
Because this isn’t just about automation. It’s about identity.
Are we still builders?
Are we reviewers?
Are we becoming directors of intelligence instead of doers?
This conversation is honest, practical, and grounded in real D365 project moments. It’s not about fear. And it’s not about hype.
It’s about figuring out who we are becoming in the age of Copilot — and deciding that intentionally.
Navigating the Chaos and Fear of an Upgrade to D365: How to Lead People Through Uncertainty
Many companies face uncertainty around data quality, integrations, reporting, process redesign, licensing changes, and years of undocumented tribal knowledge, or what we like to call "Human Glue." Users fear losing familiar processes and moving toward automation, often driven by concerns about becoming irrelevant or losing their jobs. Leaders fear downtime, cost overruns, and organizational resistance. Project teams feel pressure from every direction.
Jamie and Maria will discuss the real sources of chaos in D365 upgrades and implementations, why fear shows up at every layer of the organization, and how functional consultants, architects, and project leaders can actively reduce that fear. We will also discuss what truly matters during data migration, including the importance of standardization, mapping discipline, and early data reality checks.
Drawing from real upgrade experiences, Jamie and Maria lean on practical strategies for creating clarity, building trust, and guiding teams through change, without pretending the journey is easy.
we aim for you to walk away with concrete approaches they can apply immediately to stabilize upgrades, improve stakeholder confidence, and lead people through transformation.
Confessions of a D365 Consultant in the Age of Copilot
What AI Is Changing About Us, Not Just Our Work.
As D365 consultants, we built our careers on knowing and playing with the system. We wrote every FDD. We debugged every issue. We designed every process from scratch. Our expertise was measured by depth, detail, and the time spent navigating complexity.
Now Copilot drafts documentation in seconds. It suggests configurations. It summarizes requirements. It accelerates data analysis. It even proposes solutions.
So what does that mean for us?
Are we becoming reviewers instead of builders? Are we losing depth or gaining leverage? What happens to expertise when AI handles the “heavy lifting”?
Through practical D365 examples such as requirements documentation, solution design, data migration logic, and governance reviews, Maria will discuss how AI is reshaping our daily work and our professional identity.
5 Ways to Design D365 for Humans in the Age of AI
As AI and automation become more common in Dynamics 365, poorly designed processes break faster and frustrate users sooner. AI does not fix weak processes. It exposes them.
Many D365 processes look great on paper but struggle once real users interact with them. When processes fail to account for exceptions, unclear ownership, or daily operational pressure, users create workarounds, even when the system is technically working as designed.
We'll walk through five practical ways to design D365 processes with human behavior in mind, especially as AI and automation enter the system. Using real implementation scenarios, we’ll explore how small design decisions can either build trust or increase friction. Topics include handling exceptions, clarifying ownership, reducing cognitive load, explaining the “why” behind process steps, and why earning user trust before enforcing processes is key to the success of a project.
AP Automation in D365: What Actually Automates (and What Doesn’t)
Accounts Payable automation in D365 F&O promises speed and efficiency, but most teams quickly learn that not everything is automated and that manual intervention is still required. Questions often come up around what can truly be automated using the out-of-the-box model versus when a custom or trained model is needed.
In practice, AP remains a mix of automation, exceptions, and human review. We will take a realistic look at AP automation in D365, including invoice capture and related capabilities. We’ll explore what reliably automates today, where processes commonly break down, and why certain invoices still require manual handling. Aka: the gap between automation expectations and operational reality.
Before Automation Works: 4 D365 Foundations Teams Skip
Automation and AI promise major efficiency gains in Dynamics 365, yet many teams struggle to see real value. In most cases, the issue isn’t the technology. It’s missing foundations that prevent automation from working as intended.
This session takes a practical, beginner-friendly look at the core elements that must be in place before automation can succeed in D365. Through common finance and operations scenarios, we’ll examine how unstable data, inconsistent processes, and unclear ownership lead to automation failures and user frustration. This session is intended to help teams understand where to start, what to fix first, and how to set realistic expectations before scaling automation.
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