In the fast-paced world of enterprise software, the stability of Microsoft Dynamics 365 is non-negotiable. Yet, ensuring that stability through rigorous testing has traditionally been a complex, code-heavy endeavor, often creating a bottleneck for innovation. We sat down with Dominic Jainy, an IT professional with deep expertise in applying modern technologies to enterprise challenges, to discuss a paradigm shift in this space. Our conversation explores how a visual, no-code approach is revolutionizing Dynamics 365 quality assurance, delving into the practical implications of AI-powered maintenance, the dramatic efficiency gains teams are experiencing, and how this technology empowers business users to become guardians of their own critical workflows.
The article highlights that Leapwork’s “visual test flows” create a shared language. Could you share a specific anecdote where this visual approach helped business analysts and QA testers resolve a complex workflow issue in Dynamics 365, which might have been miscommunicated using traditional code snippets?
Absolutely, a perfect example comes to mind from a team working on a complex pricing and posting scenario in Dynamics 365 Finance. The business analyst had designed a multi-tiered discount logic, but the automated tests built by the QA team kept failing. When the QA engineer showed the analyst the code, it was like looking at a foreign language; the analyst couldn’t verify if their business logic was correctly translated. The back-and-forth was creating serious delays. Once they rebuilt the scenario using a visual flow, everything changed. They sat down together, looking at what was essentially a digital flowchart of the process. The analyst could literally point to a block on the screen and say, “Right there, that’s the step. The calculation needs to happen before the tax is applied, not after.” It was an immediate breakthrough. The visual flow became the single source of truth, bridging that communication gap instantly and resolving an issue in minutes that had previously burned hours of everyone’s time.
You cite an impressive statistic: a 97% reduction in testing time. Can you walk me through a typical data-dense ERP process, like a multi-entity consolidation, and explain which specific Leapwork features enable a team to achieve such a dramatic speed-up compared to manual or script-based methods?
That 97% figure might sound like a marketing line, but it’s rooted in the reality of eliminating massive amounts of manual, repetitive work. Take a multi-entity consolidation. Manually, a finance team member might spend three full days on this. It involves logging into a dozen different legal entities within Dynamics 365, running the same reports, exporting countless spreadsheets, and then painstakingly comparing the numbers to find discrepancies. It’s a grueling, error-prone process. With a platform like Leapwork, you build this flow once. You use a data-driven approach, where the test flow reads a list of entities from an external data source. It then loops through the entire process automatically—logging in, navigating, generating the report, and extracting the key values for each entity. The system then performs the validation and consolidation checks without any human intervention. That entire three-day ordeal can be compressed into a forty-minute, unattended test run. The speed-up comes from removing the human element of context switching, data entry, and manual comparison, allowing the machine to do what it does best: process complex, repetitive tasks at incredible speed.
The post mentions that AI helps with test maintenance by automatically adapting to UI changes. How exactly does this self-healing capability function when, for example, Microsoft updates a Dynamics 365 form? Could you provide a step-by-step example of how it prevents a test from breaking?
This is where the magic really happens, especially in an environment like Dynamics 365 that sees frequent updates. Let’s say Microsoft pushes an update that changes the underlying ID of a “Submit” button on a sales order form and moves it slightly to the right. A traditional, script-based test would fail immediately because its hardcoded locator is now invalid. The test stops, a bug report is filed, and a developer has to go in and manually fix the script. With AI-powered self-healing, the process is completely different. When the test flow runs, its intelligent locator strategy doesn’t just rely on one property. It understands the element in context—its text label (“Submit”), its proximity to other fields like “Total Amount,” and its functional attributes. So, when the test runs post-update, the AI first notices the original ID is missing. Instead of giving up, it scans the immediate area of the application for an element that matches the other stored properties. It quickly finds the button, determines with high confidence that this is the correct element despite the changes, and interacts with it successfully. It then automatically updates the test step with the new, more stable locator information and continues the test, often just leaving a note in the logs that it performed a self-heal. This turns a frantic, test-breaking emergency into a non-event.
Your content criticizes “tool sprawl” and positions Leapwork as a unified platform. For a company using Dynamics 365 with custom Power Platform apps, how would a tester build a single automated flow that validates a journey across both the UI and the underlying APIs?
This is a critical point because modern business processes are rarely confined to a single application. Imagine a journey that starts with a customer request logged in a custom Power App. A tester using Leapwork can build a single, continuous visual flow that mirrors this entire process. The flow would begin by interacting with the Power App’s user interface to create a new service ticket, just as a user would. Then, in the very next step within the same flow, it can switch gears and use a built-in block to make an API call to a backend system to verify that the customer’s service-level agreement was correctly retrieved. Finally, the flow pivots again, this time to the Dynamics 365 Customer Service UI. It will log in, navigate to the service module, and visually confirm that the new ticket from the Power App is present and has the correct status assigned based on that API data. This ability to weave together UI interactions and API calls in one seamless, visual canvas is what eliminates the tool chaos. You don’t have separate tools and scripts that need to be awkwardly stitched together; you have one holistic test that truly validates the end-to-end business journey.
Microsoft’s Mike Ehrenberg is quoted saying Leapwork lowers the “Total Cost of Ownership.” Beyond just scripting time, what are some of the most significant hidden costs associated with open-source tools that your platform eliminates for a Dynamics 365 user, and how does that typically impact their budget?
Mike’s point about TCO is something we see resonate deeply with finance and IT leaders. People hear “open-source” and think “free,” but they often overlook the enormous “open-source tax.” The most significant hidden cost is the constant maintenance of the framework itself. You often need highly skilled, expensive engineers not to test the application, but to build and patch the testing framework. Then there’s the cost of plugin management; when a browser updates or a library is deprecated, your entire test suite can break, and someone has to spend days troubleshooting compatibility issues. You also have hidden costs in training and onboarding. With a fragmented toolchain, every new team member needs to be trained on multiple complex systems. Leapwork eliminates this by providing a complete, managed ecosystem. We handle the updates, the browser drivers, and the integrations. This frees up your most valuable technical resources to focus on building better products and delivering value, not on maintaining test infrastructure. For a typical organization, this can translate into hundreds of thousands of dollars saved annually, shifting budget from internal tool maintenance to actual innovation.
The blog emphasizes that mid-market organizations often lack dedicated QA engineers. How does your codeless platform empower a non-technical ERP admin to confidently build and maintain automation for their custom extensions or ISV solutions? Please describe what their first few weeks using the tool would look like.
This is precisely where the democratization of testing becomes so powerful. An ERP admin, who understands the business processes inside and out but isn’t a coder, can become an automation champion. In their first few days with the platform, they wouldn’t be looking at a single line of code. They would use the visual editor, which feels more like creating a flowchart, to simply record their own actions as they navigate through a custom ISV solution they manage. By the end of the first week, they will have built their first complete, functional automated test—maybe for a critical workflow they are responsible for. It’s a huge confidence boost. In the following weeks, they’d start exploring more advanced concepts, like making their flows data-driven or creating reusable components. They might take that first flow and expand it to test dozens of different data variations. The platform empowers them to translate their deep business knowledge directly into a reliable automation safety net, ensuring their custom solutions work as expected after every Dynamics 365 update, without ever having to write a bug report or a ticket for a developer to build a test for them.
What is your forecast for test automation in the Dynamics 365 ecosystem?
I believe we’re at an inflection point. The complexity of the Dynamics 365 ecosystem is only going to accelerate with the deeper integration of AI like Copilot, the constant stream of monthly updates from Microsoft, and the proliferation of Power Platform customizations. The traditional, code-heavy approach to testing simply cannot keep pace with this rate of change; it’s too slow, too brittle, and requires a skill set that is already in short supply. My forecast is that codeless, AI-powered platforms will become the de facto standard for quality assurance in this space. Testing will shift from being a purely technical, end-of-cycle activity to a business-level conversation that happens continuously. Business analysts and ERP admins will be the ones building and maintaining a significant portion of the automation, ensuring that the technology always serves the business process, not the other way around. The future isn’t about writing more test scripts; it’s about empowering the people who know the business best to build resilience directly into their digital workflows.