For years, Dynamics 365 implementations have followed a familiar pattern. Large teams, multiple management layers, heavy governance, endless status reporting, and too many people positioned between the customer’s problem and the person actually solving it. Much of the commercial model has been built around managing complexity rather than removing it.

That model is now under pressure from two forces at the same time: AI, and Microsoft itself.

If you want to understand where Dynamics 365 delivery is heading, watch what Microsoft is doing internally. Across engineering, support, operations, and customer engagement, the company is rapidly embedding AI into execution. Development cycles are being compressed. Testing is increasingly automated. Knowledge retrieval is faster. Debugging is assisted by AI. Documentation is generated in minutes instead of days. Telemetry is analyzed faster and at greater scale. Decisions are moving closer to the people doing the work.

That matters because many Dynamics 365 partners are still selling delivery models that are slower, heavier, and more expensive than the organization producing the product.

In the Dynamics 365 world, this shift is especially visible. AI and MCP-style integrations now create practical leverage in areas that once required entire workstreams. Data migration can be accelerated through automated mapping, cleansing, and reconciliation logic. Testing can be generated and executed with far less manual effort. Training content can be tailored by role in hours. Functional workshops can be converted into requirements and backlog items instantly. Code scaffolding, troubleshooting, and technical analysis can be dramatically faster when handled by experienced people using AI properly.

This changes the economics of implementation teams.

The first cost category customers will challenge is not deep expertise. It is overhead. Administrative layers are always easiest to question because they are visible, expensive, and often disconnected from direct value creation. When AI can generate status reports instantly, coordinate information flows, summarize meetings, track actions, and surface risks automatically, the traditional argument for large support structures becomes weaker every quarter.

That means many Dynamics 365 partners need to ask themselves uncomfortable questions. How many roles exist today because they genuinely improve outcomes, and how many exist because the old delivery model required manual coordination? How many management layers help the customer, and how many simply help internal reporting lines? How much cost is being carried that a leaner competitor no longer needs?

The market will still pay premium rates for people who solve hard problems. Strong functional experts in Finance, Supply Chain, Commerce, Manufacturing, and Warehousing will remain valuable. Senior technical specialists who understand integrations, performance, security, extensions, and architecture will remain valuable. Trusted advisors who can guide transformation and make sound decisions will remain valuable.

But the space between those people and the customer is where the danger sits.

Inside Microsoft, the direction is already clear: fewer barriers, more automation, faster execution, tighter teams, and higher output per person. That same expectation will move into the Dynamics 365 ecosystem. Customers will increasingly compare partner proposals not only on rate cards, but on organizational efficiency. They will ask why one partner needs twelve people while another needs five. They will ask why progress requires so many meetings. They will ask why expensive coordination still exists in an AI-enabled world.

Some partners will adapt quickly. Others will try to defend structures built for a different era.

The uncomfortable truth is that AI may not remove the most valuable consultants first. It may remove the distance between those consultants and the customer.

That is the real Order 66 for Dynamics 365.

I did get help from AI to write this, but this is how the world works now.