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In this article:
Why the cycle is so hard to compress What this costs Why this is a structural problem not an execution problem
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The BC Implementation Opportunity Nobody Is Talking About Yet

18.08.2026
AI

Every BC implementation partner knows the pattern: margin absorbed, timelines extended, client expectations managed downward. The opportunity to change that is arriving, and most of the ecosystem has not yet looked up from the current process long enough to see it.

There is a process at the centre of every Business Central implementation that has remained essentially unchanged since the platform was first deployed at scale. A client describes a business requirement. A functional consultant interprets it. A developer translates the interpretation into AL code. Someone tests the result manually. Feedback comes back. The cycle repeats.

The number of tools available to support this process has grown considerably. The process itself has not.

The requirement-to-production cycle in BC customisation is still, at its core, a handmade process. Each extension is built from scratch or adapted from a prior project. Each test is run by a person following a test script. Each deployment is managed by a developer who understands the specific configuration of this client’s BC environment.

This is not a criticism of the people doing the work. BC implementation teams are, in many cases, operating at the limit of what the current process allows. The problem is the process, and the process has structural characteristics that make it resistant to improvement within its existing design.

Why the cycle is so hard to compress

The requirement-to-production cycle in BC is long for reasons that are interconnected and mutually reinforcing.

The first is the translation problem. Business requirements are expressed in operational language. The person describing the requirement understands what the business needs, but not necessarily how BC’s data model, permission architecture, or extension framework will accommodate it. The developer understands the implementation constraints, but not necessarily the business context that makes one approach preferable to another. The functional consultant sits between them, translating in both directions. This translation layer adds time, introduces interpretation errors, and creates a feedback loop that is difficult to short-circuit.

The second is the testing problem. Manual testing of BC customisations is time-consuming, inconsistent, and incomplete. Test scripts capture the scenarios the tester anticipates. They do not capture the scenarios the tester did not think to test, which are precisely the scenarios most likely to surface as production issues after go-live. Automated testing in BC environments exists but is not yet standard practice across the partner ecosystem, and implementing it adds a layer of upfront investment that many projects cannot absorb.

The third is the knowledge problem. Every BC implementation accumulates environment-specific knowledge, configuration decisions made early in the project, integrations added at different points, customisations that interact with each other in ways that are not always fully documented. This knowledge lives primarily in the heads of the people who built the system. When those people are not available, or when a new requirement touches a part of the environment they did not build, the investigation work required before a new extension can be safely developed adds time that the project timeline did not anticipate.

What this costs

The cost of the handmade build process is distributed across three places.

Partners absorb it in margin. Projects that were scoped on the assumption of a linear, well-understood build process encounter translation delays, testing rework, and knowledge investigation work that was not in the estimate. The additional effort comes out of the project margin rather than the client’s budget, because raising a change request for work that should have been part of the original scope is a conversation nobody wants to have.

Clients absorb it in timeline. The requirement that was described in week three of the project is tested in week eleven. By week eleven, the business context has shifted. The person who described the requirement has moved to a different role. The urgency that justified the customisation has either intensified or resolved without the system’s involvement.

The relationship absorbs it in trust. A client who expected a three-month implementation and experienced a five-month one, with a final result that only partially matches what was described, does not approach the next project with the same confidence. The gap between what was promised and what was delivered is the gap where partner-client relationships erode.

Why this is a structural problem, not an execution problem

The instinctive response to the build problem is to improve execution within the existing process. Better project management. Better requirements documentation. More experienced developers. More thorough testing.

These improvements help at the margin. They do not change the structural characteristics of the process. The translation layer is still there. The manual testing is still there. The environment-specific knowledge is still concentrated in individuals rather than systematically captured.

The build problem in Business Central is not a problem that can be solved by doing the same thing better. It requires a different approach to how requirements become extensions, how extensions are tested, and how environment knowledge is captured and reused.

That different approach is beginning to arrive in the Dynamics ecosystem. Microsoft’s announcement of Project MIA at DynamicsMinds in May 2026, aimed initially at F&SCM partners, signals that the ecosystem’s direction of travel is toward AI-assisted implementation. What that means for BC, and on what timeline, has not yet been confirmed. What is clear is that the build problem is recognised at the highest level of the ecosystem, and that the current process is not the destination.

The partners and clients who understand the structural nature of the problem now will be better positioned to evaluate and adopt what comes next. The ones who attribute it to execution will keep trying to fix the wrong thing.

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Related blog articles.

27.03.2026 AI

Bluefort Launches Two AI Agents for Dynamics 365 Business Central

Bluefort has released two AI-powered agents for Microsoft Dynamics 365 Business Central, now available on Microsoft AppSource. The tools, the LISA Business Contract Agent and the Due Diligence Sentiment Agent, are designed to move AI beyond a peripheral feature and into the core of day-to-day ERP operations. The launch reflects a growing trend among business software vendors: rather than offering AI as a separate dashboard or add-on, embedding intelligence directly into the workflows where decisions and transactions actually happen. Automating the Contract Lifecycle The LISA Business Contract Agent targets one of the more time-consuming pain points in subscription-based businesses: translating customer communications into commercial actions. The agent reads inbound customer emails and attachments, autonomously generating sales quotes, sales orders, and contract updates within Business Central, including handling upgrades, cancellations, pro-rata adjustments, and future-dated changes. For high-volume subscription businesses where manual contract entry doesn't scale, this removes the layer of processing that typically sits between a customer request and its execution in the system. Key capabilities include: Email and attachment interpretation: reads inbound communications in full and converts them into structured sales quotes, orders, and contract actions without manual input Full subscription lifecycle support: handles add-ons, one-time charges, upgrades, removals, cancellations, pro-rata adjustments, and future-dated changes Pricing governance preserved: all pricing and discount logic remains controlled by Business Central; the agent assists execution but never overrides approved policy Governed automation: invoicing is only triggered under predefined conditions, with non-subscription items remaining under standard ERP control End-to-end auditability: every action is traceable back to the originating email through Copilot task logs and sales order records The pricing governance point matters. Organizations nervous about AI acting outside defined rules can configure the agent knowing their commercial policy stays intact, reducing the risk of billing errors, disputes, and credit notes downstream. Due Diligence Gets an AI Layer The Due Diligence Sentiment Agent, Bluefort's first agent built natively in Microsoft's AL language, performs automated sentiment analysis on customers and vendors, pulling exclusively from publicly available web sources to generate a risk score between 1 and 10, with citations included for transparency. Key capabilities include: Automated sentiment analysis: evaluates public web data on customers and vendors to surface qualitative risk signals without manual research Scored risk output: produces a sentiment score from 1 to 10, giving teams a consistent, comparable benchmark across counterparties Public data only: the agent draws exclusively from information available on the open web, with no access to private or proprietary data sources Source citation: every score is backed by cited sources, allowing teams to validate findings and dig deeper where needed Native ERP integration: runs entirely within Business Central, eliminating the need to switch between external research tools and internal systems Due diligence has traditionally lived outside ERP systems, requiring analysts to manually gather information across multiple platforms before making a judgment. By bringing that process inside Business Central, Bluefort is betting that finance teams will act faster, and more consistently, when risk signals surface within the same environment they already work in. Bluefort has indicated the agent is an early-stage release, with the company actively seeking user feedback to shape its development, suggesting further capabilities are on the roadmap. A Bet on Agentic ERP The two agents serve different functions, one executes, the other informs, but together they point to a broader strategic direction for Bluefort: positioning AI not as a standalone capability, but as an operational layer woven into Business Central itself. For subscription businesses in particular, the combination is meaningful. The Contract Agent reduces the overhead of processing recurring revenue operations at scale, while the Due Diligence Agent surfaces vendor and customer risk before it becomes a financial problem. Used together, they address both sides of the commercial relationship, execution and evaluation, without leaving the ERP environment. Both agents are available now on Microsoft AppSource. LISA Business – Contract Agent Due Diligence Sentiment Agent

Bluefort is the Microsoft Cloud Partner and Authority with core competence in Subscription Management and Recurring Revenue automation for SMBs and Enterprise Business.

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