Build, Buy, or Extend: The AI Decision Framework

Three paths to AI

The decision framework

Factor	Buy (Copilot as-is)	Extend (Copilot + plugins)	Build (Custom AI)
Time to deploy	Days to weeks	Weeks to months	Months to years
Cost	Licence only ($30/user/mo)	Licence + development	Significant dev + infrastructure
Control	Limited to built-in features	Moderate — custom within the platform	Full control over everything
Maintenance	Microsoft handles updates	Shared — Microsoft platform + your customisations	You own all maintenance
Technical skill needed	IT admin	Power users or developers	AI/ML engineers and developers
Best for	Standard M365 productivity	Organisation-specific workflows	Unique, competitive-advantage AI
Risk level	Low	Low to medium	Medium to high

When to Buy

Choose “buy” when:

• The use case is standard M365 productivity (drafting, summarising, analysing)
• Speed matters more than customisation
• You want the lowest risk and fastest ROI
• Your team lacks technical resources for customisation

When to Extend

Choose “extend” when:

• Copilot needs to access data outside Microsoft 365
• Users need Copilot to perform organisation-specific tasks
• You want to stay on the Copilot platform but add custom intelligence
• Your team has power users or developers who can build extensions

When to Build

Choose “build” when:

• No existing product meets the requirement
• The AI application is a competitive differentiator
• You need full control over the model, data pipeline, and user experience
• You have the engineering team and budget to develop and maintain it

💡 Exam tip: The exam favours the simplest sufficient approach

When the exam presents a scenario, apply this priority:

1. Can you Buy? If Copilot handles it out of the box, that’s the answer.
2. Can you Extend? If Copilot needs a plugin or connector, that’s next.
3. Must you Build? Only if neither Buy nor Extend works.

The exam penalises over-engineering. If a scenario describes a common productivity need, “build a custom solution in Foundry” is almost always the wrong answer.

Question

What does 'Extend' mean in the build, buy, or extend framework?

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Answer

Extend means adding custom capabilities to Copilot for M365 — plugins, Graph connectors, declarative agents, and API integrations. You stay on the Copilot platform but add organisation-specific intelligence. It's the middle ground between using Copilot as-is and building from scratch.

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The Copilot extensibility framework

When you choose to “extend,” Microsoft provides a structured framework:

Extension Type	What It Does	Who Builds It	Example
Declarative agents	Custom agents defined by instructions, knowledge, and skills	Power users or devs	An agent that answers questions about company policies using SharePoint docs
API plugins	Connect Copilot to external APIs and services	Developers	A plugin that lets Copilot query Salesforce CRM data
Graph connectors	Bring external data into the Microsoft 365 index	IT admins or devs	Connect ServiceNow tickets so they appear in Copilot search results
Custom engine agents	Agents powered by custom AI models (via Foundry) that surface in Copilot	AI engineers	A specialised industry compliance agent using a fine-tuned model
Message extensions	Interactive cards and forms within Copilot conversations	Developers	A booking extension that displays available meeting rooms

How extensions layer on top of Copilot

Think of it as a stack:

Layer	What It Provides
Copilot for M365 (base)	Built-in productivity in Word, Excel, Teams, Outlook
+ Graph connectors	External data becomes searchable alongside M365 data
+ Declarative agents	Custom agents with specific knowledge and instructions
+ API plugins	Real-time actions in external systems
+ Custom engine agents	Completely custom AI models surfaced within Copilot

Question

What are declarative agents in the Copilot extensibility framework?

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Answer

Declarative agents are custom agents defined by instructions, knowledge sources, and skills — without writing traditional code. You specify WHAT the agent should do and know, and the platform handles HOW. Power users can build them in Copilot Studio.

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Question

What is the difference between an API plugin and a Graph connector?

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Answer

A Graph connector brings external data INTO the Microsoft 365 index (making it searchable in Copilot). An API plugin lets Copilot CALL external systems in real-time to read data or take actions. Connectors are for search; plugins are for interaction.

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🏗️ Ravi’s decision tree for TechVantage

Ravi, CTO of TechVantage Solutions, has five AI needs. He applies the framework:

1. Help developers write documentation faster

• Decision: Buy — Copilot in Word handles this natively
• Reasoning: Standard productivity use case, no customisation needed

2. Let sales reps query the CRM from within Teams

• Decision: Extend — API plugin connecting Copilot to Salesforce
• Reasoning: Copilot can’t access Salesforce by default, but a plugin solves this

3. Make IT knowledge base searchable in Copilot

• Decision: Extend — Graph connector for the Confluence wiki
• Reasoning: Bring external docs into the M365 search index

4. Build an AI assistant that analyses code quality

• Decision: Build — Custom application using Foundry
• Reasoning: Highly specialised, competitive differentiator, no off-the-shelf solution

5. Create an onboarding agent that guides new hires through their first week

• Decision: Extend — Declarative agent in Copilot Studio
• Reasoning: Custom knowledge + structured workflow, but doesn’t need a custom model

ℹ️ Notice the pattern in Ravi's decisions

Ravi used all three strategies:

• 2 Buy decisions for standard productivity (documentation)
• 3 Extend decisions for organisation-specific needs (CRM, knowledge base, onboarding)
• 1 Build decision for a unique, competitive-advantage application (code quality AI)

This is the typical enterprise pattern. Most needs are met by Buy or Extend. Building is reserved for truly unique requirements.

Question

When should an organisation BUILD a custom AI solution instead of using Copilot?

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Answer

Build when: no existing product meets the requirement, the AI is a competitive differentiator, you need full control over the model and UX, and you have the engineering team and budget. Building is the most expensive and slowest option — reserve it for unique, high-value use cases.

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Knowledge Check

Ravi's IT team at TechVantage wants Copilot to answer questions using data stored in their ServiceNow instance. What is the best approach?

ABuy — Copilot can already access ServiceNowBBuild — create a custom AI application in Foundry that connects to ServiceNowCExtend — set up a Graph connector for ServiceNow so the data is searchable in CopilotDBuy — switch from ServiceNow to a Microsoft tool that Copilot supports natively

Check Answer

Knowledge Check

Ravi needs AI to help developers write documentation faster. They already use Word. What approach should he take?

ABuild a custom documentation AI using Azure OpenAIBExtend Copilot with a documentation pluginCBuy — deploy Copilot for M365, which includes AI in WordDBuy — purchase a third-party documentation AI tool

Check Answer

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🎬 Video coming soon

Next up: Microsoft Foundry: Your AI Platform — understand when and why to use Foundry for custom AI development.