For many organisations, this is incredibly exciting. Imagine having an AI-powered team member that can analyse customer data, review opportunities, generate reports, update systems and deliver business insights with minimal human intervention.

The opportunity is enormous. But so is the potential cost.

Unlike traditional software licensing, where organisations pay a fixed monthly fee per user, many Copilot agent scenarios introduce a consumption-based model. The more work AI performs, the more resources it consumes. 

“Understanding that relationship is critical to achieving a positive return on investment. The organisations that gain the most value from Copilot Cowork won’t necessarily be the ones using the most AI. They’ll be the ones applying AI to the right business processes, supported by quality data, strong governance and a clear understanding of what drives consumption” explains Robert Buck, Managing Director, Diamond IT.

The Shift from AI Assistant to Digital Labour

Most organisations are already familiar with AI assistants. 

| You ask a question. You receive an answer

| You request a summary. You get a summary

Copilot Cowork is designed to go much further.

Rather than simply responding to prompts, it can perform multi-step tasks, interact with systems, retrieve information from multiple sources, analyse data and deliver outcomes rather than answers.

| Instead of asking: “Summarise this customer meeting.”

| You might ask: “Review all customer interactions over the last six months, identify accounts at risk, generate a Power BI report, update relevant records and draft follow-up recommendations.”

That is a very different type of workload.

It’s also why Microsoft’s approach to billing is changing. As AI moves from generating content to performing work, consumption increasingly reflects the level of processing, retrieval and automation required.

“Copilot Cowork doesn’t charge for conversations. It charges for the work being performed” added Robert.

Understanding the Billing Model

One of the biggest misconceptions organisations have is assuming AI billing works like traditional Microsoft licensing. In reality, cost is influenced by the amount of work being performed.

While Microsoft’s licensing models will continue to evolve, three key factors tend to drive consumption.

1. Model Usage

Not all AI tasks are equal. A simple summarisation request requires substantially less processing than advanced reasoning, forecasting or large-scale analysis.

The more sophisticated the task, the more resources the AI model consumes.

2. Data Retrieval

Before Copilot Cowork can provide an answer or complete a task, it often needs to locate information. 

That could involve:

• Reading documents
• Searching SharePoint
• Reviewing emails
• Analysing meeting transcripts
• Accessing customer records
• Querying operational systems

The broader the search and the larger the dataset, the greater the consumption required.

3. Actions Performed

Many organisations want AI to do more than provide recommendations. They want it to act.

That might involve:

• Updating Dynamics 365
• Running Power Automate workflows
• Querying Dataverse
• Generating reports
• Creating documents
• Triggering business processes

Every action increases the amount of work being performed.

This doesn’t mean AI is expensive. It means organisations must think differently about cost management. The question becomes less about licence counts and more about business value.

Consumption-Based Billing Explained

Traditional Microsoft licences are generally charged per user, per month. Whether a user sends one email or one thousand emails, the licence cost remains the same.

Copilot Cowork introduces a different approach. In many scenarios, organisations are effectively paying for the amount of AI work performed. The more data that needs to be analysed, the more systems that need to be queried and the more actions the AI performs, the greater the consumption.

Think of it like cloud computing. Running a small workload may incur very little cost. Running a large workload that analyses thousands of records, generates reports and updates multiple business systems will consume more resources because more work is being performed on your behalf.

This doesn’t mean AI is expensive. It means organisations must think differently about cost management. The question becomes less about licence counts and more about business value.
In fact, some of the most valuable use cases are often those consuming the most resources because they’re replacing hours of manual effort. The key is ensuring the business value being generated exceeds the consumption cost.

“The goal isn’t to minimise consumption. The goal is to ensure the value created by AI exceeds the cost of the work being performed,” explains Robert.

Why Costs Can Escalate Quickly

Let’s compare three common examples.

1. Low-Complexity Task

“Summarise this proposal.”

The AI reviews a single document and returns a concise summary.

Relatively low consumption.

2. Medium-Complexity Task

“Review my customer meetings from the past month and identify opportunities.”

The AI retrieves multiple data sources, analyses interactions and produces recommendations.

Moderate consumption.

3. High-Complexity Task

“Analyse all customer opportunities, compare against historical performance, create a Power BI dashboard, identify accounts at risk, update Dynamics records and draft an executive summary.”

This workload involves data retrieval, reasoning, reporting, system integration and business process execution.

It consumes considerably more resources.

However, this isn’t necessarily a problem. In many cases, it represents exceptional value.

After all, if an AI agent can perform work that might otherwise take an employee several hours, or even days, to complete, the return on investment may still be compelling.

The objective shouldn’t be minimising consumption. The objective should be maximising business value.

The most expensive AI task isn’t always the least efficient. Sometimes it’s replacing hours of manual effort.

Governance: The Conversation Most Organisations Haven’t Had Yet

One of the most interesting themes emerging from Microsoft’s partner ecosystem is that organisations are being encouraged to treat Copilot Cowork more like a cloud consumption service than a traditional software licence.

Before activating Cowork, business leaders should consider:

• What spending policies will be implemented.
• What reporting is required and who will receive it.
• What cost controls and spending limits will be configured.
• Who owns consumption monitoring and governance.
• How unexpected costs will be managed.

“This is a different conversation to simply assigning a Microsoft 365 licence. It requires executive ownership, clear accountability and transparency around how AI services are being consumed” guided Gavin Hall, Business Technology Consultant, Diamond IT.

Importantly, organisations should not assume unexpected consumption costs will automatically be waived. Just as with Azure, success often depends on establishing governance before adoption, not after.

At Diamond IT, we recommend treating Copilot Cowork the same way organisations manage other consumption-based cloud services: establish ownership, define acceptable spending thresholds, monitor usage patterns and regularly review business outcomes against costs.

AI success is rarely a technology challenge. More often, it’s a governance and cost management challenge.

Where Copilot Cowork Delivers the Greatest Value

Many businesses will initially use Copilot Cowork for general productivity tasks. That delivers some value.

However, the real opportunity often emerges when AI is connected to structured business systems. This is where organisations are likely to see the strongest return on investment.

For organisations already using Microsoft’s business applications ecosystem, Copilot Cowork becomes significantly more powerful.

Microsoft Dataverse provides a structured data platform containing business-critical information and relationships between records. Rather than searching through disconnected files, emails and spreadsheets, Copilot can work with trusted business data.

That may include:

• Customers
• Opportunities
• Projects
• Service requests
• Assets
• Contracts
• Financial information

Because the data is structured, AI can analyse it more effectively and deliver more consistent outcomes. This becomes even more powerful when combined with Dynamics 365 and Power BI.

Consider a sales team managing hundreds of opportunities. Instead of manually reviewing records, analysing trends and building reports, Copilot Cowork could identify opportunities at risk, recommend next actions, surface key insights and prepare management summaries.

Likewise, service teams could analyse ageing requests, identify recurring issues and highlight areas requiring attention. Power BI adds another layer of value.

Most organisations have access to data. Far fewer have the time or resources to consistently turn that data into insight.

Imagine asking:

| Identify declining customer segments, explain the likely causes and recommend corrective actions.

Or:

| Analyse profitability trends over the past twelve months and highlight areas requiring management attention.

Rather than simply creating reports, AI begins contributing to business analysis and decision-making. The result isn’t just visibility. It’s actionable intelligence.

“When connected to Dataverse, Dynamics 365 and Power BI, Copilot Cowork stops being a productivity tool and starts becoming a business capability” added Rob.

Copilot Cowork Isn’t Just AI, It’s Digital Labour

Microsoft Copilot Cowork represents one of the most significant advances in workplace technology since the introduction of cloud computing. It has the potential to automate complex processes, augment teams, unlock new insights and reduce the administrative burden that consumes so much of the modern workday.

But organisations need to enter with realistic expectations.

| Copilot Cowork is powerful. It is practical. And in the wrong scenarios, it can be expensive.

The businesses that succeed won’t simply deploy AI because they can. They’ll identify high-value business processes, connect AI to quality data, establish clear governance, monitor consumption carefully and focus relentlessly on business outcomes. Particularly for organisations already invested in Dataverse, Dynamics 365 and Power BI, the opportunity is substantial.

The future of AI isn’t just about generating answers.

It’s about getting work done.

And that’s where Copilot Cowork may have its greatest impact.

At Diamond IT, we help organisations move beyond the hype and focus on practical outcomes. From readiness assessments and governance frameworks through to Dynamics 365, Dataverse, Power Platform and Power BI integration, we work with businesses to identify where AI can create genuine operational and commercial impact.

Whether you’re just starting your AI journey or looking to extend your existing Microsoft investment, our team can help you implement Copilot Cowork in a way that’s secure, scalable and commercially sustainable.

| The goal isn’t simply to use more AI. The goal is to use AI where it creates measurable business value.