CIO Playbook: Adopting Microsoft 365 Copilot and AI Services

CIO Playbook: Adopting Microsoft 365 Copilot and AI Services

Generative AI is rapidly transforming workplace productivity. Microsoft’s Copilot suite – led by Microsoft 365 Copilot – promises to automate content creation, summarize information, and act as an intelligent assistant across everyday tools.

As a CIO (and licensing expert), you must navigate Copilot’s licensing model, evaluate its costs vs. benefits, and plan for strategic adoption.

This playbook provides a comprehensive guide to Microsoft 365 Copilot and related AI services from a licensing and ROI perspective, with actionable recommendations for IT and finance leaders.

Microsoft 365 Copilot Licensing Model

Microsoft 365 Copilot is an AI assistant add-on for Microsoft’s productivity cloud. Key points about its licensing include:

• Add-On License & Pricing: Copilot is licensed as a separate add-on for eligible Microsoft 365 subscribers. It costs $30 per user, per month (with an annual commitment) for businesses and enterprises. (Microsoft offers a slight discount foran annual payment upfront.) Each licensed user can use Copilot across Word, Excel, PowerPoint, Outlook, Teams, and more within their tenant. There is currently no free trial of Copilot’s full features.
• Prerequisites (Base License Eligibility): To purchase Microsoft 365 Copilot, a user must already have a qualifying Microsoft 365 or Office 365 plan. Eligible plans include Enterprise subscriptions (Microsoft 365 E3 or E5, Office 365 E1/E3/E5, as well as F and G series for frontline and government), Business plans (Microsoft 365 Business Basic, Standard, or Premium), and even standalone M365 Apps or certain component licenses (Exchange/OneDrive/SharePoint plans)​. In other words, most commercial Microsoft 365 subscribers – from SMB to enterprise – are covered as long as they have a modern M365/O365 subscription. (Notably, consumer/home Microsoft 365 plans are not eligible for the $30 Copilot add-on – Copilot is targeted at organizational use.)
• How to Buy: Initially, Copilot was available only to enterprises via an Enterprise Agreement (with a 300-seat minimum). Now, Microsoft has opened availability through Cloud Solution Provider (CSP) channels with no minimum seat requirement, allowing even small organizations or single users to subscribe​. Licenses are generally sold on annual terms (you can pay monthly or annually, but an annual commitment is required). At launch, Microsoft did not offer standard volume discounts on Copilot – the $30/user/month rate applied uniformly, even to large EA customers. Over time, enterprise customers may negotiate custom terms, but plan budgets assuming the full rate.
• No Bundled Inclusion (Yet): Copilot is not included in any existing E3/E5 bundle by default – it’s always an add-on cost. Whatever your organization already spends on Microsoft 365 licensing, Copilot comes on top of that. (For example, if E3 costs ~$36 user/month, adding Copilot brings it to ~$66 for that user.) Microsoft may introduce new bundles in the future (some speculate about a potential “M365 E7” SKU that includes Copilot), but currently an all-inclusive plan does not exist​. Be prepared for Copilot to remain a standalone line item in licensing costs for the foreseeable future.
• Free “Copilot Chat” vs. Paid Copilot: Microsoft 365 customers might notice a free AI chat feature available (formerly Bing Chat Enterprise, now sometimes just called Copilot (free) or Copilot Chat). This free service is included with many business plans and provides secure, browser-based generative AI chat using web data and your organizational context. However, Copilot Chat is limited to Q&A style interactions. The paid Microsoft 365 Copilot license is what unlocks AI directly inside Office apps and Teams with deep integration to your business data via the Microsoft Graph. The paid Copilot also offers enterprise-grade data protection, access to organization-specific context, and features like meeting recap in Teams – none of which the free tier provides​. It’s important to recognize this distinction when justifying the cost: the $30 Copilot delivers far richer capabilities than the basic free AI chat.

Licensing Summary: In short, Microsoft 365 Copilot requires an existing Microsoft 365 subscription and comes at a premium $30/user/month price point. It is sold as an add-on (no matter how large or small your organization) and currently must be budgeted separately from your standard Microsoft 365 license costs.

All users must have a qualifying base license; there is no “Copilot-only” user license for those without Microsoft 365. (Microsoft does offer a separate Copilot Pro subscription for individuals, discussed later, but that is distinct from the enterprise Copilot.) CIOs should ensure their organization’s Microsoft licensing is up-to-date (e.g. consider upgrading any users on older standalone Office licenses or unqualified plans) so that everyone who needs Copilot is eligible to receive it.

Example: A company with 500 users all on Microsoft 365 E5 would pay an additional $30 * 500 = $15,000 per month (=$180K/year) to license Copilot for all employees (assuming no discounts). If only a subset of, say, 100 key users are given Copilot, the incremental cost is $3,000 per month. We’ll discuss strategies for phasing adoption and targeting high-ROI users in the budgeting and recommendations sections below.

Budgeting and Cost Planning for Copilot Adoption

Adopting generative AI in Microsoft 365 requires careful budgeting. Below are key considerations and strategies for planning the cost:

• Assess Who Should Get Copilot: You do not need to license every user on day one. In fact, a common strategy is to start with a pilot group or specific departments. Identify users or roles that will benefit most – for example, content creators, analysts, developers, or executives who deal with information overload. By rolling out to a subset (e.g. 5–10% of users) first, you contain initial costs and can gauge value before wider deployment​. This phased approach lets you align spending with proven impact.
• Calculate Total Cost of Ownership: Besides the per-user Copilot fee, consider ancillary costs. For instance:
  • Annual License Commit: Remember that $30/user is an annual commitment (even if billed monthly). Ensure your budget owners understand this is a recurring cost of $360 per user/year (list price).
  • Prerequisite Licensing: If some employees only have basic email or older Office licenses, you might need to upgrade them to a Microsoft 365 plan before adding Copilot. The base Microsoft 365 E3/E5 or Business Premium licenses have their costs ($.X per user). Include those in your cost projections.
  • Support & Training: Allocate resources for training users to effectively use Copilot (possibly leveraging Microsoft’s adoption materials). While Microsoft 365 Copilot is user-friendly, some upskilling will help maximize ROI. Training costs (or time) are an “investment” needed to realize the value of the Copilot licenses.
  • Technical Readiness: Ensure your IT environment meets requirements (e.g. using latest Office apps, enabling required services). While these may not have direct costs, they could involve IT effort. (For example, enabling the new Teams client for Copilot features, or configuring Microsoft Entra ID settings as per Copilot guidance.)
• Volume Discounts & Negotiation: Microsoft initially set a flat $30/user with no standard discounts, even for large enterprises​. This means you should budget at list price. However, in enterprise negotiations (EA true-ups or CSP renewals), it’s worth discussing Copilot pricing with Microsoft or your licensing partner. Some organizations have negotiated step discounts (e.g. a lower price in Year 1 that escalates in later years) or other incentives​. If you’re committing to a large number of Copilot seats, prepare a negotiation strategy:
  • Engage Microsoft early, expressing interest but citing budget constraints and uncertain ROI initially.
  • Consider asking for a phased ramp cost (e.g. $20 in first year, $25 in second, $30 in third) or some promo credits, especially if you’re a strategic customer.
  • However, be cautious: any first-year deal you get might not carry over at renewal – Microsoft could hold firm on $30 later​. Aim for a sustainable deal, not just a short-term win.
  • Important: Do not assume Copilot will be discounted as deeply as other Microsoft products. Microsoft knows Copilot’s value is high and is positioning it as premium. Budget for the worst-case (no discount) and treat any concession as a bonus.
• Annual Budgeting & License Management: Given Copilot’s add-on nature, build a separate line item in your IT budget for generative AI. Track this spend distinctly. You might even create an internal cost center or project code for “Copilot & AI initiatives” to monitor expenditure. This helps in evaluating ROI later. Also plan for some growth in usage: if the pilot is successful, you may expand licenses in subsequent quarters – ensure the budget can accommodate scaling to more users. Likewise, have a off-boarding plan: if a user leaves or a department isn’t seeing value, licenses can (and should) be reallocated or reduced at renewal to avoid wastage.
• Comparing Alternatives: In budgeting discussions, leadership might ask “Why not use free ChatGPT or cheaper tools?” Be ready to explain that Microsoft 365 Copilot is enterprise-grade – it has access to your internal documents (unlike public chatbots), keeps data within your tenant (no data leaves to public services), and integrates with tools employees already use. These benefits justify its cost. However, also consider the mix of tools: for some basic use cases, the free Copilot Chat (or existing automation tools) might suffice. You could save Copilot licenses for the more advanced, high-value use cases. Budgeting for AI is about optimizing spend: use the right tool level for each scenario (free vs. paid) and avoid paying $30 for users who won’t fully utilize the capabilities.
• Long-Term Planning: Generative AI in Microsoft 365 is likely to evolve. When forecasting 2-3 years out, consider that Microsoft might bundle Copilot differently or adjust pricing (for example, if adoption is slower or competitors cut prices). Maintain flexibility in your agreements where possible. If you’re signing a multi-year volume license agreement now, try to include options to add Copilot later at predetermined rates, or at least avoid clauses that lock you out of new bundles. The goal is to future-proof your budget so you can adapt if an “M365 E7 with Copilot” or similar offering appears. (No one wants to over-pay for an add-on if a year later it’s included in a suite you already own.)

Tip: It’s helpful to run a “Copilot cost scenario” for leadership: e.g., “If we give Copilot to 25% of employees who are client-facing and estimate it saves each ~5 hours/month of work, the cost will be $X and the productivity value gained is $Y – yielding a net benefit.” This kind of model ties budgeting to ROI, which we’ll cover next.

Evaluating ROI of Copilot and AI Productivity Tools

Investing in AI assistants should ultimately improve productivity and business outcomes. CIOs must evaluate the return on investment (ROI) of Microsoft 365 Copilot (and related tools) to justify the cost and to refine deployment.

Here’s how to approach ROI analysis and maximize value:

1. Identify Key Productivity Metrics: Determine which workflows Copilot will impact and define how to measure improvement. Examples:

• Time savings: Copilot can draft documents, emails, or reports faster than employees doing it manually. Track how much time users report saving on these tasks. For instance, early user studies found employees spent 79% less time on email triage and 81% less time searching for information when using Copilot-like tools​. These time savings can be translated into monetary value (hours saved * average hourly salary).
• Output quality or volume: Does Copilot enable better quality outputs or more volume (e.g. more sales proposals generated per week, or more insights analyzed from data)? Collect feedback from teams – e.g., “Copilot helped us produce a client presentation in 1 day instead of 3, and it was more thorough.”
• Employee focus on high-value work: By automating drudgery (like formatting slides or summarizing meeting notes), employees can spend more time on strategic tasks. Survey managers on whether Copilot is freeing their teams to focus on higher-value activities.

2. Use Microsoft’s Analytics and Tools: Microsoft 365 Copilot comes with a built-in adoption and impact dashboard for admins, which can provide metrics on Copilot usage within your organization (e.g. number of Copilot prompts, which apps are used most, etc.)​. Leverage these stats. For example, if you see heavy usage in Excel Copilot, you might infer it’s helping with data analysis tasks. Microsoft’s dashboard might also offer “suggested ROI” metrics (Microsoft has hinted at tools to quantify Copilot’s impact). Utilize these to supplement your measurements.

3. Gather User Feedback and Anecdotes: Numbers are important, but so are stories. Collect qualitative feedback from Copilot users:

• Did Copilot help them meet a deadline they would have missed?
• Did it enable a project or proposal that wouldn’t have been possible otherwise?
• Are there errors avoided or insights gained thanks to AI assistance?
  Positive anecdotes (e.g. “The marketing team used Copilot to draft a campaign outline in hours – something that used to take days”) can illustrate value beyond what pure metrics show.

4. Quantify Business Outcomes: Translate productivity gains into business outcomes whenever possible:

• Faster document creation could mean faster sales cycles (getting proposals to clients sooner, potentially winning deals).
• Better analysis could lead to cost savings (finding inefficiencies or opportunities that humans missed).
• Time saved in meetings (Copilot summarizing meetings, generating minutes) might allow employees to handle more client engagements per week, impacting revenue.

For example, a recent Microsoft-commissioned study on Copilot in SMBs found a 6% increase in net revenue and 20% reduction in operating costs on average for companies using Copilot, contributing to an ROI range of 132% up to 353%​. While each organization’s results will vary, these figures demonstrate that effective use of Copilot can more than pay for itself.

5. Account for Intangibles: Some benefits are hard dollars, others are softer but still important:

• Employee Satisfaction: Eliminating tedious work with AI can boost morale. Happier employees are more productive and less likely to leave. (The SMB study noted an ~18% increase in employee satisfaction and 11–20% reduction in attrition for Copilot adopters.) Reduced turnover saves hiring and training costs – part of ROI.
• Innovation and Agility: With Copilot taking over routine tasks, teams have more mental bandwidth for creativity and strategic thinking. This can lead to new ideas, products, or improvements that drive future revenue. It’s tricky to measure, but executives will appreciate if you highlight this potential value-add of AI.
• Customer Experience: In roles like sales or support (if using Copilot in communications), faster responses or more personalized documents can improve customer satisfaction, indirectly affecting retention and sales. Gather any customer feedback that ties to use of AI assistance.

6. Compare Against the Investment: Once you have data on time saved, output gains, and any financial impacts, tally the “annual benefit” and compare it to the annual cost of Copilot licenses. For example:

• If 100 users have Copilot ($30 * 100 * 12 = $36,000/year cost) and each saves ~5 hours per month that they redirect to productive work, that’s 6,000 hours/year reallocated. If their average fully-loaded salary is $50/hour, that’s $300,000 worth of productivity – an ROI of roughly 733%. Even if only a fraction of those hours translate to bottom-line impact, the investment is justified.
• Alternatively, you might find one department saved $100k by automating a process with Copilot (by not having to hire extra analysts or consultants), directly offsetting the license cost.

7. Evaluate Continually: Make ROI evaluation an ongoing process. After the pilot phase, decide if results warrant expanding licenses. Set targets for the next phase (e.g. “We expect another 10% productivity gain in Documentation tasks by rolling Copilot to Technical Writers team”). Also watch for diminishing returns – it might be that the first 100 users yield huge gains (low-hanging fruit) but the next 100 have a smaller impact. Use that insight to prioritize who really needs Copilot.

8. Leverage Other AI Tool ROI: Microsoft 365 Copilot is one part of the AI toolset. If you adopt GitHub Copilot or Dynamics 365 Copilot (discussed next), include their benefits in your overall ROI analysis for AI. For instance, GitHub Copilot might significantly speed up software development – reducing time-to-market for a product is a concrete ROI that could dwarf the license cost. The same ROI principles (time saved, improved outcomes) apply to those tools. By presenting a holistic view of generative AI ROI, you can justify a broader AI budget, not just each tool in isolation.

In summary, to evaluate ROI: measure, measure, measure. Use a mix of hard data and user insights to build a case that generative AI tools are yielding productivity dividends.

Over time, these metrics will guide your decisions on scaling usage, adjusting training, or even discontinuing licenses that aren’t providing value. ROI analysis isn’t one-and-done; it’s a continuous improvement loop to ensure you’re getting the best bang for your buck from Copilot and related AI services.

GitHub Copilot (Developer AI Assistant)

In addition to Microsoft 365 Copilot, Microsoft offers GitHub Copilot – an AI pair-programmer that helps software developers by suggesting code and functions within their coding environment. CIOs should consider GitHub Copilot for any teams involved in software development or script writing, as it can significantly improve engineering productivity.

Key points on licensing and usage:

• What It Does: GitHub Copilot integrates with code editors (VS Code, Visual Studio, etc.) to auto-complete code, suggest snippets, and even generate whole functions based on natural language prompts. Developers can comment their intent (e.g. “// function to sort a list of orders by date”) and Copilot will suggest code to accomplish it. It’s powered by OpenAI models that have been trained on billions of lines of code. The benefit is accelerated development, fewer repetitive coding tasks, and assistance in exploring new APIs or languages.
• Pricing Tiers: GitHub Copilot is licensed separately from Microsoft 365 (it is tied to GitHub subscriptions). There are a few tiers:
  • Individual: $10 per user per month (or $100 per year) for a single developer’s use. This plan is for individuals or very small teams. Notably, GitHub offers it free to certain groups (verified students, teachers, and popular open-source project maintainers can get Copilot at no charge).
  • Business: $19 per user per month for organization use (this is often referred to as GitHub Copilot for Business). This tier includes administration features for organizations (like license management via GitHub Enterprise Cloud, policy controls, and the ability to enforce that code suggestions are public or open-source only to avoid compliance issues). Businesses can purchase this through GitHub Enterprise or directly on GitHub for teams.
  • Enterprise: GitHub has introduced an Enterprise tier (around $39 per user per month) that offers additional enterprise-grade capabilities and enhanced support​​. However, many companies will find the Business plan sufficient, and the Enterprise plan may be geared towards very large orgs with specific needs (like advanced security or on-premise solutions – note that Copilot does not currently support on-prem GitHub Server).
• Licensing Requirements: To use GitHub Copilot, each user needs a GitHub account with the appropriate Copilot subscription. For Business/Enterprise plans, your company likely needs a GitHub Enterprise Cloud or Teams setup to assign those licenses to developers. From the Microsoft licensing perspective, GitHub Copilot is not included in Microsoft 365 or Visual Studio subscriptions – it’s an add-on via GitHub. So even if your developers have MSDN or Visual Studio Enterprise, Copilot is separate. Budget accordingly for your development teams.
• Deployment Considerations: Enabling GitHub Copilot is straightforward, but CIOs should coordinate with software engineering leadership on:
  • Policy and Compliance: GitHub Copilot learns from public code, which raised questions about code licensing. There’s a setting in Copilot to block suggestions that match public code to mitigate any license compliance risk. Ensure your legal/compliance team is aware and comfortable with Copilot usage policies.
  • Security: Make sure using Copilot aligns with your secure development lifecycle. Copilot can sometimes suggest insecure code if the training data had it. Developers should still review and test all AI-generated code. Microsoft has been improving the model to avoid obvious vulnerabilities, but due diligence is key.
  • ROI for Copilot in Coding: Expect faster coding and possibly fewer errors. Metrics like “pull requests completed per week” or “lines of code written” might increase. Also, developer satisfaction can rise – it makes coding more fun and less menial. These factors can help justify the $19/user/month cost when presenting to finance. Given the high cost of developer time, even a modest productivity boost (e.g. 5-10%) easily outweighs Copilot’s fee.
• Integration with Azure DevOps/GitHub: GitHub Copilot works best with GitHub, but developers using Azure Repos (Azure DevOps) can still use Copilot in their editor for code. There’s no direct integration with Azure DevOps work items or CI, it’s focused on the coding experience. Microsoft is, however, starting to integrate AI assistance in other dev tools (like Azure DevOps has some backlog AI features preview). For now, GitHub Copilot is the primary code assistant and it’s under the GitHub product family.

Bottom Line: For organizations doing software development, GitHub Copilot can be a game-changer in productivity. The licensing is on a per-user basis ($10-$19/month for most) and can be managed via your GitHub Enterprise portal. It’s worth conducting a trial with a few developers (GitHub often offers a 30-day free trial for Copilot) to gauge the benefits.

Many companies have found that code quality and development speed improve, making the ROI very high – which is why Microsoft now includes Copilot as a highlight in its developer offerings. Ensure to include GitHub Copilot in your broader AI adoption budget and strategy, and coordinate its rollout with proper guidelines for use.

Dynamics 365 Copilot (CRM/ERP AI Features)

Microsoft is also embedding Copilot AI capabilities into its Dynamics 365 suite of business applications (CRM and ERP). Often branded as Dynamics 365 Copilot, these features aim to streamline business processes in sales, customer service, marketing, finance, and more by leveraging AI for insights and content generation. For CIOs, it’s important to understand how these capabilities are licensed, especially if your organization uses Dynamics 365 products:

• Copilot in Different Dynamics Apps: Unlike Microsoft 365 Copilot (which is a single add-on across multiple apps), Copilot in Dynamics 365 is more segmented. Microsoft has introduced AI features into individual Dynamics modules. For example:
  • Dynamics 365 Sales: AI can help draft sales emails, generate meeting summaries, and provide talking points for sales reps.
  • Dynamics 365 Customer Service: AI can assist support agents by drafting responses or summarizing cases.
  • Dynamics 365 Customer Insights/Marketing: AI can suggest audience segments or generate copy for campaigns.
  • Dynamics 365 Finance and Supply Chain: AI might help analyze financial trends or summarize reports.
  These are often collectively referred to as “Copilot” features within those products. Each module might have some Copilot functions included and others requiring additional licensing.
• Licensing Structure: Microsoft’s approach has been to include some basic AI features in existing Dynamics licenses (especially the high-end editions), while offering more advanced capabilities as add-ons. Two prominent add-ons as of 2024:
  • Microsoft 365 Copilot for Sales – despite the name, this is essentially a Dynamics 365 Sales AI add-on. It’s licensed per user (for sales team members) at roughly $50 per user per month​. This add-on includes the full Microsoft 365 Copilot functionality plus premium sales-specific AI features. (In effect, it bundles the $30 Copilot and adds $20 worth of sales AI extras, totaling ~$50.) Sales users who have this license get AI help not only in Dynamics 365 Sales, but also in Outlook and Teams for sales scenarios (e.g. drafting a reply to a client email, or summarizing a sales meeting in Teams). Note: A user must have a base Dynamics 365 Sales license (Enterprise or Premium) and a Microsoft 365 base license to use this add-on​.Microsoft 365 Copilot for Service – similarly, an add-on (~$50 per user/month, $600/year) for customer service agents that bundles the core Copilot plus advanced AI for customer service workflows​. It can integrate with Dynamics 365 Customer Service or other helpdesk systems to provide AI summaries, draft responses, and intelligent case wrap-ups. It also requires the agent to have the appropriate base licenses for Dynamics 365 and Microsoft 365.
  In both cases, Microsoft’s strategy is that these role-based Copilot add-ons (Sales, Service, etc.) include the standard Microsoft 365 Copilot. If you buy Copilot for Sales for a user, you do not need to also buy the $30 Copilot – it’s already in there​. This is an important budgeting point: if, say, a sales rep needs AI assistance, and you’re considering both M365 Copilot and D365 Sales Copilot, you can just buy the Sales Copilot license for that user and they’ll get everything (no need to double-pay).
• Included vs. Paid in Dynamics Licenses: Microsoft has indicated that some Copilot capabilities are included in Dynamics 365 Sales Enterprise and other top-tier plans at no extra cost​. For instance, standard AI features (like basic email summaries, or talking points) might be included in Sales Enterprise ($95 user/month license) and Sales Premium ($135 user/month) without the add-on. However, the premium Copilot experiences (the cutting-edge GPT-4 stuff and cross-application integration) typically require the add-on or at least Microsoft 365 Copilot. For example, Dynamics 365 Sales Premium users get a lot of AI out-of-the-box, but to activate the full Copilot for Sales integration, they need to have Microsoft 365 Copilot licensed as well​. This can be confusing: essentially, if you have Sales Premium, you already paid for some AI, so Microsoft only charges you the $30 M365 Copilot to unlock the rest; if you have a lower Sales license (or even Salesforce CRM), you can buy the $50 Copilot for Sales to get everything in one go.
• Other Dynamics Copilots: Microsoft has previewed or launched Copilot features in Dynamics 365 Finance, Dynamics 365 Supply Chain, Dynamics 365 Marketing, etc. So far, many of those seem included in the product or available during preview at no extra cost. But be prepared: as these AI features mature, Microsoft could introduce specific licensing or require Copilot add-ons for them. Always check the latest Dynamics 365 Licensing Guide for any AI feature licensing notes (Microsoft updates these documents as new capabilities like Copilot roll out).
• Value Proposition: For organizations using Dynamics 365, these Copilot features can drive significant efficiency:
  • Sales reps can shorten the sales cycle with AI-generated follow-ups and research.
  • Support agents resolve cases faster with AI-suggested answers and summaries.
  • Marketing teams spend less time drafting content and more time refining strategy.
    The $50/user/month add-ons might sound steep, but consider the roles: a salesperson or contact center agent’s productivity directly ties to revenue or customer satisfaction. If Copilot enables an agent to handle 10% more inquiries or a salesperson to close deals faster, the ROI is tangible. In budgeting, you might choose to license a subset of high-impact users (e.g. senior sales reps, or tier-2 support agents) with these advanced Copilot tools. Also, factor in that these users likely also need Microsoft 365 Copilot or at least Office apps access, which is often already in place.
• Licensing Example – Sales Team: Suppose you have a sales team with Dynamics 365 Sales Enterprise licenses. By default, they get some AI features (standard Copilot). If you want them to have the top-tier AI that, for example, generates full proposal drafts and does meeting recaps in Teams, you have two options:
  1. License each rep with Microsoft 365 Copilot ($30) and rely on the built-in AI in Sales Enterprise for basic features. (This gives them most Copilot functions except some specific Sales add-ons.)
  2. License each rep with Copilot for Sales ($50) which covers everything (including Microsoft 365 Copilot).
     You would compare cost vs benefit of those options. If the team heavily uses Outlook/Teams for sales, the Copilot for Sales add-on may justify its cost by boosting their overall workflow. If they primarily want help inside the CRM, maybe only the base is enough.

Action for CIOs: Review your current Dynamics 365 license landscape. Engage business owners (Sales VP, Service/Support Director, etc.) to identify pain points that Copilot could address. Microsoft often provides trials or demos of Dynamics Copilot features – use those to gauge the fit. In licensing terms, budget the add-on costs for targeted users in those departments if the value is clear.

Also, keep an eye on Microsoft’s announcements: the AI capabilities in Dynamics are evolving quickly, and licensing models might be adjusted (for example, Microsoft could decide to bundle some Copilot features into the base licenses in the future to drive adoption, or introduce new role-based Copilot packages like “Copilot for Finance”).

Lastly, ensure your IT and data teams consider the data access and security implications: Dynamics Copilot will use your CRM/ERP data in combination with AI models. Microsoft maintains that Copilot respects your data privacy and does not leak info between tenants.

Still, you should apply normal governance – for instance, restrict who can use Copilot if the underlying data is highly sensitive and ensure outputs are reviewed for accuracy. This governance piece ties into successful adoption, which in turn affects realized ROI.

Azure OpenAI Service (Custom AI via Azure)

While Microsoft 365 Copilot and the other copilots are packaged solutions, Azure OpenAI Service is Microsoft’s Azure cloud offering that gives organizations direct access to OpenAI’s advanced models (GPT-4, GPT-3.5, Codex, DALL-E, etc.) as APIs. It allows you to build custom AI applications or integrations tailored to your business.

From a CIO’s perspective, Azure OpenAI is relevant when you have needs that go beyond the out-of-the-box Copilot scenarios – for example, building a proprietary AI chatbot for your customer portal, or doing AI-driven data analysis on internal datasets.

Key points on Azure OpenAI and its licensing/cost model:

• Service Model: Azure OpenAI is offered as a cloud service in Azure, meaning you must have an Azure subscription to use it. Microsoft requires an application or approval process to gain access (to ensure responsible use), but many businesses are now eligible. Once enabled, you can deploy various AI models (like GPT-4) in Azure and call them via REST APIs or SDKs. Essentially, you’re renting the AI model’s processing power.
• Consumption-Based Pricing: Unlike Copilot’s per-user fee, Azure OpenAI is billed on a pay-as-you-go basis. You pay for the usage of the AI model, typically measured in number of tokens processed. Tokens are chunks of text (roughly 3/4 of a word each). For instance, you might pay a certain rate per 1,000 tokens input and output. The exact prices depend on the model:
  • GPT-4 is the most advanced and expensive (for example, on the order of ~$0.03–$0.06 per 1K tokens for input and a bit more for output; actual rates change as models evolve).GPT-3.5 (the model behind earlier ChatGPT versions) is cheaper (fractions of a cent per 1K tokens).There are also specialized models like Codex (for code) or image generation models, each with their own pricing.
  Azure OpenAI billing can be thought of like utility billing – similar to how you pay for Azure compute or storage by consumption. If no one uses the AI (no API calls made), you pay $0 that month. If you use it heavily, costs accumulate accordingly. This model gives flexibility (scales with usage) but also means you need to monitor and manage usage to control cost​.
• Cost Management: CIOs should ensure proper cost governance:
  • Set up budgets and alerts in Azure for the OpenAI resource to avoid unexpected bills.
  • Use rate limiting or quotas on your applications using the API, so one rogue script doesn’t burn through millions of tokens.
  • Understand the use-case: e.g., an internal app that summarizes lengthy documents for employees could use a lot of tokens with GPT-4 (costly). You might decide to use GPT-3.5 for that if the quality is acceptable, dramatically reducing cost.
  • Azure OpenAI allows fine-tuning models on your data and deploying them – which can have a fixed cost for training plus the usage cost. Include that in budgets if you plan to fine-tune custom models for better performance on your domain (e.g. training a model on your company’s manuals to better answer tech support questions).
• Comparing Azure OpenAI vs. Copilot Licensing: If your organization’s needs are fully met by Microsoft 365 Copilot and Dynamics/GitHub Copilots, you may not need to directly use Azure OpenAI at all. Microsoft 365 Copilot is essentially Microsoft using Azure OpenAI on your behalf (Microsoft runs GPT-4 on the backend and charges you a fixed fee for unlimited use). However, some organizations have requirements for custom AI solutions that Copilot doesn’t cover:
  • Example: You want an AI to read thousands of legal documents in your SharePoint and answer specific questions for your legal team. Microsoft 365 Copilot might not support such deep Q&A on a custom corpus (beyond what the Copilot Chat can do in limited fashion). Building a custom Azure OpenAI chatbot could be the answer.
  • Example: You want to integrate GPT-based analysis into a proprietary app (say, a customer-facing website that answers support FAQs). That’s not something Copilot provides; Azure OpenAI would allow that via API.
  In these cases, you are now dealing with usage-based costs vs. the flat per-user costs of Copilot. One isn’t strictly cheaper than the other – it depends on scale. A single heavy user of Azure OpenAI (making many large queries) could incur hundreds of dollars in usage, whereas the same user on a flat $30 Copilot can use it all day at no extra charge. Conversely, a light usage across many users might favor a consumption model. It’s a different calculus.
• Enterprise Agreements for Azure OpenAI: If your Azure spend is significant, you might have an Azure commitment (Azure Consumption Commitment, ACC). Azure OpenAI usage is just part of your Azure bill, so it can draw down from those pre-committed amounts. Microsoft also can do custom pricing or volume discounts for very large Azure OpenAI usages (if you’re, say, spending millions on AI, they will negotiate). As a CIO, loop in your cloud procurement team when scaling Azure OpenAI – ensure it falls under any discount agreements your organization has with Microsoft for Azure. Also note that Azure OpenAI usage in a tenant doesn’t automatically grant rights to Copilot, and vice versa – they’re separate. Copilot’s cost doesn’t include unlimited Azure OpenAI for other purposes; you’d pay separately for any custom use.
• Responsible AI and Security: When using Azure OpenAI, you are directly handling prompts and retrieving outputs, which might include sensitive data. Build guardrails: for instance, don’t feed raw confidential data into the service without understanding how it’s handled. (Azure OpenAI guarantees that your data is not used to train the public models and stays within your instance – an advantage over hitting OpenAI’s public API). Still, implement data protection measures, monitoring for misuse (like users asking the model for sensitive info it shouldn’t reveal). Microsoft provides guidelines and tools for responsible AI usage – adhere to them to mitigate risks.

When to use Azure OpenAI: If you foresee building custom AI capabilities beyond what Microsoft’s pre-built Copilots offer, plan a portion of your AI budget for Azure OpenAI. This could be experimental at first – perhaps set aside a small monthly budget for a pilot project. Some organizations create internal “AI Labs” that use Azure OpenAI to prototype new solutions (like intelligent assistants for specific processes).

The consumption model means cost can grow unpredictably, so keep pilots controlled until you understand usage patterns. Over time, you might operationalize some Azure OpenAI solutions (e.g. embed them into your products or internal systems). At that point, treat it as you would any Azure service in production: with capacity planning, cost optimization (like choosing the right model for the job), and continuous monitoring.

In summary, Azure OpenAI Service gives you ultimate flexibility to apply generative AI in ways Microsoft’s packaged Copilots might not. Its licensing is cloud consumption-based – essentially a utility model.

For CIOs, the focus should be on governance: ensure you have the right people (data scientists, developers) to build with it, the right controls to manage cost, and a clear understanding of the business value expected from any custom AI development you undertake.

Future Evolution of Microsoft’s AI Licensing Model

Microsoft’s AI licensing strategy is still in its early stages, and we can expect it to evolve in the coming years. As CIOs plan medium- to long-term, here are some potential changes and trends in Microsoft’s Copilot and AI licensing model to watch for:

• Bundling into Existing Plans: Today, Copilot is an add-on to E3/E5 rather than included. In the future, Microsoft might introduce a new top-tier subscription (often speculated as “M365 E7” or “E5+”) that bundles Copilot by default​. This would simplify licensing for customers willing to pay a premium for an all-inclusive package. If such a plan emerges, it could be attractive for enterprises planning to roll out AI to everyone. However, Microsoft will be cautious – bundling Copilot too soon could slow down its lucrative add-on sales. A compromise might be offering Copilot bundled into E5 for certain segments (education or nonprofit) or as a limited-time bundle to drive adoption.
• Adaptive or Usage-Based Pricing: Microsoft 365 Copilot is a flat per-user fee, but Microsoft might explore usage-based models in the future if that flat pricing becomes a barrier or if customer usage patterns vary widely. For instance, some customers might prefer a model where they pay per 100 Copilot queries or per hours of AI usage, which could be cheaper for light users. This hasn’t been announced for M365 Copilot, but other Copilots give clues: Security Copilot (Microsoft’s AI for cybersecurity) uses a consumption model based on “Security Compute Units” rather than per user​. This shows Microsoft is open to non-per-user pricing when it makes sense. It’s conceivable that if companies complain “$30 is too high for casual users,” Microsoft could introduce a lighter SKU or usage-based add-on for occasional use. Keep an eye on feedback in the market – Microsoft has adjusted product pricing before when adoption lagged (e.g. halving Power Platform per-user costs in 2022)​.
• Tiered Copilot Experiences: We already see a tiering with Copilot Chat (Free), Copilot Pro ($20), and Copilot for Microsoft 365 ($30). Microsoft may further stratify capabilities:
  • The free tier might get more features over time (to entice users into the ecosystem), but still limited to web/bing integration.
  • Copilot Pro (for individuals) is a new offering (launched in late 2023) aimed at Microsoft 365 Personal/Family subscribers and small businesses. For $20/user/month, Pro users get many Copilot features (like in Word, Excel, etc.) but not all enterprise-level integrations​. For example, Copilot Pro doesn’t include Teams meeting summaries or organizational data grounding via the Graph. Microsoft will likely expand Pro’s capabilities for solo users but maintain some gap so that enterprises still opt for the $30 full version. As a CIO, you might see very small subsidiaries or specific contractors opt for Copilot Pro if they aren’t under your main tenant, but generally Pro is a consumer/SOHO product.
  • We could envision Microsoft offering Copilot “lite” versions for certain roles. Perhaps a $10 add-on for frontline workers if they only need Copilot in Teams for brief summaries, or a specific Copilot bundle for education at a lower price/student. These aren’t reality yet, but Microsoft often creates pricing variations for different segments once a product matures.
• Increased Bundling of AI in Apps: Microsoft might bundle some AI features directly into product licenses instead of as separate Copilot. For instance, some AI features in Dynamics 365 or Power Platform might become included components (Microsoft has already included basic AI assist in Windows 11 “Copilot” for consumers at no extra cost). If competitors (like Google Workspace’s AI or others) start bundling at no extra charge, Microsoft could respond similarly to stay competitive for those features. Already, we see that Teams Premium (a paid upgrade for Teams) includes some AI-generated meeting notes features. Over time, those might just roll into Teams or Copilot proper. As CIOs, we should monitor Microsoft’s licensing guides each year – AI capabilities might shift from “add-on” to “included” as products evolve.
• Cross-Product Discounts or Bundles: As the Copilot family grows (Microsoft 365, GitHub, Dynamics, Security, etc.), Microsoft could introduce bundled pricing for multiple Copilots. For example, a company using both Microsoft 365 Copilot and Dynamics Copilot might get a better rate on one of them as part of a promotion. Or Microsoft could have an “AI bundle” SKU that gives access to Copilot across Microsoft 365, Dynamics 365, and Security at a combined lower price than buying all separately. Nothing official yet, but from a licensing expert perspective, this kind of bundling often happens to encourage broader adoption (similar to how Microsoft 365 bundles Office, Windows, EMS, etc.). If your organization is adopting AI broadly, engage your Microsoft rep about multi-product deals – even if there’s no public bundle, they might craft a custom arrangement.
• Expanded Copilot Offerings: Microsoft is continuously adding AI to new domains:
  • Microsoft Security Copilot (for SOC teams) – currently in preview, likely to be a separate per-user or per-capacity license.Microsoft Copilot Studio – a tool for building your
  Copilots (custom AI bots) which may have its licensing (perhaps included with the main Copilot or as a separate tool). Stoneridge’s guide suggests a separate “Copilot Studio” user license is needed to create custom copilots.
  • Industry Copilots – e.g., a Copilot for Healthcare or Copilot for Supply Chain might emerge, tailored with domain-specific models, possibly as add-ons.
  The point is, the portfolio of Copilot-branded AI services will grow, and each may have a distinct licensing approach. Microsoft might unify some of it (for ease, maybe a single per-user price to get all Copilots relevant to that user’s licenses), or keep them separate to maximize revenue per product line. As a CIO, your licensing team should treat these AI capabilities like another layer on top of your Microsoft stack: track which users have which Copilot licenses and ensure you’re not over-paying or under-utilizing.
• Pricing Adjustments: We should acknowledge the possibility that Microsoft could adjust the $30 price in the future. If Copilot proves indispensable and competitors charge more, Microsoft might raise prices (though $30 is already high in many eyes). Conversely, if a major competitor undercuts (say Google drops their equivalent to $10), Microsoft might lower Copilot’s price or offer more value at the same price. Also, economic factors or cost of providing the service (running AI models isn’t cheap) will influence pricing over time. Plan contingencies: if you base a lot of your workflow on Copilot, consider what you’d do if price increased at renewal – or have conversations during renewals to lock pricing for multiple years if possible. Many enterprise agreements allow price locks for 2-3 years; it could be wise to secure Copilot’s price in writing given potential volatility.

In summary, expect Microsoft’s AI licensing to be dynamic. We are at the early stage of a new paradigm, and Microsoft is undoubtedly watching adoption rates, customer feedback, and competitive moves to refine their strategy.

As a CIO and licensing strategist, stay informed: attend Microsoft briefings, consult with Microsoft licensing experts regularly, and review product terms each quarter.

A proactive approach will ensure you can adapt your AI adoption strategy in step with Microsoft’s evolving licensing models – whether that means seizing a new bundled offering or adjusting your budget assumptions when a change comes down the line.

CIO Recommendations

Finally, here is a checklist of key actions and strategic decisions for CIOs (and IT/finance leaders) to successfully adopt Microsoft 365 Copilot and related AI services:

1. Assess Eligibility and Readiness: Inventory your current Microsoft licenses to ensure users are on eligible plans (M365 E3/E5, Business Standard/Premium, etc.). Upgrade those who aren’t, or plan for additional base license costs. Also verify technical readiness – modern Office app versions, Teams upgrades, and Entra ID configuration for Copilot.
2. Start with a Pilot (Start Small): Identify a pilot group of users or a department that could benefit greatly from Copilot (e.g. a content-heavy team like marketing, or overwhelmed teams like customer support or finance reporting). Purchase a limited number of Copilot licenses for a proof-of-concept period. Observe usage and gather feedback. This controlled rollout will help you understand real-world value and any challenges, informing a broader deployment plan.
3. Budget Incrementally & Secure Funding: Treat Copilot and AI spend as a distinct item in your IT budget. Use the pilot results to build an ROI case and secure funding for a wider rollout. Communicate the expected ongoing cost (per user/year) to finance well in advance. If needed, prepare to trim costs elsewhere or phase other projects – frame Copilot as a productivity investment that may require reallocation of budget, not just an add-on expense.
4. Engage in Licensing Negotiation: Don’t hesitate to negotiate with Microsoft or your reseller, especially if you plan a large deployment. While Microsoft’s stance is $30/user with few discounts, enterprise customers can sometimes get concessions. Aim for price protections (multi-year lock) or introductory discounts if you’re an early adopter in your industry. Just be wary of future price hikes after any initial deal.
5. Develop Usage Policies & Training: Create guidelines for Copilot use within your organization. For example, instruct users on types of questions to ask, how to verify AI-generated content, and handling of sensitive data (though Copilot is designed to respect internal data controls, users should still practice good judgment). Conduct training sessions or workshops to educate users on Copilot’s capabilities – many employees might not know how to best leverage it. Well-trained users = higher ROI. Consider internal “Copilot champions” or power users who can help others and share creative use cases.
6. Monitor Adoption and Benefits: Once deployed, actively monitor Copilot’s usage and impact. Use Microsoft’s admin reports and gather user stories. After a few months, report back to executives: e.g., “Copilot was used to generate 500 project status reports and 1,200 email drafts last quarter, saving an estimated 400 hours of work.” Regularly refresh these metrics. If certain teams aren’t using Copilot much, find out why (lack of training? Not integrated into their workflow? Or maybe they truly don’t need it – and you can reassign those licenses).
7. Scale Smartly: Based on pilot success, scale up the deployment – but do so strategically. You don’t necessarily have to give Copilot to everyone at once. Perhaps roll out by function: today marketing and finance, next month to HR and operations, etc. Prioritize high-value use cases. Conversely, if some roles see little use for Copilot (say, warehouse floor workers), you might decide not to license them now. Regularly revisit who has a license and adjust the allocation to maximize usage and value.
8. Integrate Other AI Services: Look beyond Microsoft 365 Copilot to the broader ecosystem:
   • If you have software developers, enable GitHub Copilot for them and include that in your AI adoption roadmap. It’s a complementary tool that can yield huge productivity boosts in coding – align with your dev team’s budget to get it deployed.If you’re a Dynamics 365 shop, evaluate Dynamics Copilot features/add-ons for sales and customer service. Work with those business unit leaders to pilot the Sales or Service Copilot – these could directly impact revenue or customer satisfaction.Experiment with Azure OpenAI Service for custom scenarios specific to your business. Perhaps set up an innovation project to build a small internal AI chatbot or to process internal data with GPT. This will build internal competency with AI and might unlock unique solutions that off-the-shelf Copilot cannot provide. Just keep an eye on consumption costs and start with clear objectives.Keep track of Security Copilot if you have a large security operations team. When it becomes generally available, consider a pilot there too, as it addresses a very different but critical domain (cybersecurity).
   By treating AI holistically, you can ensure your organization reaps the benefits across departments. It also helps in negotiations – a broader AI engagement with Microsoft could give you leverage to get better terms.
9. Stay Informed on Licensing Changes: Assign someone on your team (or your licensing partner) to continuously monitor Microsoft announcements, product terms updates, and industry news on Copilot and AI services. If Microsoft launches a new plan (like an “E7” or adds Copilot into certain SKUs) or adjusts pricing, you want to know immediately to adjust your strategy. Consider joining Microsoft’s customer advisory boards or tech community webinars on Copilot. Licensing for AI is a fast-moving area – what’s true today might change in 6 or 12 months. Being informed ensures you won’t miss opportunities (like a new bundle that could save money) or get caught off-guard by a change.
10. Governance and Ethics: Establish an AI governance committee or at least guidelines to oversee ethical and compliant use of generative AI. Ensure that using Copilot aligns with your data compliance requirements (e.g., no sensitive regulatory data should be prompted in a way that violates policy, though Copilot is designed not to leak data, the outputs still need review). Address any employee concerns about AI (job displacement fears, etc.) by positioning Copilot as an assistant, not a replacement. Maintaining trust and clarity will help user adoption and prevent misuse. From a CIO perspective, also consider the impact on support: users might sometimes treat Copilot as infallible; IT should be ready to handle cases where Copilot produces incorrect results or any technical issues in the rollout.
11. Measure and Communicate Success: Over the long term, measure the broader impact of Copilot on your organization. This could include improved employee engagement scores, faster project delivery times, cost savings from process improvements, etc. Communicate these successes to stakeholders – both to maintain funding and to identify further expansion opportunities. For example, if marketing had huge success with Copilot, maybe it’s time to extend it to your international offices or other departments. If some ROI targets weren’t met, analyze why – maybe more training is needed or the use case wasn’t suitable.
12. Prepare for the Future: AI capabilities will become standard in software. Plan for a future where what is now “optional” (like Copilot) may become a baseline expectation for productivity. This could mean budgeting for AI features as part of every software investment, updating job descriptions (employees skilled in using AI tools will perform better), and considering organizational changes (perhaps creating an “AI enablement” team internally). In other words, align your IT strategy to an AI-augmented workforce. Microsoft’s Copilot is one of the first major steps in this direction; more will follow (from Microsoft and others).

By following these recommendations, CIOs and IT leaders can effectively harness Microsoft 365 Copilot and related AI services to boost productivity while managing costs and risks. The goal is to strike a balance – empower your organization with cutting-edge AI tools, but do so in a controlled, value-driven manner.

When executed well, the adoption of Copilot can be a cornerstone of your digital transformation, driving significant efficiency gains and enabling your talent to focus on the work that matters most.