GitHub Admin UI + Billing API: Better together for smarter spend decisions
As a GitHub administrator, you already have a strong place to start when somebody asks, “Why did our AI spend go up?” In Metered usage, you can see the change, choose the period, and group the data by organization or cost center. That first investigation often leads to questions that are specific to your company. Finance may want a month-end report based on its own reporting calendar. An engineering leader may want to see whether an increase is spread across a team or concentrated among a few people. Answering those questions once is useful; answering them repeatedly calls for a reusable approach. Use each surface for what it does best The GitHub admin UI shows you where to look and gives you the controls to respond. The Billing Usage API helps you answer the recurring questions that are specific to your company. Neither replaces the other. Together, they give administrators a practical loop: spot the change in Metered usage, understand it through a reusable API-powered view, and act with a targeted budget. That means better cost control without treating every user or team as the problem. Let’s walk through this better-together approach using a common example: AI spend starts to rise, but the reason is not yet clear. The question: Spend is up, but what is driving it? Imagine that finance notices an increase in AI spend before the next close. It could be a sign that more developers are getting value from Copilot. It could also be one workload using far more than expected. At this point, nobody knows, and a broad restriction would be premature. The GitHub administrator needs to help finance and engineering answer three practical questions: - Which part of the business is driving the increase? - Is the spend concentrated among a few users or broadly distributed? - Which control should change without disrupting everyone else? The goal is not simply to reduce a number. It is to understand the increase well enough to protect useful work while addressing anything unexpected. 1. Start in the admin UI: Find the increase The admin UI is the natural place to begin because it lets you explore the data before you decide what kind of report or control you need. Open **Billing and licensing > Metered usage** and select the relevant reporting period. This first check matters. It confirms that the increase is real, shows when it happened, and gives you a shared starting point for the conversation with finance and engineering. Fig 01: Metered usage establishes the increase and the period that needs investigation. Narrow the increase by organization An enterprise total tells you that spend changed, but not where to look next. Group the usage by organization to see which part of the enterprise contributed most to the increase. Fig 02: Organization grouping narrows an enterprise-wide increase to an accountable business area. Suppose the octodemo organization stands out. You now know where to continue the investigation and which leaders can add context. You do not yet know whether the spend is justified, and that distinction matters. The increase could come from successful Copilot adoption, a migration, a seasonal workload, or an automated process that needs attention. Connect the increase to a cost center An organization can contain several teams, programs, and budgets. Grouping by **cost center** takes the investigation one step closer to the people who understand the work behind the spend. Fig 03: Cost-center grouping identifies the financial owner of the increase. In this scenario, octodemo-org-cc has the largest increase. In only a few clicks, the admin UI has taken us from an enterprise-wide signal to the cost center that needs a closer look. For a one-time question, this may be enough. Now imagine that finance asks for the same analysis every month, with a fixed reporting period and a ranking of spend by user. That is the point where the API adds value. It does not replace the investigation you just completed; it helps you repeat and extend it. 2. Continue with the API: Answer the repeatable question The Billing Usage API gives you access to the data behind a more tailored report. You can use filters to match the period finance cares about, focus on the cost center you found in the UI, and build a view that can run again tomorrow or next month. Fig 04: Billing usage endpoints and time filters provide the inputs for a reusable report. Define the reporting question first Before writing code, state the question the report needs to answer. In this example, it is: > Which users in the selected cost center account for the most net spend during this reporting period? That one question keeps the report focused. It also determines the workflow: 1. List the organization's members to establish the candidate users. 2. Resolve which members belong to the selected cost center. 3. Query organization AI credit and premium-request usage for those users and the selected period. 4. Combine the results into a per-user total. 5. Rank users and aggregate the result by cost center. The prototype uses year, month, and optional day filters so the output matches the finance period. It also accepts a cost-center filter. Because the admin UI has already pointed us to `octodemo-org-cc`, there is no reason to start with every member of the enterprise. Understand the per-user query pattern There is one API behavior to understand before building the report. The organization billing endpoints return an aggregate when the user filter is omitted. To create a spend-by-user ranking, the workflow makes a filtered request for each selected user and usage type. For example, this request asks for Eve's AI credit usage in July 2026: curl -L \ -H "Accept: application/vnd.github+json" \ -H "Authorization: Bearer $GITHUB_TOKEN" \ -H "X-GitHub-Api-Version: 2026-03-10" \ "https://api.github.com/organizations/octodemo/settings/billing/ai_credit/usage?year=2026&month=7&user=eve" The response contains one or more usage items, with amounts such as `grossAmount`, `discountAmount`, and `netAmount`. The prototype adds the `netAmount` values to calculate Eve's AI credit total for the period. It then runs the equivalent premium-request query and combines the two totals. We can now see one user's contribution during the same period we investigated in the UI. Repeating the request for the members of the selected cost center gives us the ranking that finance asked for. For a production workflow, a few practical details matter: - Limit the candidate list to the cost center under investigation. - Paginate organization membership and cost-center results. - Use bounded concurrency instead of sending every request at once. - Record partial failures rather than silently treating them as zero spend. - Keep an audit record of when the data was pulled and transformed. For a daily check, the report can use a narrow period and write a timestamped output. At finance close, the same workflow can produce the month-end rollup. The question stays the same; only the reporting window changes. Reveal concentration that totals can hide The result is a custom Spend by User view that brings the organization, cost center, reporting period, AI credit usage, premium-request usage, and total net spend into one place. Fig 05: A company-specific dashboard exposes per-user concentration inside the selected cost center. In the illustrative data, the octodemo organization has 22 users and $3,651 in total net spend for July 2026. The octodemo-org-cc cost center accounts for $2,700 of that amount. Two users stand out: User AI credit net spend Premium-request net spend Total net spend Eve $900 $600 $1500 Adam $600 $400 $1000 Together, Adam and Eve account for $2,500 of the $2,700 attributed to that cost center. That is approximately 93% of its total in this example. These figures are demonstration data, but they show why the extra view is useful. Instead of reacting to a $2,700 cost-center total, the administrator can talk to the owners of two workloads and understand what the spend supported. Concentration does not automatically mean waste. Adam and Eve may be doing approved, high-value work. The dashboard tells the business where to ask the next question; the people involved provide the context needed to answer it. 3. Return to the admin UI: Choose the right control The API has helped us understand the increase, but it does not make the decision for us. Return to Billing and licensing > Budgets and alerts to review the available controls and choose the narrowest one that fits what you learned. Fig 06: Budget scopes turn the investigation into a targeted governance decision. Set a cost-center user-level baseline A cost-center user-level budget applies the same per-user amount to every current and future member of that cost center. This is useful when the group needs a different baseline from the rest of the enterprise. For example, the administrator might give octodemo-org-cc additional per-user headroom because its work legitimately uses more AI credits. This avoids raising the universal user-level budget for everyone. A user-level budget counts both included and paid AI credit usage. It is always a hard stop for the individual. It does not reserve part of the shared pool, and it does not replace the cost center's paid-usage budget. Preserve justified exceptions If Adam or Eve has an approved role that requires more capacity, an individual user-level budget can replace the cost-center baseline for that person. The exception stays limited to the person who needs it instead of increasing the budget for the whole cost center. Fig 07: Cost-center baselines and individual overrides preserve useful work without widening access for everyone. The precedence is straightforward: 1. An individual user-level budget overrides the cost-center user-level budget. 2. The cost-center user-level budget overrides the universal user-level budget. In practice, you can set a universal baseline, add more headroom for a cost center with a clear business need, and use individual overrides for documented exceptions. Why the UI and API work better together At this point, the better-together pattern becomes clear: - Metered usage supports interactive discovery. - Billing Usage API supports repeatable, company-specific analysis. - Budgets and alerts supports targeted policy decisions. Each surface does the job it is best suited to do. The UI makes it easy to explore and manage GitHub. The API lets you repeat a company-specific analysis without rebuilding it by hand. Used together, they give finance, engineering, and administrators the same evidence before a control changes. Make it part of the operating rhythm A useful dashboard should lead to a useful conversation. Decide who receives the report, how often they review it, and what happens when a user or cost center stands out. For example: - Run a daily pull to detect unusual changes early. - Produce a month-end rollup aligned to finance close. - Route cost-center summaries to the relevant business owner. - Review high-consumption users with engineering before changing limits. - Record approved individual overrides and revisit them regularly. Over time, the conversation can move from “Who spent this?” to “What outcome did this spend support, and does the current policy still fit?” When the same users repeatedly appear at the top, leaders can inspect the workload, remove waste, validate business value, or approve more capacity. When usage becomes broadly distributed, the cost-center baseline may need adjustment instead. The report makes those patterns visible over time. The better-together workflow at a glance The story above introduces each surface when it becomes useful. This table summarizes their roles. Surface Primary role Best used for Important limitation Metered usage Interactive investigation Finding the affected period, organization, and cost center Manual exploration is not a reusable company report Billing Usage API Programmatic usage retrieveal Scheduled reporting, time-sliced analysis, and per-user views Per-user attribution requires filtered requests and careful handling of pagination and failures Custom spend by user view Company-specific interpretation Ranking users and aligning usage to internal ownership Concentration is evidence to investigate, not proof of waste Budgets and alerts Governance controls Cost-center baselines and individual overrides A broader budget cannot override a user who has reached their ULB The practical takeaway is simple: begin with exploration, automate only the question worth repeating, and adjust policy after the data has context. That sequence keeps governance precise while preserving useful AI work. Learn more - REST API endpoints for billing usage - List organization members] - Budgets for usage-based billing] - Using cost centers to allocate costsFeedback : building the foundations for AI adoption with AI itself
I would like to share some feedback on the recent SharePoint Copilot improvements. As a consultant, trainer, and Microsoft MVP working daily with Microsoft 365 Copilot customers, I am genuinely impressed by the direction SharePoint is taking. For years, we have told customers that successful AI adoption requires strong information architecture, metadata, governance, content organization, and naming conventions. What I find particularly interesting today is that SharePoint Copilot is starting to help organizations build these foundations instead of simply depending on them. Features that assist with site creation, page creation, content organization, metadata generation, metadata enrichment, and automation significantly reduce the effort required to establish a well-structured SharePoint environment. This is a meaningful shift. AI is no longer only consuming well-organized knowledge. It is increasingly helping users create and maintain that organization. From my perspective, this may become one of the most important accelerators for Microsoft 365 Copilot adoption because many organizations struggle more with content structure than with AI itself.Scaling Seller Impact with ASPX Insights: From Data Access to AI-Driven Execution
ASPX Insights in Partner Center Most sellers are not constrained by opportunity; they are constrained by time and signal. With up to 70% of effort spent on administrative work, portfolio coverage continues to expand while insight quality declines. Sellers are forced to manually interpret fragmented telemetry across multiple systems, slowing decision-making and reducing precision in where they focus. The result is missed revenue signals, delayed interventions, and inconsistent execution at scale. Productivity is not just about efficiency, it is about enabling every seller to consistently identify and act on the highest-value opportunity, in real time. To drive consistent, data-led growth across Security and AI Business Solutions, partners should connect to ASPX Insights within Partner Center. This provides direct access to adoption propensity models, customer telemetry, and actionable account-level insights across Microsoft 365 Copilot, E7, and Agent 365 scenarios. Access to ASPX Insights is only the starting point. The real value comes from how you operationalise that data and surface it directly to sellers in the flow of work. The most effective pattern is to build a lightweight “opportunity agent” that connects to ASPX data via API and translates telemetry into clear actions. This ensures your sales teams have the right conversation with the right customer at the right time - Conversations that are backed by intelligent insights to help guide your customer's on their AI and security journey. The Architecture ASPX Insights is powered by Partner Center data and exposes rich telemetry and propensity signals that can be accessed programmatically. This allows partners to move beyond dashboards and embed insights directly into seller workflows. As demonstrated in internal adoption patterns, partners can connect to ASPX via API and pull Customer-level adoption and usage telemetry Copilot, Security, and Agent usage signals Propensity scores for expansion, adoption, and conversion Licensing, whitespace, and engagement indicators The M365 Partner API – AI Business Solutions & Security Insights allows partners to ground an agent in real, actionable data rather than static pipeline assumptions. By pulling live telemetry and seat-level signals directly into the agent, the solution continuously reflects actual customer usage patterns - who is adopting, who is stalled, and where there is untapped potential. This means opportunity identification is no longer based on periodic reporting or manual interpretation, but on near real-time behavioural insight. As a result, account prioritisation, upsell motions, and intervention strategies are driven by evidence rather than instinct, enabling account teams to act with precision and focus on the highest-impact opportunities across their portfolio. The agent should act as a translation layer between raw telemetry and seller action. The goal is not to expose more data, but to remove ambiguity and tell the seller exactly where to focus. A simple architecture looks like this: Data layer Ingest ASPX Insights data via API on a daily or scheduled basis. Optionally store monthly snapshots to track trends and smooth out variability. This creates both real-time signal and historical context. With the data layer you have a couple of options. You can integrate directly into Partner Centre ASPX Insights by using the API. This is technically complex and may have a longer lead time to see results. Alternatively, to see results with less complexity, you can simply download snapshots of the data monthly from ASPX Insights in Partner Centre. This is manual but easy to achieve and offers a shorter time to value for your agent. Scoring layer Use ASPX propensity outputs directly or combine them with your own logic to rank accounts across a small set of opportunity lenses Expansion ready (Copilot scale) Conversion ready (free to paid) At risk (low adoption vs paid licenses) Transformation ready (Agent 365 and advanced AI scenarios) These align directly with the machine learning models and signals already surfaced in ASPX. Action layer Translate scores into next best actions Who to engage Why now What motion to run (sell, enable, expand, govern) This is where agents create value. Sellers should not see raw dashboards. They should see prioritised accounts and recommended actions. Internal Adoption Path The key design principle is simple: bring insight into the tools sellers already use. CRM integration Push ranked accounts and recommendations directly into CRM as opportunities, tasks, or account insights. This ensures data becomes part of pipeline management, not a separate activity. Copilot / Agent interface Expose the agent through Microsoft 365 Copilot or a custom chat interface where sellers can ask Which customers should I prioritise this week Which accounts are ready for Copilot or E7 expansion Where are my adoption risks The agent queries the ASPX-backed dataset and returns structured recommendations in seconds. Proactive notifications Trigger alerts based on signal changes Spikes in Copilot usage Drops in adoption for paid tenants New high-propensity accounts entering threshold This shifts sellers from reactive to proactive engagement. Portfolio dashboards (secondary) Maintain dashboards for leadership and planning, but not as the primary interaction model for sellers. Dashboards support strategy, agents drive execution. Extending into E7 and Agent 365 scenarios Once the agent is connected to ASPX, partners can extend the same model across broader solution plays E7 opportunities Use signals such as usage depth, licensing posture, and workload adoption to identify customers progressing toward advanced security and compliance requirements. The agent can flag these accounts as ready for E7-led conversations. Agent 365 opportunities Combine Copilot maturity with agent usage signals to identify customers moving beyond productivity into process automation. These are high-value transformation plays where partners should proactively engage. This ensures sellers are not operating in silos but are guided toward the next logical workload based on real behavior, not assumptions. Where to Next If you lead a partner sales team, connect to ASPX Insights and see how these insights can empower your sales teams to achieve more. Check out our ready made ASPX Insights agent in Github.Calling all IT Admins - webinar on configuring Copilot Chat and updates for Students 13+
This IT Admin-focused workshop walks through how to configure Microsoft 365 Copilot Chat, from your tenant all the way to the end-user experience. When you enable Copilot Chat for students 13+, they will also get access to the new Study & Learn agent, Copilot Notebooks, Learning Activities and more. We cover the latest features that are available — including the new 13+ student configuration options, CSV, SDS and Powershell uploads, Copilot agents & extensibility, and updated licensing & security controls. By the end, you’ll be able to confidently deploy, manage, and optimize Copilot Chat in your environment so your users can safely harness AI productivity from day one. This 45-minute webinar will be led by Bill Sluss Principal Product Manager from the Microsoft Education team. When: Wednesday, August 19th @ 8am Pacific time Register: https://df.events.teams.microsoft.com/event/df.95feda23-419a-4d99-bfad-f7e4fd52a498@72f988bf-86f1-41af-91ab-2d7cd011db47?source=copyLinkOneEventsShareDialog Mike Tholfsen Group Product Manager Microsoft EducationFrom Leadership Engagement, Town Halls to Communities: Put Viva Engage to Work at Comms Camp
The best way to learn Viva Engage is not by watching someone else publish another perfectly prepared demo post. It is by starting with a real communications challenge. Maybe you are planning a leadership campaign and want employees to do more than simply read an update. Perhaps you are trying to build a community with a clear purpose, improve an AMA, make a town hall part of an ongoing conversation, or understand what employee questions are telling you. Bring that challenge to Comms Camp, a free, hands-on workshop taking place October 12–13, 2026, at Microsoft in Redmond, Washington. Comms Camp is designed for corporate communications teams and the IT, adoption, employee experience, and community partners who support them. Participants will use Viva Engage, Microsoft 365 Copilot, and practical agent patterns to turn real communications scenarios into reusable plans and workflows. Start with the outcome, not the feature Viva Engage can support leader visibility, employee conversation, community building, campaigns, events, and knowledge sharing. But successful communications programs rarely begin with a list of product features. They begin with questions: Who needs to understand or do something differently? What does meaningful participation look like? Which leader, community, or conversation can create trust? What should happen after employees respond? Which signals will tell us whether the communication worked? Where can AI help without replacing the communicator’s judgment? At Comms Camp, you will start with those questions and use Viva Engage as part of a practical communications plan. What you will work through The workshop takes participants through a complete communications scenario, from the original ask to activation and measurement. Choose your challenge and bring a scenario or select a sample. Define your audience, intended outcome, risks, and the action you want employees to take. Design the Viva Engage activation Determine how Viva Engage, Copilot and other Microsoft products can support the communication. Depending on your scenario, that could include: A leader or executive communication A community activation A campaign moment An AMA or event An employee prompt designed to encourage useful participation A follow-up plan that keeps the conversation moving Turn conversations into signals Publishing is not the finish line. Employee questions, comments, reactions, and event inputs can provide important context about what people understand, what remains unclear, and what should happen next. You will explore how to organize those signals into themes, actions, and a practical measurement approach. Share what you built Participants will share their developing playbooks, learn from one another, and get feedback they can apply when they return to their organizations. Explore Copilot and agent workflows Identify where AI could save time or improve consistency across planning, drafting, summarizing, and follow-up. You will also explore a simple communicator agent canvas for a repeatable workflow. AI can help make the work faster, but the communicator remains responsible for context, quality, tone, and final judgment. Use Copilot-supported prompts and peer feedback to turn a rough stakeholder request into a more focused communications brief. What you will take home Comms Camp is designed to create reusable outputs, not just inspiration. Depending on your chosen scenario, you can leave with: A strategic communications brief A Viva Engage activation plan Copilot prompts and workflows A leader communication, event, AMA, campaign, or community plan A communicator agent canvas A signal and measurement plan A reusable communications playbook You will also leave with ideas from other communicators who are navigating many of the same challenges, including channel complexity, leader visibility, responsible AI adoption, employee participation, and demonstrating impact. Who should attend? Comms Camp is intended for: Corporate and employee communications professionals Leader and executive communications teams Viva Engage community managers Change and adoption professionals Employee experience leaders IT partners supporting communications and communities Organizations may send multiple participants, and communications and technology partners are encouraged to attend together. Participants should have access to Microsoft 365 and Viva Engage. Microsoft 365 Copilot access is recommended. Register for Comms Camp in Redmond Join us October 12–13, 2026, at Microsoft in Redmond, Washington. The workshop is free, and registration is required. Explore the Comms Camp experience: https://adoption.microsoft.com/comms-camp Register directly for the Redmond Comms Camp: https://aka.ms/CommsCamp/Joinus Cannot join us in Redmond? Comms Camp is planned as a multi-city experience. Visit the Comms Camp site to learn when more locations are announced. Tell us where you want us to bring camp next! Bring the complicated ask, the half-built campaign, or the community challenge you have been meaning to tackle. We will help you turn it into something you can use. Learn. Share. Build.Partner Blog | From AI curiosity to Copilot adoption in 30 days
A focused, partner-led 30-day Copilot trial is now available, backed by record FY27 investments to accelerate SMB growth. Thirty days. Twenty-five users. One clear path to AI. For small and medium-sized businesses, AI is no longer a someday conversation, it's a right-now decision. SMB customers aren't asking whether AI matters anymore; they're asking how to put it to work in ways that are practical, fast, and secure. The hard part isn't interest. It's the starting line. Customers are looking to identify relevant use cases, experience AI in their everyday work, and evaluate its value before making a broader commitment. This creates a significant opportunity for Cloud Solution Provider (CSP) partners to lead customers from initial interest to sustained adoption. The SMB segment represents a Microsoft-estimated $625 billion* market opportunity in FY27, yet most organizations remain early in their AI transformation journey. As shared at MCAPS Start for Partners, FY27 brings record levels of CSP and programmatic incentive investments through the Microsoft AI Cloud Partner Program, alongside investments in partner capabilities, skilling and go-to-market resources designed to enable growth, bring new customers and workloads to the Microsoft ecosystem, and deliver customer success through Frontier transformation, starting with Microsoft Copilot. One of the primary investments we are making for the partner ecosystem is Copilot in 30, now available through CSP New Commerce. Copilot in 30 is a new, limited-time, CSP partner-led Microsoft 365 Copilot Business trial offering designed for SMB customers with fewer than 300 employees. It is available through December 31, 2026. This offer combines a 25-user, 30-day Microsoft 365 Copilot Business trial with partner-ready resources and customer guidance, campaign materials, setup resources, adoption content, and conversion guidance. Together, these resources give you a structured way to turn AI interest into hands-on Copilot experience. What’s new For partners, Copilot in 30 provides a repeatable path to turn customer engagement into adoption planning and growth. Rather than positioning Copilot as a standalone product trial, you can lead a guided experience centered on real business needs. Customers can explore how Microsoft 365 Copilot Business fits into their daily work, test scenarios across roles, and build confidence with a focused group of users. Copilot is the on-ramp. It enables people to work smarter and faster today, and it opens the door to the agents and workflows that follow. You can use the 30-day experience to guide customers through practical scenarios, identify high-value use cases, and create a clearer path from evaluation to paid Microsoft 365 Copilot Business deployment. Continue reading here
Launching DIY Data Control for Nonprofits
I want to create a library of open-source resources that helps self-taught IT champions in nonprofit organisations build fully governed, secure shared data systems. I have plenty of ideas about how to do this, but before I press ahead, I want to listen to the people I hope to support to ground those ideas in reality. For my first project, I want to draw on part of the Microsoft ecosystem, which provides some useful tools for safely building your own data systems: Microsoft Learn: Microsoft provides a wealth of free learning resources. I use them a lot and they are as good as other resources that I have happily paid for. The two big barriers to using them are finding time and working out where to start. The Common Data Model for Nonprofits: This is an open-source resource from Microsoft, it describes the tables of data that a nonprofit organisation needs, and the relationships between them. Once you add your own data it becomes a shared functioning model of your organisation. Role based column and row level security: This is the revolutionary part that lets you safely replace scattered spreadsheets with a single, comprehensive, shared model of your organisation. It lets you decide exactly which parts of which records people are allowed to see or change, so everyone who interacts with your shared model can only see and change the things that they need to. Model-driven Power Apps and Power BI: Once you have a detailed model of your organisation with governance baked into it, adding tools to interact with it becomes straightforward. Both Model-driven Power Apps and Power BI can understand the structure of your organisation from your model, and they will respect the governance policies that you built into it. In theory, these should provide all the tools you need to bring together scattered data in siloed spreadsheets into a single, secure, auditable shared source of truth. But there are gaps, and I want to find out what guides, signposts and tools would be needed to bridge them. Later I will want to explore the features that you could add with Copilot Studio if you wanted to. Once you have established a clearly defined, precisely secured data environment, Copilot Studio can provide the tools to develop and deploy AI agents safely. But for now, I will focus on the foundations of well-defined, well-governed, accessible data. If you have any thoughts about this project then I would love to hear them, and I’d especially like to find out what pain-points there are that I can target. So please do get in touch. Patrick Killeen Head and Heart CIC email address removed for privacy reasons https://www.headandheart.info/ This work is released under the MIT Licence and is available at https://github.com/head-and-heart-cic/public/blob/main/in-practice/2600707-launching-diy-data-control-for-nonprofits/README.md
