Land Your Offer - Anatomy of Revenue Generating Partner Offer - Part 2 - Copilot Envisioning
In Part 1 we dissected Copilot in 30 — a $0 trial offer for SMB customers. This time the customer is larger, the engagement is funded rather than free, and the anatomy of revenue changes with it. It also lands when Microsoft just introduced the new Copilot — Home, Code and Autopilot, running on usage-based billing and governed through FinOps for AI — which makes a structured envisioning engagement the front door to a much bigger conversation. Most organisations with 300 or more seats already believe Copilot and agents matter. What they lack is a clear picture of where AI will pay off, what it will take to get ready, and how they'll prove it before committing budget. The Frontier Accelerate for Copilot: Envisioning & POC engagement gives you a pre-sales, partner-led answer to all three — funded by Microsoft and sized from a 10-hour readiness sprint to a 280-hour enterprise programme. Package it as a Microsoft Marketplace offer and you have a repeatable front door to every Copilot, Agent 365 and Microsoft 365 E7 opportunity in your territory. Start Here: Why Publishing on Microsoft Marketplace Matters Microsoft Marketplace is Microsoft's partner-focused business platform, designed to help you reach more customers and simplify how you sell. A published offer gives your practice a permanent, discoverable storefront in the place customers and Microsoft sellers already look for Copilot expertise. More importantly, an offer turns your expertise into something repeatable. Define the engagement once — phases, activities, deliverables, sizing — and run it across every qualified customer instead of scoping from scratch. Professional service and managed service offer types are available in Partner Center, so one listing can carry the envisioning engagement, the POC and the ongoing services that follow. The Enterprise Opportunity: Interest Is High, Direction Is Missing The customers for this offer are organisations with at least 300 Office 365 / Microsoft 365 seats — mid-market through to the largest enterprises. They are the customers with the most to gain from Copilot and agents, and the most complexity to work through first: security and governance, tenant and access dependencies, adoption and change, and a credible way to measure value. That gap between ambition and a plan is where partners win. Microsoft is investing in the full Copilot journey in FY27, from envisioning and proof of concept through deployment and adoption — and the envisioning stage is where you shape the roadmap, the scope and the commercial conversation before anyone else does. Why Copilot and Agents Are the Right Place to Start Microsoft 365 Copilot puts AI inside the apps people already use every day — Outlook, Teams, Word, Excel and PowerPoint — so value arrives without a platform change. For larger organisations, that is only the first layer: Agent 365, custom agents built with Copilot Studio, and Microsoft 365 E7 extend Copilot from personal productivity into role-based and process-level automation. The new Copilot adds a third layer. Cowork takes delegated work and returns a finished result; Code lets knowledge workers build apps, dashboards and automations in natural language, hosted on Copilot Managed Runtime; and Autopilot is a persistent agent with its own identity that keeps work moving without a prompt. All three run on usage-based billing rather than the per-user subscription, which means every customer now has to decide which users and which scenarios justify consumption spend — and how to govern it with FinOps for AI. Each layer brings its own questions — which personas, which scenarios, what governance, what consumption model, which capabilities are worth paying for by the task — and each question is an envisioning conversation a partner is best placed to lead. Meet the Offer: Envisioning & POC, Sized to the Customer The Frontier Accelerate for Copilot: Envisioning & POC engagement is a pre-sales, partner-led engagement that identifies personas and use cases and builds a business case for Microsoft 365 Copilot, Agent 365, Microsoft 365 E7 and/or agents — with an optional proof of concept. The essentials: Who qualifies: Customers with a minimum of 300 Office 365 / Microsoft 365 seats; larger tiers unlock at 500, 1,000, 1,500, 3,000 / 5,000 and 10,000+ seats How it's sized: Six tiers — XXS (10 hrs), XS (20 hrs), S (40 hrs), M (100 hrs), L/XL (150 hrs) and XXL (280 hrs) — with hours scaling with the seats in scope What it covers: Five phases — Assess, Inspire, Design, POC and Executive Summary — with a working POC and measured results from the S tier upward What Microsoft provides: A delivery guide, pre-engagement planning resources and Microsoft Commercial Incentives (MCI) funding tied to proof of execution What the customer gets: Readiness findings, a business case and value plan including usage-based billing and Copilot Credits, technical requirements and a remediation plan, an adoption roadmap, a working POC and an executive readout Microsoft funds the engagement. You own the scope, the relationship and everything that follows. Your Role: From Trusted Assessor to Transformation Partner An envisioning engagement is not a workshop; it is a guided decision. Your job is to move the customer from curiosity to a signed proposal, with evidence at every step. Assess — identify high-value scenarios, choose the right assessments, define what success looks like and deliver readiness findings the customer can act on. Inspire — show what Copilot and agents can do across roles; make security, governance, adoption and reporting concrete rather than abstract concerns. Design — turn findings into a business case and value plan (including usage-based billing), a remediation plan, technical requirements, an adoption roadmap and clear POC criteria with risks, owners and dates. Prove — scope the POC users and products, prepare the environment, build the agent or solution, train the users and measure results including Copilot Credits consumed. Summarise — deliver the executive readout on seat growth and consumption, then convert: trial to paid licences, commercial proposal and signature, and a named wave 2 expansion plan. Every phase produces something the customer keeps — and every deliverable positions you as the partner who should build what comes next. Inside the Offer: Activities and Hours by Engagement Size Below is the full activity plan behind the offer, with hours for each of the six engagement sizes. Use it to size your own offer plans and statements of work. ID Phase Activity XXS XS S M L/XL XXL — Pre-req Customer eligibility (min. O365/M365 seats) 300+ 500+ 1,000+ 1,500+ 3,000+ / 5,000+ 10,000+ A1 Assess Identify high-value scenarios 0.5 1 1.75 3.75 5.5 10.5 A2 Assess Select assessment(s) 0.5 0.5 1 2.25 3.5 6.25 A3 Assess Define success 0.5 0.75 1.5 3 4.5 8.5 A4 Assess Deliver readiness assessment(s) 1 1.75 2.75 6 9 16.75 I1 Inspire Product overviews & demos across Copilot and agent capabilities 1 1.5 2 4.5 6.75 12.5 I2 Inspire Security/governance overview, incl. tenant and access dependencies 0.5 1 1.5 3 4.5 8.5 I3 Inspire Adoption/change overview 0.5 0.75 1 2.25 3.5 6.25 I4 Inspire Reporting/analytics overview 0.5 0.75 1 2.25 3.5 6.25 I5 Inspire Stories & Scenario Library 0.5 1 1.5 3 4.25 8.5 D1 Design Business case/value plan, incl. usage-based billing (UBB) 1 1.75 2.75 6.25 9.5 17.5 D2 Design Remediation plan 0.5 1 1.75 3.75 5.5 10.5 D3 Design Technical/functional requirements 0.75 1.5 2.25 5 7.5 14 D4 Design Adoption roadmap 0.5 1 1.75 3.75 5.5 10.5 D5 Design POC success criteria & environment prep 0.5 1 1.75 3.75 5.5 10.5 D6 Design Recommendations/risks/owners/dates, incl. validation and next-step owners 0.25 0.75 0.75 2.5 4 7 P1 POC Scope/users/products/features 0 0.25 1 3.5 5.25 9.75 P2 POC Confirm requirements/design 0 0.25 1 3.5 5.25 9.75 P3 POC IT access & environment prep 0 0.25 1.75 5.25 8 14.75 P4 POC Trial licenses 0 0.25 1 3.5 5.25 9.75 P5 POC Build POC agent(s)/solution(s); confirm Copilot Credits consumption 0 0.5 3.75 12.25 18.5 34.25 P6 POC Train POC users 0 0.25 1 3.5 5.25 9.75 P7 POC Measure/evaluate results, incl. usage and Copilot Credits consumed 0 0.25 1.5 3.5 5 10 E1 Exec summary Executive readout: seat growth and consumption implications 1 2 4 10 15 28 TOTAL Hours 10 20 40 100 150 280 Land Your Offer: What One Customer Is Worth The table below is the revenue anatomy of one Envisioning & POC engagement at each of the six sizes — and it shows that the funded engagement is only the first of three revenue streams. They stack on top of each other: MCI engagement incentive — Microsoft funds the envisioning and POC work itself, from $2K for a 10-hour XXS engagement to $100K for a 280-hour XXL programme, paid against proof of execution. CSP incentive on the licences that follow — earned on the Copilot revenue the business case unlocks, from the trial-to-paid conversion (T1) through the wave 2 expansion (X1), and growing as agent consumption and Copilot Credits scale. Managed services and follow-on professional services — the recurring engagement described in After the Readout, which is where the largest and most durable share of revenue lives. Item XXS XS S M L/XL XXL Minimum customer seats 300+ 500+ 1,000+ 1,500+ 3,000+ / 5,000+ 10,000+ Engagement hours 10 20 40 100 150 280 Post-delivery outcomes: Copilot rev (K) | Agent consumption (K) | Agent MAU 10 | 6 | 300 25 | 15 | 500 50 | 30 | 1,000 125 | 75 | 1,500 250/375 | 150/225 | 3,000/5,000 500 | 300 | 10,000 MCI engagement incentive (K) $2K $5K $10K $25K $50K / $75K $100K CSP incentive on Copilot revenue (K)† $1.95K $4.88K $9.75K $24.38K $48.75K / $73.13K $97.5K † CSP incentive shown at a blended 19.5% of the Copilot revenue outcome (direct bill 2.5 + 7 + 10; indirect reseller 7 + 12.5). Illustrative estimates from the offer plan — confirm current MCI payouts, CSP rates, eligibility and proof-of-execution requirements in the Microsoft Commercial Partner Incentives Guide. Now multiply. Everything above is the anatomy of a single customer. Landing the offer means running it across every qualifying customer in your territory — and you don't need to guess who they are. Partner Center's growth insights reporting, available through the AI Business Solutions & Security Insights (ASPX) dashboard, gives you account-level Copilot eligibility and seat whitespace, E7 opportunity, data security maturity, MCI eligibility and potential earnings for the customers you already manage. How the Offer Fits Together: From Sizing to Proof of Execution The offer runs left to right in three layers: Sizing & value — six engagement sizes from XXS (10 hrs) to XXL (280 hrs). Hours scale with the seats in scope, and value is tracked in the customer's own metrics. Five phases — Assess (A1–A4), Inspire (I1–I5), Design (D1–D6), POC (P1–P7) and Executive Summary (E1, T1, T2, X1). Each phase produces a concrete output the sponsor can see. Proof of execution — readiness and assessment findings; a business case and value plan including usage-based billing and Copilot Credits; technical requirements and a remediation plan; an adoption roadmap; a working POC with measured results; an executive readout covering next steps and consumption implications — and a named wave 2 expansion beyond the pilot team. The highlighted activities — security & governance (I2), adoption & change (I3), remediation plan (D2), technical requirements (D3), adoption roadmap (D4), IT access & environment (P3), build POC solution (P5), train POC users (P6), trial-to-paid conversion (T1), commercial proposal (T2) and the wave 2 expansion plan (X1) — are where the engagement stops being a project and becomes an ongoing relationship: managed services, ongoing optimisation and follow-on professional services after the engagement closes. After the Readout: Managed Services That Keep Delivering The executive readout is the start of the real engagement. Package these as standing services in your offer. Each one is sized in partner days so you can price it, and each one is tied to a result the customer's sponsor will recognise without a glossary: Managed service Partner activity — what you deliver and measure Customer business outcome — what it drives (illustrative targets, 1,500-seat customer) Deployment and remediation delivery • Effort: 5–10 days per wave • Activity: Close every item on the remediation plan and technical requirements (D2, D3) against dated owners, then licence and activate the wave's users by the roadmap date • Reported as: Items closed on time; seats activated; days from readout to go-live • Wave 1 live within 30 days of the readout, not 90 — two extra months of value on every seat • ≥95% of paid seats assigned and active; 75 idle seats would waste ≈$27K a year • Roll-out delivered within ±5% of the business-case budget Security and governance management • Effort: 2 days a month • Activity: Maintain the admin-settings baseline and data-protection controls, review agent permissions and access dependencies, approve plugins through the plugin registry and govern apps hosted on Copilot Managed Runtime, act on every Admin Settings Recommendation • Reported as: Recommended settings enabled; findings opened and closed; agents, plugins and apps with a named owner • Zero Copilot-related oversharing incidents; one enterprise data breach averages $4M+ • 100% of recommended settings on; findings closed within 30 days • Audit evidence produced in hours, not weeks — Data Security Maturity at Advanced-Healthy Adoption and change management • Effort: 3–4 days a month • Activity: Run the adoption roadmap (D4): coach champions, deliver role-based training, refresh scenarios, hold the monthly Copilot Analytics business review • Reported as: Active users as a share of assigned seats; people trained; low-activity users re-engaged • ≥80% of assigned seats active every month • 2–4 hours saved per user a week (≈3,000–6,000 hours across 1,500 seats) • ≈$0.5–1M a month of staff time released at $40/hour Agent and solution build-out • Effort: 5–15 days per agent or solution, then half a day a month to tune • Activity: Take each POC agent (P5) into production with Copilot Studio and Agent 365; release new Copilot Studio agents, Code-built apps and Autopilot agents from the scenario backlog, hosted on Copilot Managed Runtime • Reported as: Agents and apps live; active users per agent; tasks completed; Copilot Credits per completed task • 20–40% of tier-1 tickets or cases deflected per automated process • Cycle time cut 30–50% on each agent-run workflow; 200–500 hours removed a month per agent • Cost per completed task tracked and falling quarter on quarter FinOps for AI: consumption and licence management • Effort: 1-2 days a month • Activity: Track Copilot Credits and usage-based billing across Cowork, Code and Autopilot; set budgets, limits and model-family policies per user group; route credit requests through the customer's approval workflow; forecast spend and align seat additions, renewals and terms to each wave • Reported as: Reported as: Forecast versus actual variance; credits per active user; spend per business outcome; seats added; renewals completed on schedule • AI spend held within ±10% of forecast — no unplanned overage • Zero unused seats at renewal; 100% of renewals on schedule • Cost per outcome down 10–20% a year as usage matures Quarterly value reviews • Effort: 2 days a quarter • Activity: Refresh the business case (D1) with actuals, capture proof points in the customer's own words, agree and date the next named expansion wave with the executive sponsor • Reported as: Realised versus forecast value; proof points captured; next wave scheduled • ROI in dollars: ≈$125K a year of Copilot seats vs. $6M+ of time released • ≥3 quantified proof points in the sponsor's words each quarter • Each review dates the next wave: +100–300 seats or +1–2 agents a quarter Effort shown is indicative for an M-tier customer (1,500+ seats) and scales with seats and agents in scope, exactly as the engagement hours above do. Add the recurring rows together and one M-tier customer with three agents in production sustains roughly 9–10 partner days a month after the readout, before wave deployments and new agent or solution builds are counted. Every row pairs a number you can invoice against with a result the customer already cares about, which is what turns a recurring service into a renewable one and keeps you positioned as the customer's AI transformation partner as their ambitions grow. Each of these is a recurring, outcome-based service rather than a one-off project — and each keeps you positioned as the customer's AI transformation partner as their ambitions grow. Ready to Build Your Envisioning & POC Offer? Read the engagement terms in the Microsoft Commercial Partner Incentives Guide and download the delivery guide and pre-engagement planning resources. Confirm your eligibility for Microsoft Commercial Incentives engagements in Partner Center and align your delivery team on the five-phase model. Publish your offer in Partner Center as a professional service (Envisioning & POC) with a managed service follow-on (deployment, adoption and optimisation). Pick your first cohort — customers with 300+ Microsoft 365 seats and no clear Copilot or agent roadmap yet, then size each one to the right tier. Book the executive readout before Assess begins — so the conversion, proposal and wave 2 conversation is already on the calendar. The customers are already in your base. Publish the offer and open the conversation. Resources Frontier Accelerate for Copilot: Envisioning & POC | Microsoft Commercial Partner Incentives Guide Copilot Envisioning & POC — Delivery Guide Copilot Envisioning & POC — Pre-Engagement Planning The new Copilot is here: the opportunity for Microsoft partners
Dell PowerScale for Azure is now Generally Available
We're excited to announce that Dell PowerScale for Azure – Dell managed is now Generally Available (GA). Following a successful Public Preview announced at Ignite, PowerScale for Azure is now production-ready for enterprise workloads. Co-developed with Dell as an Azure Native Integration, this fully managed service brings Dell's proven scale-out NAS technology and the PowerScale OneFS operating system directly into Azure — delivering the performance and scale enterprises expect with the simplicity of Azure-native provisioning, management, and billing. The solution is purpose-built for modern, data-intensive workloads such as AI/ML pipelines, media & entertainment, electronic design automation (EDA), high-performance computing, backup & recovery, and enterprise content management. Product highlights Dell-Managed Service: A streamlined experience where Dell handles deployment, monitoring, maintenance, and upgrades — freeing IT teams to focus on higher-value initiatives. Azure-Native Experience: Provision, manage, and monitor PowerScale directly from the Azure portal, with full Azure Resource Manager (ARM) integration and unified billing on your monthly Azure invoice. Enterprise-Grade Durability: Data is distributed across multiple nodes within the cluster for high durability and fault tolerance. Advanced Protection: Space-efficient erasure coding plus SyncIQ asynchronous replication across sites keep data available even during outages. Secure Private Access: Integrates into your Azure Virtual Network (VNet) via VNet Injection, with data encrypted at rest using Microsoft-managed keys. Massive scale & multi-protocol: Up to 8.4PB in a single namespace with simultaneous NFS, SMB, and S3 support, powered by custom PMEM-enabled compute SKUs engineered for Dell Consider a large health system running PACS (Picture Archiving and Communication System) imaging archives, Electronic Health Record (EHR) data pipelines, and AI/ML diagnostic workloads on an on-premises Dell PowerScale cluster. As PACS volumes grow alongside demand for AI-driven diagnostics, the team wants to scale into Azure for GPU-accelerated model training without re-architecting their environment. With Dell PowerScale for Azure, they can provision the fully managed service directly from the Azure portal, giving clinicians, researchers, and applications low-latency multi-protocol access to the same global namespace across NFS, SMB, and S3. Since Dell handles deployment, monitoring, and upgrades, IT teams stay focused on patient outcomes rather than infrastructure, while enterprise-grade durability and encryption at rest help protect sensitive patient data. Availability Dell PowerScale for Azure is generally available through the Azure Marketplace and Azure portal (search for Dell PowerScale for Azure – Dell managed). GA is rolling out in waves, starting with US East, with additional regions coming online shortly. Get started Azure Marketplace: Dell PowerScale for Azure – Dell managed Microsoft Learn: Dell PowerScale – Azure Native Integrations Solution Brief: Dell PowerScale for Microsoft AzurePartner Blog | Build. Monetize. Scale. Frontier Accelerate for Marketplace launches to power software companies on Microsoft Marketplace
For software development companies building the next generation of AI-powered apps and agents on the Microsoft Cloud, getting a solution ready for customers is only part of the commercial journey. Publishing, becoming transactable, reaching customers, aligning with Microsoft sellers, and building Marketplace momentum all require different resources as their business progresses. Today, we are announcing the availability of Frontier Accelerate for Marketplace, a new Microsoft AI Cloud Partner Program experience that brings those resources into one connected journey, while providing updated benefits and additional value. The experience follows three stages: Build & Publish, where partners prepare their solutions for Microsoft Marketplace and transactability; Grow, where they turn Marketplace presence into customer acquisition, transactions, and early commercial momentum; and Differentiate, where they build on established Marketplace performance through deeper go-to-market engagement, benefits, and opportunities to further differentiate their solution. As partners progress, a unified Partner Center experience connects guidance, skilling, Marketplace resources, and milestone-based benefits to the stage their business has reached. Eligible partners can choose the level of engagement that fits their strategy: The no-cost experience provides self-service tools, guidance, skilling, and milestone-based benefits that expand as partners progress through the Marketplace journey and meet applicable performance milestones. Frontier Accelerate for Marketplace Premium is available for a fee and adds deeper Microsoft engagement and investment across the journey. Eligible Premium partners can access up to $30,000 in Azure sponsorship for eligible build and test activities, along with technical consultations and a named engagement manager. 1 As they move into growth, Premium partners also receive customer propensity scoring, immediate access to Partner Marketing Center Pro, and additional go-to-market guidance and benefits. Both experiences follow the same Build & Publish, Grow, and Differentiate journey, giving partners the flexibility to choose the level of guidance and investment that fits their business. Continue reading herePartner Blog | The new Copilot is here: The opportunity for Microsoft partners
AI at Work is entering a new phase as customers look beyond individual productivity gains to AI that can take on complex work, build solutions, and automate business processes. The next evolution of Frontier Transformation is about matching the right mode of intelligence to the task at hand. Today, Microsoft is advancing that vision with the new Copilot, an evolution of the Copilot app that connects the tools people rely on with the next generation of capabilities they'll need to build, customize, and scale AI across work. The Copilot app now includes three new capabilities: Home, where Chat and Copilot Cowork come together with the full power of Office; Code, powered by the same underlying technology as GitHub Copilot, extending solution-building to more knowledge workers; and Autopilot, a persistent, proactive, and personal agent that keeps working even when you're not. Together, these new capabilities expand what customers can do with Copilot and the platform partners can build on. We are also introducing platform innovations including Microsoft IQ, Microsoft Copilot Managed Runtime, and an evolving commercial model with usage-based billing and FinOps for AI. For Microsoft partners, the opportunity extends well beyond the product experience. Today's announcements advance Copilot across three connected dimensions: how people use AI, how customers adopt it commercially, and how partners build, extend, secure, govern, and manage it. That creates opportunities across AI advisory, security and governance, agent development and deployment, FinOps for AI, adoption and change management, software development, and ongoing managed services. Learn more about today’s product announcement from Jared Spataro, Chief Marketing Officer, AI at Work. (live 9/25) What is new and why it matters for partners One Copilot experience brings AI-powered work together The new Copilot gives people access to the right capability for the work they want to accomplish: Home is the new starting point, bringing Chat—for questions, lookups, and drafts—together with Cowork, where work is delegated and returned as a completed result. Within the Home tab, Office in Copilot brings the full power of Microsoft Word, Excel, and PowerPoint into the app, creating and updating real, editable files that stay live for the whole team. Code turns natural-language ideas into apps, dashboards, automations, and workflows, with Copilot Managed Runtime providing the governed hosting infrastructure to run and share them inside Microsoft 365. Autopilot, previously called Scout, is a cloud-hosted digital teammate with its own identity, memory, and workspace that takes on work and keeps it moving within the permissions and boundaries the organization sets. Together, these capabilities let people match the right tool to the job, while staying in the flow of work. For partners, this creates opportunities to move customers beyond assistive productivity into business process transformation, grounded in the organization’s own data, and governed by the permissions and controls IT already sets. Continue reading herePartner Blog | Build the skills to turn AI opportunity into customer execution
Customers are moving from AI interest to implementation. They want to understand where AI can create meaningful business value, which solutions fit the opportunity, and how to deploy, secure, govern, and scale those solutions with confidence. For partners, readiness now must extend across the customer journey. Sales teams need the skills to identify and position the right opportunity. Technical teams need the depth to design it. Delivery teams need practical experience to turn a promising AI conversation into a successful customer project. Building that capability takes time and investment, and you do not have to fund it alone. One of the best ways to get skilling is through partner benefits packages: bundled, discounted offerings of licenses, credits, and support that help your teams skill, build, and grow faster. Pair the learning journeys below with the benefits your organization is eligible for, and training turns into customer-ready delivery in the same quarter. This month’s skilling opportunities connect those capabilities. Whether you are building a Microsoft Copilot practice, expanding into agents, serving small and medium-sized business (SMB) customers, or developing deeper Frontier Transformation engineering expertise, the goal is the same: build skills you can apply in your next customer engagement. Build Copilot and Cowork skills around the customer opportunity Microsoft 365 Copilot Cowork creates new opportunities to connect AI with the work customers need to get done. For partners, the starting point is the customer scenario: where could delegated, AI-powered work create value, and what skills does your team need to take that opportunity from conversation to implementation? Continue reading hereLand Your Offer - Anatomy of Revenue Generating Partner Offer - Part 1 - Copilot in 30
Copilot in 30: A Ready-Made Marketplace Offer to Grow Your SMB Practice Thirty days. Twenty-five users. One repeatable offer that turns AI curiosity into a long-term customer relationship. Small and medium businesses know AI matters. What they lack is a trusted guide and a low-risk way to start. Copilot in 30 gives you both: a $0, 25-user, 30-day Microsoft 365 Copilot Business trial from Microsoft, wrapped in a structured journey that only a partner can deliver. Package it as a Microsoft Marketplace offer and you have a scalable on-ramp to every SMB customer in your base — and to the managed services that follow. Start Here: Why Publishing on Microsoft Marketplace Matters Microsoft Marketplace is Microsoft's partner-focused business platform, designed to help you reach more customers and simplify how you sell. A published offer gives your practice a permanent, discoverable storefront in the place customers already look for Copilot help. More importantly, an offer turns your expertise into something repeatable. Instead of scoping every engagement from scratch, you define the journey once — activities, timeline, deliverables — and run it across dozens of customers. Professional service and managed service offer types are available in Partner Center, so the same offer can carry both the 30-day journey and what comes after it. The SMB Opportunity Hiding in Plain Sight SMB customer segment is still early in their AI journey. These are organisations with 300 or fewer users on Microsoft 365 Business Basic, Standard or Premium — typically without an in-house AI team. That combination is exactly where partners win: high demand, limited internal capacity, and a customer base large enough that a well-designed, repeatable offer scales far beyond what bespoke projects can. Why Copilot Is the Right First AI Step for SMBs Microsoft 365 Copilot Business is the cost-effective Copilot add-on built for SMB customers, delivering the same capabilities as Microsoft 365 Copilot inside the apps their people already use — Outlook, Teams, Word, Excel and PowerPoint. No platform overhaul, minimal training, immediate relevance. Copilot is also the on-ramp. Once a team works confidently with Copilot, the natural next steps are agents, automated workflows and Copilot Cowork — each one deepening the customer's dependence on the partner who guided them there. Meet Copilot in 30: 25 Users, 30 Days, $0 Copilot in 30 is a limited-time, CSP partner-led Microsoft 365 Copilot Business trial for SMB customers with fewer than 300 employees. The essentials: What the customer gets: 25 Microsoft 365 Copilot Business seats for 30 days at $0, transacted through CSP New Commerce (Product ID CFQ7TTC0MM8R · SKU 006Z) Who qualifies: Customers on Microsoft 365 Business Basic, Standard or Premium with no paid Microsoft 365 Copilot today — one trial per customer How long it runs: Available to transact until 31 December 2026 What happens at Day 30: The trial auto-converts to a paid subscription unless renewal settings are changed, with a 7-day cancellation window What Microsoft provides: A launch kit, campaign materials, setup guidance, the Copilot Success Planner and conversion guidance Microsoft supplies the licences and the assets. The offer — and the customer relationship — is yours. Your Role: The Guide Who Turns a Trial Into a Habit A trial alone rarely changes behaviour. A guided trial does. Your job across the 30 days is to make sure 25 people experience real value in real work, and that the sponsor can see it. Before Day 0 — pick the right customers, become "Customer Zero" by using Copilot in your own business, secure a named sponsor and Copilot admin, and build a 30-day success plan with agreed measures. Day 0 — transact the trial, set the paid renewal quantity and term, complete admin setup, assign all 25 licences and run the kick-off with starter prompts. Days 1–28 — lead a weekly scenario (Outlook, Teams, Apps, Agents), review Copilot Analytics, re-engage low-activity users and capture proof points in the customer's own words. Days 29–30 — run the outcome and ROI review, confirm the paid offer and open the expansion and consumption conversation. Every touchpoint is partner expertise the customer cannot get from a licence alone — and every one moves the decision at Day 30 from "should we?" to "how much more?" Inside the Offer: Activities, Timeline and Deliverables Below is the full activity plan behind the offer, ready to drop into your own offer description or statement of work. ID Stage Activity Trial day (of 30) Key deliverables — Pre-req Customer eligibility (Copilot Business trial) Before Day 0 Active M365 Business base licence; no paid M365 Copilot; one $0 trial per customer; CSP New Commerce transactable; offer open to 31 Dec 2026 I1 Identify Build the prioritised target list Pre-trial Tier A/B target list from ASPX and Cloud Ascent; 50–300 eligible seats I2 Identify Confirm eligibility and trial fit Pre-trial Eligibility check: M365 Business base licence, no paid Copilot, one trial I3 Identify Launch the acquisition campaign Pre-trial Campaign email sent; briefing delivered; responses triaged into pipeline I4 Identify Be Customer Zero: complete microskilling Pre-trial Microskilling complete; internal Copilot experience; team briefed P1 Plan Confirm sponsor and success measures Pre-trial Named sponsor and admin; 25 trial users; agreed success measures P2 Plan Build the 30-day success plan Pre-trial Personalised Success Planner output; weekly scenarios; admin and user views P3 Plan Confirm technical and compliance readiness Pre-trial Minimum requirements verified; data and compliance review; blocker log A1 Activate Transact the trial in CSP New Commerce Day 0 25-seat, 30-day, $0 trial ordered (CFQ7TTC0MM8R · SKU 006Z) A2 Activate Configure the paid renewal settings Day 0 Renewal quantity, term and billing set; Cowork usage-based billing if in scope A3 Activate Complete admin setup and assign licences Day 0 Recommended settings on; 25 licences assigned (starts the clock) A4 Activate Run the kick-off and share starter prompts Day 0 Kick-off email; starter prompts; four-week prompt series scheduled X1 Experience Week 1 · Outlook — catch up and communicate Days 1–7 Week 1 prompts landed; first-week activation rate reviewed X2 Experience Week 2 · Teams — meetings that run themselves Days 8–14 Copilot Analytics checkpoint; recaps adopted; low-activity users re-engaged X3 Experience Week 3 · Apps — create in minutes Days 15–21 App scenarios and proof points; week 3 training gate before day 30 X4 Experience Week 4 · Agents — unlock the next level Days 22–28 Role-built agents trialled; 30-day usage trends from the admin centre C1 Convert Outcome review, paid offer and expansion plan Days 29–30 ROI review; 50-seat offer confirmed in 7 days; wave 2 plan; consumption conversation opened Land Your Offer: What One Customer Is Worth The table below is the revenue anatomy of one Copilot in 30 engagement — and it shows that the money is not in the trial, but in what the trial sets up. Item Value Detail Offer duration 30 days Trial clock runs Days 1–30; identify, plan and Day 0 setup precede it Trial offer 25 seats M365 Copilot Business · 30 days · $0 · one per customer · to 31 Dec 2026 CSP incentive — 25 seats (K) $0.32K 5.0% direct bill (2.5% M365 CSP Core + 2.5% Strategic Product Accelerator Tier 1) on 25 M365 Copilot Business seats x $21/mo† ≈ $6.3K/yr; indirect reseller 2.5% ≈ $0.16K Conversion target 50 seats Lead with 50 paid seats at conversion; sets up the wave 2 expansion plan CSP incentive — 50 seats (K) $0.63K 5.0% direct bill (Core + SPA Tier 1) on 50 M365 Copilot Business seats x $21/mo† ≈ $12.6K/yr; indirect reseller 2.5% ≈ $0.32K Frontier Accelerate deployment funding (K) $2.5K Microsoft Commercial Incentives funding for the Copilot deployment engagement when the conversion lands with 50 paid seats†; funds the deployment and adoption work that leads into managed services † Illustrative estimates from the offer plan. Confirm current incentive rates, funding and eligibility in Partner Center. Three streams stack on top of each other: CSP incentive — earned on every paid Copilot Business seat from the moment the trial converts, and growing again when the customer expands from 25 to 50 seats. Frontier Accelerate deployment funding — $2,500 available when you lead the conversion with 50 paid seats, paying for the deployment work that makes the expansion stick. Managed services — the recurring engagement described in Day 31 and Beyond, which is where the largest and most durable share of revenue lives. Now multiply. Everything above is the anatomy of a single customer. Landing the offer means running it across every eligible customer in your base — and you don't need to guess who they are. Partner Center's growth insights reporting, available through the AI Business Solutions & Security Insights (ASPX) dashboard, gives you account-level Copilot eligibility, seat whitespace, free Copilot Chat usage and adoption signals for the customers you already manage. To turn that export into a ranked target list, my colleague Brian O'Shea has built a Copilot for 30 Power BI dashboard that sits over your ASPX data and scores each customer on a 0–100 priority scale from eligible seats, whitespace, free-to-paid potential and opportunity signals — so your first cohort is the ten customers most likely to convert, not the first ten who reply. How the Offer Fits Together: From Trial Inputs to Proof of Value The offer runs left to right in three layers: Trial inputs — 25 users, 30 days, $0 CSP trial SKU; an SMB with 50–300 eligible Microsoft 365 seats; no paid Copilot today; a Business Basic, Standard or Premium base; one trial per customer to 31 Dec 2026; a named sponsor and Copilot admin; auto-conversion to paid unless changed. Five stages — Identify (I1–I4), Plan (P1–P3), Activate (A1–A4), Experience (X1–X4) and Convert (C1, T1, T2, W2). Each stage produces a concrete output the sponsor can see. Proof of value — a prioritised list and campaign responses; agreed use cases and success measures; a provisioned trial with 25 licences assigned; weekly usage from the Microsoft 365 admin centre; adoption proof points in the customer's words; paid conversion confirmed in Partner Center — and a named wave 2 expansion beyond the first 25. The highlighted activities — admin setup (A3), Week 4 agents (X4), 25→50 paid seats (T1), Frontier Accelerate funding (T2) and the wave 2 expansion plan (W2) — are where the engagement stops being a project and starts becoming an ongoing relationship: managed services, agent build-out, Copilot Studio and Copilot Cowork follow-on once the trial converts. Day 31 and Beyond: Managed Services That Keep Delivering The end of the trial is the start of the real engagement. Package these as standing services in your offer: Copilot adoption management — monthly Copilot Analytics business reviews, prompt and scenario refreshes, champion programme and onboarding for each new wave of users Licence and expansion management — take the customer from 25 to 50 paid seats and on to wave 2, aligning renewals, terms and billing as the footprint grows Agent build-out — design, build and maintain role-based agents with Copilot Studio for sales, service, finance and operations scenarios surfaced in Week 4 Copilot Cowork enablement and governance — introduce consumption-based Cowork scenarios, set budgets and cost controls, and report on usage each month Security, compliance and readiness — keep data protection, permissions and governance in step with expanding AI use, including a path to Microsoft 365 Business Premium Quarterly value reviews — refresh success measures, capture new proof points and agree the next expansion plan with the sponsor Each of these is a recurring, outcome-based service rather than a one-off project — and each keeps you positioned as the customer's AI partner as their needs grow. Ready to Build Your Copilot in 30 Offer? Download the Copilot in 30 launch kit and Microsoft 365 Copilot Partner FAQ from the Microsoft AI Cloud Partner Program. Be Customer Zero — run Copilot and the microskilling series inside your own business first. Publish your offer in Partner Center as a professional service (the 30-day journey) with a managed service follow-on (Day 31 and beyond). Pick your first cohort — customers with 50–300 seats on a Microsoft 365 Business plan and no paid Copilot today. Transact your first trial through CSP New Commerce (Product ID CFQ7TTC0MM8R · SKU 006Z) and set the paid renewal on Day 0. Book the Day 30 review before Day 1 — so the conversion and expansion conversation is already on the calendar. The window closes on 31 December 2026. The customers are already in your base. Publish the offer and start the clock. Resources From AI curiosity to Copilot adoption in 30 days — Microsoft Partner Blog Copilot in 30 Launch Kit — partner GTM playbook, customer trial guide, invitation and weekly prompt emails, admin setup guidance Build Your 30-Day Copilot Success Plan Copilot Success Planner Walkthrough video Partner Skilling Hub | Microskilling for Copilot in 30 Power BI Dashboard that integrates with your ASPXi Partner Data · By Brian O'Shea Create compelling customer business casesPartner Blog | Plan today, grow tomorrow: Turn partner investments into sustained demand
The customer journey is changing, and partners have more opportunities to influence technology decisions across it. But taking advantage of those opportunities requires more than individual campaigns or one-time investments. Recent Omdia research maps 28 critical presales touchpoints, with additional customer success opportunities after the sale. Yet 62% of partners surveyed invest 10% or less of their marketing budgets in demand generation. For FY27, we see three areas that can reinforce one another: build the expertise customers increasingly expect, invest in sustained demand generation around the challenges they need to solve, and apply those capabilities to opportunities such as Microsoft Copilot and Frontier Transformation. 1. Build the expertise customers increasingly expect As AI becomes part of more business decisions and processes, customers are looking for partners that can connect technology to specific industries, workflows, and business challenges. That makes skilling a business investment. Marketing teams need enough technical and industry fluency to communicate value clearly. Sales and presales teams need to connect customer priorities to solutions. Technical teams need the depth to design and deliver them, while customer success teams need the expertise to drive adoption and identify opportunities to extend value. Start with the customer opportunities you want to pursue, then identify where your teams need greater depth. The Microsoft Partner Skilling Hub provides partner-focused learning across Microsoft Cloud solution areas, roles, and technical certifications. For partners that have earned co-op, eligible Partner AI Adoption activities may also provide an opportunity to build AI capability within your own organization. Applying AI and agents to your internal workflows can give your teams practical experience that strengthens customer conversations. Review the current Microsoft Commercial Partner Incentives Guide for applicable eligibility and requirements. 2. Invest in sustained demand generation around customer challenges Expertise creates more value when customers can discover it throughout their buying journey. Omdia's research shows that buyers use sources ranging from AI tools and search engines to social media, events, peer groups, partners, review sites, and digital marketplaces. A single webinar, email, or paid activation is unlikely to carry that entire journey. That makes isolated tactics less effective than a connected program that builds relevance and trust over time. Continue reading herePartner Blog | Back at your desk? Start FY27 with the resources that matter most
A new fiscal year often begins before everyone is ready. If MCAPS Start for Partners arrived while you were wrapping up July, managing customer priorities, or taking some time away, now is a good moment to reconnect. What matters most is not whether you attended live, but what you do with the FY27 guidance from MCAPS Start now that you are back at your desk. As the new Microsoft fiscal year (FY27) gets underway, partners are turning their focus to planning, customer engagement, and execution. If MCAPS Start for Partners coincided with customer priorities, other commitments, or time away, now is a great opportunity to explore the guidance and resources available. Whether you joined the live sessions or are engaging with the content now, what matters most is having the insights and tools you need to make the year ahead a success. The MCAPS Start keynotes and sessions are available on demand, and the Microsoft Partner FY27 GTM Kickoff offers a deeper look at the year’s go-to-market priorities. Additionally, Microsoft has released new resources to help partners turn that strategy into action across skilling, benefits, Microsoft 365 Copilot, marketing, Microsoft Marketplace, cloud, AI, security, and partner operations. With brand new information and guidance, here is a practical way to get started. Start with the shift from kickoff to execution MCAPS Start for Partners established the direction for partners: build differentiated capability, go to market with greater reach, and align with Microsoft sellers to turn customer opportunities into business outcomes. The sessions from this event are now available on demand to watch and share with your team. The Microsoft Partner FY27 GTM Kickoff then dives into our priorities across AI Business Solutions, Commercial Cloud and AI, and Security. You can now play the session videos and download the presentations along with the transcripts. When it comes to Frontier Transformation, customers are moving from experimentation toward implementation, creating an opportunity for partners to connect their capabilities to real customer needs and measurable outcomes. A customer may need to modernize applications, infrastructure, or data before AI can scale. Another may be ready to build agents or redesign a business process. Others may be focused on Microsoft Copilot adoption, security, governance, or creating new AI-powered products and services. The right starting point reflects where each customer is along their AI journey and the outcomes they want to achieve. Pick the customer conversation you want to lead The Microsoft FY27 go-to-market approach is increasingly organized around customer conversations that connect foundational modernization with AI transformation. Frontier Accelerate provides a framework for thinking about that journey. Core Conversations focus on areas such as cloud and AI readiness, migration and modernization, data and platform modernization, security, and Copilot adoption. Frontier Conversations extend into emerging opportunities such as agentic AI and AI-powered business transformation. The question for partners is practical: Which conversations are you best positioned to lead today, and which capabilities will enable you to lead the next one? New research illustrates why that next conversation matters. In a Microsoft-commissioned Total Economic Impact™ study, Forrester Consulting modeled the potential Azure services opportunity for a composite small and medium-sized business (SMB) customer. The study estimated $23,278* in expected partner revenue over three years based on observed attach rates, compared with $95,000 in total potential services opportunity across the customer lifecycle. That broader opportunity spans Azure migration, data platform modernization and unification, and Azure AI and agentic solutions. The same pattern appears at enterprise scale. In a separate Microsoft-commissioned TEI study (download pdf), Forrester modeled approximately $3.0 million in expected partner revenue for a composite enterprise customer over three years, with a total potential partner opportunity of approximately $5.7 million. The research points to data platform modernization and unification, AI and agentic solutions, solutions development, and managed services as important areas for longer-term partner value. For partners, this reinforces the value of a land-and-expand approach. A migration can establish the cloud foundation and customer relationship. From there, partners can identify opportunities to modernize and unify data, introduce AI and agentic solutions, and provide managed services that create recurring value over time. The opportunity will vary by customer, but the progression gives you a way to connect today’s project with the customer’s longer-term transformation priorities. Continue reading herePartner Blog | FY27 is the year to execute on AI: A starting point for Azure partners
FY27 is the year to execute on AI. For Azure partners, that means moving more customer AI initiatives into production, modernizing the cloud, data, application, security, and governance foundations they depend on, and connecting those investments to outcomes customers can measure. Across the partner ecosystem, you are starting from different places. Some partners are already scaling AI solutions in production. Others are modernizing legacy environments, unifying data, or strengthening security and governance so customers are ready for what comes next. The opportunity is to understand where each customer is today and create a practical path forward. Microsoft has aligned FY27 customer conversations, go-to-market guidance, incentives, skilling, and partner resources around that goal. The focus is less on starting with a product and more on starting with what the customer is trying to achieve. In July, MCAPS Start for Partners and the Microsoft Partner FY27 GTM Kickoff laid out that direction. If you missed the events or want to revisit a specific topic, the content is available on demand: Watch MCAPS Start for Partners on demand Explore the Microsoft Partner FY27 GTM Kickoff The more important question now is what you do with that guidance. Turn customer priorities into Core and Frontier conversations Customers rarely begin by asking for a portfolio of technologies. They begin with a challenge, an ambition, or an outcome: modernize an aging application, make fragmented data useful, strengthen security, improve employee productivity, automate a process, or create a new customer experience. That is the starting point for FY27. Core conversations establish the foundation customers need to become AI-ready. Depending on the customer, that can mean modernizing infrastructure and applications, bringing data together on a governed platform, improving security, or establishing the controls required to operate AI with confidence. Continue reading hereBeyond Tokens: Rethinking AI Economics with Microsoft Foundry
Beyond Tokens: Rethinking AI Economics with Microsoft Foundry From the cost of intelligence to the value of outcomes Enterprise AI has an accounting problem. Executives expect agentic AI to return roughly 171% on investment, according to one widely cited survey. Yet McKinsey finds only about 39% of organizations can attribute any earnings impact to AI at all. Both numbers can be true at once — because the gap between them is not a technology gap. It is a measurement gap. For the first few years of generative AI, one number dominated the economics conversation: tokens. How many tokens did a model consume? What was the cost per million tokens? Could a smaller model perform the same task? Those questions mattered when enterprises were experimenting with AI. They are no longer enough as AI moves into production. An enterprise agent doesn't simply consume tokens. It reasons, retrieves context, invokes tools, calls APIs, verifies its work, retries unsuccessful actions and sometimes escalates exceptions to humans. The model call might cost pennies. The business outcome could cost considerably more. Which leads to an increasingly important question: What is the right economic unit for intelligence? From AI experimentation to economic accountability The first wave of enterprise AI was about possibility: Can AI do this? The next wave is about production, as AI becomes embedded in software engineering, customer service, finance, healthcare and supply chains. And production changes the question: Should AI do this and at what cost? Microsoft has moved decisively onto this ground. In August 2026, the Microsoft Foundry team launched its Economics of Agent Optimization series, arguing that "tokens have become the new unit of technology spend" and that AI should be run as a managed investment system. On the latest earnings call, Satya Nadella described Microsoft's objective as "advancing the frontier on the cost-to-outcome curve, ensuring every customer can turn tokens into business results." The discipline is going mainstream too: 98% of FinOps teams now manage AI spend, up from 31% two years ago. Microsoft's series is largely about the numerator of that curve - making every request, agent and dollar more efficient. This article is about the denominator: what an outcome is, what it truly costs, and what it is worth. The evolution of Microsoft Foundry reflects the same shift. At Build 2026, Microsoft expanded the conversation beyond building agents toward tracing behavior, evaluating quality, monitoring production performance, optimizing agents and connecting their operation to ROI. Think of the progression as: Trace → Evaluate → Monitor → Optimize → ROI This is more than a technology roadmap. It represents a shift from observing AI as technology to managing AI as an economic asset. Tokens became the unit of spend. They were never the unit of value. Consider two AI agents handling the same customer-service workflow. Agent A costs $0.08 per interaction. Agent B costs $0.20. Agent A appears cheaper. But suppose Agent A successfully resolves only 55% of cases, while Agent B resolves 90%. The remainder require retries, additional reasoning or human intervention. Which agent is actually cheaper? The inexpensive interaction may produce the expensive resolution. This illustrates a fundamental problem: We often measure AI where it is consumed rather than where value is created. Tokens are a unit of consumption. Businesses operate in outcomes. A customer-service leader cares about issues resolved. An engineering leader cares about high-quality software reaching production. A finance leader cares about reconciliations completed accurately. The economic denominator needs to move closer to the business. The AI Economic Ladder I think of this evolution as an AI Economic Ladder: Tokens → Interactions → Tasks → Outcomes → Value Each step moves measurement closer to what the enterprise actually cares about. At the token level: What intelligence did we consume? At the interaction level: What did each AI run cost? At the task level: What did it cost to complete the work? At the outcome level: What did a successful result cost? At the value level: Was the outcome worth creating? An AI system can become more efficient at every technical metric while creating little economic value. Conversely, an expensive AI workflow could be extraordinarily valuable if it prevents revenue leakage, reduces operational risk or accelerates a critical business process. The objective isn't cheaper AI. It is better economics. Not every completed task is a successful outcome There is another complication. If an agent completes a workflow, should we count it as a successful outcome? Not necessarily. A meaningful outcome needs three characteristics: Completed. Quality-gated. Attributable. It must reach its intended end state, meet an explicit standard for quality, accuracy, safety or business acceptability, and be attributable to the agent or workflow that produced it. That gives us a more meaningful measure: Cost per Successful Outcome = Fully Loaded AI Workflow Cost / Completed, Quality-Gated, Attributable Outcomes The denominator becomes real only when named in business language: cost per prior authorization resolved in healthcare, per pull request triaged and tested in engineering, per disputed invoice reconciled in finance operations. If you cannot name the outcome in a sentence the process owner recognizes, you are not ready to measure it. The quality gate matters. With AI, "the system ran successfully" and "the system produced a good outcome" are not the same thing. Microsoft Foundry's tracing and evaluation capabilities become economically important for precisely this reason. Evaluation isn't merely quality control. It helps determine what gets counted as value. What does an AI outcome really cost? The true economic footprint goes far beyond inference: Model + Reasoning + Grounding + Tools + Orchestration + Infrastructure + Retries + Evaluation + Governance + Human Intervention Human intervention is particularly easy to overlook. Every time someone must review, correct, approve or recover an AI-generated outcome, the economics change. The same applies to verification. An agent reaching an acceptable result in three steps has different economics from one requiring fifteen steps and multiple retries. And verification is not a rounding error — it is the bulk of the bill. McKinsey's 2026 analysis of production agentic workflows found roughly 60% of an agentic task's cost is tied to refining answers — checking, repairing, re-verifying — not generating the initial response. Most of what you pay for is not intelligence. It is assurance. This means quality and economics are connected. The quality bar you set influences the cost you pay. The challenge isn't simply minimizing consumption. It is finding the right balance between quality, cost, speed and risk. Cost per outcome is only half the equation Now imagine two agents. Both cost $5 per successful outcome. One saves an employee ten minutes of administrative work. The other prevents $500 in revenue leakage. Their cost efficiency is identical. Their economics clearly aren't. So we need to move another step up the ladder: from Cost per Outcome to Value per Outcome. The question isn't only how cheaply AI can complete the work. It is: How much economic value does this outcome create relative to the intelligence required to produce it? Now the CIO, CFO, CAIO and business leader have a common conversation. Give every outcome an Intelligence Budget Not every problem deserves the smartest model available. Classifying an email may require relatively little intelligence. Resolving a complicated customer complaint may justify more context and reasoning. Assessing the risks in a multimillion-dollar contract may justify sophisticated reasoning, multiple validations and human review. Every business outcome therefore has an economically rational amount of intelligence worth spending on it. Call it an Intelligence Budget. This changes the architecture question from which model should we standardize on, to: What combination of model, reasoning, context, tools and human judgment does this outcome deserve? This is where Microsoft Foundry's model router becomes interesting. Individual requests can be dynamically routed so simpler work doesn't consume the same model resources as complex reasoning. If the Intelligence Budget is the economic principle, intelligent routing is one way of operationalizing it. The future enterprise AI architecture won't be about one model doing everything. It will route intelligence according to the economics, quality and risk of the outcome. Making AI economics observable None of this works without visibility. An AI system can be technically healthy and economically unhealthy — responsive and error-free while repeatedly choosing inefficient reasoning paths, invoking unnecessary tools or producing outputs requiring expensive human correction. AI economics and AI observability are becoming inseparable. Microsoft Foundry increasingly connects these disciplines. Tracing shows what an agent did. Evaluation determines whether it met required criteria. Observability helps monitor production behavior. Agent optimizer can test improvements across prompts, skills and models. Microsoft's emerging ROI capabilities take the next step by connecting operating costs with measures such as task completion, time saved and cost efficiency. Attribution is the bridge to the finance conversation. Teams place Azure API Management in front of Foundry endpoints as an AI Gateway, stream token telemetry into Application Insights, and use Entra Agent ID to give every agent run a discrete identity that maps cost to its cost center. Microsoft Agent 365 extends the discipline tenant-wide — spending policies, budget caps and departmental chargeback across Microsoft and third-party agents. Together, they create something enterprises have historically lacked: A feedback loop between how intelligence is consumed and what that intelligence accomplishes. The paradox of cheaper intelligence There is another reason AI economics will become more important as models get cheaper. The Jevons paradox suggests that when technology makes a resource cheaper and more efficient, total consumption can actually increase. AI may experience the same effect. Cheaper intelligence enables more agents, more reasoning and more workflows that were previously uneconomic. So we could see cost per unit of intelligence fall while total intelligence consumed rises. Cheaper AI may therefore produce larger AI bills. That isn't necessarily bad — provided value grows faster than consumption. The objective isn't minimum AI consumption. It is maximum economic value from AI consumption. From workload economics to portfolio economics As AI scales, economics becomes a capital-allocation question. I see three levels. Workload Economics: Is this AI system running efficiently? Outcome Economics: Is it producing quality outcomes economically? Portfolio Economics: Where should we put our next AI dollar? That final question will become increasingly important. An enterprise with hundreds of AI initiatives shouldn't assume every one deserves continued investment. Some should scale. Some need optimization. Some should be redesigned or consolidated. And some should be stopped. The ability to experiment cheaply created the first explosion of enterprise AI. The discipline to allocate capital intelligently will determine what scales. Who owns AI economics? Once an agent becomes part of how work gets done, its economics cannot remain purely an IT metric. The business understands the value of the outcome. Technology understands the architecture and optimization levers. Finance brings economic discipline and comparability. That suggests a shared model: Business owns the outcome. Technology owns the optimization levers. Finance owns the economic discipline. AI economics ultimately isn't just a technology-cost conversation. It is a business-performance and capital-allocation conversation. From abundant intelligence to intelligent economics We are entering an era where intelligence is becoming an increasingly abundant, programmable and variable-cost resource. Microsoft Foundry and the broader Microsoft AI stack are making it easier to build, evaluate, observe, optimize and govern that intelligence. But abundant intelligence does not guarantee abundant value. Enterprises still need to decide where AI belongs, how much intelligence each problem deserves, what defines a successful outcome, when humans should remain involved and which AI investments deserve more capital. The winners won't necessarily use the cheapest models. They won't consume the fewest tokens. And they won't be the organizations that build the most agents. They will become exceptionally good at moving up the AI Economic Ladder: from consumption, to outcomes, to value. Because the next era of AI won't be won by organizations that buy intelligence most cheaply. It will be won by those that convert intelligence into value most efficiently. Where to start: the first 90 days Define the denominator for your top three agents — what counts as done, what quality gate applies, who signs off. Instrument attribution — Azure API Management as an AI Gateway, token telemetry to Application Insights, Entra Agent ID on every run. Wire evaluations into the cost pipeline so only quality-gated outcomes count. Set Intelligence Budgets — model router per request, agent optimizer against your evaluators, Agent 365 policies as circuit breakers. Stand up a joint monthly review — business, technology and finance on one dashboard: outcomes delivered, cost per outcome, value per outcome. Frequently asked questions What is Cost per Successful Outcome in enterprise AI? The fully loaded cost of an AI workload divided by outputs that were completed, quality-gated and attributable - for example, cost per prior authorization resolved or per pull request triaged. It turns token metrics into the unit economics of AI-performed work. What is an Intelligence Budget? The economically rational amount of intelligence - model capability, reasoning, context, tools and human review — worth spending on a given outcome, based on its value and risk. Model router in Microsoft Foundry is one way to operationalize it. Why do AI agents cost more than single model calls? One agent task can involve planning, tool calls, retries and verification - many model calls with compounding context. Research on production agentic workflows attributes roughly 60% of task cost to refining and verifying answers, not generating the first response. Will falling model prices make AI cost management unnecessary? No. By the Jevons paradox, cheaper intelligence expands consumption, so total AI spend typically rises as unit prices fall. The discipline that matters is maximizing value per unit of intelligence. Who should own AI economics? A shared model: the business owns the outcome and its value, technology owns the optimization levers, and finance owns the economic discipline and review cadence. #MicrosoftFoundry #Agent365 #AzureAI #FinOps #AgenticAI #AIAgents #Azure #MicrosoftCostManagement #AIEconomics #Tokens References Microsoft Azure Blog: "The Economics of Agent Optimization: From pilots to measurable returns" (August 12, 2026) Microsoft FY26 Q4 earnings call (Satya Nadella, July 2026) McKinsey — "Cost versus value: managing agentic AI system performance" (July 2026) FinOps Foundation — State of FinOps 2026; Microsoft Learn — Model router for Microsoft Foundry; Agent optimizer; Foundry Control Plane cost optimization
