D&H Channel Playbook: Copilot as the AI Entry Point for Storage and AI PCs

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D&H’s message to partners is blunt and practical: use Microsoft Copilot as the conversational entry point to sell AI, storage and PCs — and lean on distribution to deliver the infrastructure, security and services that make those Copilot projects real and repeatable. D&H Distributing’s senior vice president Jason Bystrak told the channel that Copilot is an “easy button” for accelerating adoption because thousands of partners already run Microsoft 365 and Azure, and that the real revenue opportunity for VARs and MSPs is the work that surrounds Copilot — data preparation, storage and security, plus PC refreshes to deliver the native AI experience.

Two suited men observe a glowing, swirling data portal at a futuristic exhibit.Background​

Who D&H is and why the channel is listening​

D&H Distributing is a North American reseller-focused distributor that has been aggressively expanding beyond client devices into cloud, data center and services through its Modern Solutions business unit and the D&H Cloud Marketplace. The company says fiscal results show dramatic, category-level growth — including triple-digit increases in professional services and strong growth in infrastructure, cloud and device categories — and D&H has rolled programs such as “Go Big AI” to train partners and surface AI-led opportunities.

Market context: PC refresh, Copilot momentum, Windows 10 end of support​

Two concurrent market forces are colliding to create a channel sales moment: (1) Microsoft’s Copilot wave — Copilot for Microsoft 365, Copilot Studio and the broader Copilot ecosystem — has given partners a concrete, business-facing product to demo and sell; and (2) the Windows 10 end-of-support calendar is forcing device refreshes and giving partners a clear hardware upsell path to premium AI-capable PCs. Microsoft’s official guidance states Windows 10 support ends October 14, 2025, which is driving migrations to Windows 11 and creating timing pressure for upgrades.
At the same time, PC vendors are shipping updated AI-enabled hardware and the market is rebounding after multi-year softness. Market trackers show Lenovo is the global leader in shipments and grew share in the refresh cycle — a dynamic partners should factor into inventory and OEM positioning.

Why Copilot is the right conversation starter — and what that really means​

Copilot is not a lab experiment anymore​

Copilot for Microsoft 365 is productized, integrated into Word, Excel, PowerPoint, Outlook and Teams, and sold as a paid add-on to Microsoft 365 subscriptions. It is promoted by Microsoft as a workplace assistant that combines large language models with user data held in the Microsoft Graph to generate summaries, drafts, insights and templates — functionality partners can demo for immediate productivity wins. That “out-of-the-box” narrative is what Bystrak means by the “easy button”: Copilot reduces friction to an initial AI use case because it plugs into systems many customers already use.

Copilot is also an integration project​

Behind the simplicity of the demo lies a set of technical dependencies that create business opportunities for partners: data hygiene, content indexing, storage capacity, access controls, sensitivity labeling, Purview policies, and often hybrid connectors or RAG (retrieval-augmented generation) pipelines. Copilot’s value is only as good as the data it can reliably access and the governance policies that prevent oversharing or compliance mistakes. Partners who understand that reality can upsell storage, backup, security, and consultancy. Microsoft’s Copilot guidance and Copilot Studio governance docs explicitly drive partners toward these readiness activities.

Data readiness and storage: the real revenue engine​

What “data readiness” actually covers​

  • Inventory and classification of content stores (SharePoint, OneDrive, Teams, network shares, line-of-business systems).
  • Clearing stale, redundant or trivial content so AI doesn't surface junk or outdated facts.
  • Applying sensitivity labels and DLP rules to prevent Copilot from exposing regulated or confidential data.
  • Deciding where to store indexed content and how much nearline/on-premise capacity is required for performance.
  • Establishing retention, audit and access-control policies tied to compliance needs.
Microsoft’s Copilot and Copilot Studio guidance emphasize discovery, classification, and Purview-driven governance as a first phase before wider Copilot rollouts. Those activities frequently surface additional infrastructure requirements: tiered storage for searchable indices, backups for continuity, encryption keys for regulatory compliance, and secure connectors for enterprise systems.

Storage designs partners should be selling​

  • Short-term, high-performance storage for indexed content that powers prompt responses.
  • Cost-tiered object storage for long-term archival, legal hold and compliance retention.
  • Hybrid designs that keep sensitive datasets on-premises while allowing secure metadata queries or RAG orchestration.
  • Managed backup and rapid restore solutions integrated with Purview sensitivity labeling to ensure encrypted files remain protected in transit and at rest.
These are tangible products: SAN/NAS arrays, HCI nodes, cloud object buckets with lifecycle policies, encrypted backups, and the orchestration scripts and connectors needed to integrate them into Copilot Studio and Microsoft 365. Each of these elements is a standard infrastructure sale multiplied by governance and professional services revenue.

Security, governance and compliance: not optional​

Governance is baked into Microsoft’s Copilot story​

Microsoft explicitly architects Copilot with governance controls: Customer Lockbox, Purview sensitivity labels, DLP integrations, tenant-level admin restrictions, and Copilot Studio features to restrict or audit agent behavior. Copilot Studio’s security guidance calls for stakeholder alignment (IT, security, legal), compliance reviews and explicit decisions about which data sources agents may or may not use. Partners should position governance as a core professional service offering.

Practical security sell points​

  • Implement Purview classification and DLP policies before Copilot pilots.
  • Configure sensitivity labels across SharePoint and OneDrive to protect “data in use.”
  • Leverage Copilot interaction export APIs and logging to capture prompts, responses and data pointers for audits.
  • Build role-based access controls and minimal-privilege connectors for external systems.
  • Offer continuous compliance monitoring as a subscription.
These are enduring, recurring revenue items — not one-off professional services — because policy tuning, audit reports, and data hygiene are ongoing work.

AI PCs: the finishing move in the sales cycle​

Why AI-capable PCs matter now​

Copilot+ PCs (the new generation of AI-native Windows devices) and OEM AI feature sets are designed to provide local inference acceleration, better multimodal experiences, and improved battery/latency trade-offs for on-device AI tasks. For customers upgrading from Windows 10 — particularly organizations with knowledge workers who will use Copilot heavily — a “Copilot-ready” or AI PC is a natural upsell. Partners can position device refreshes as a final user-experience optimization after infrastructure and Copilot readiness are in place.

What to sell with an AI PC upgrade​

  • Premium Copilot-enabled laptops with NPUs or specialized silicon.
  • Deployment and migration services (Windows 11 upgrades, bitlocker and TPM enablement).
  • Device management and remote support (MDM, zero-touch provisioning, remote security features).
  • Training for end-users to accelerate adoption and show ROI quickly.
Lenovo, HP and Dell — the OEMs who dominate shipments — will be critical inventory partners for distributors and resellers focused on refresh cycles. Channel planning should align OEM promotions and finance offers with Windows 10 migration calendars to maximize conversion.

The partner playbook: a practical five-step approach​

  • Discovery and readiness assessment
  • Run a Copilot readiness workshop: inventory data sources, map sensitive content, and produce a prioritized remediation roadmap. Use Microsoft’s Copilot readiness frameworks and tenant-scanning tools.
  • Quick pilot with a high-value use case
  • Pick one department (sales, HR, customer service) where Copilot delivers quick wins and measurable time-savings.
  • Implement governance and storage backbone
  • Deploy Purview, sensitivity labels, DLP policies and the proper storage tiers required by the pilot.
  • Scale to production and add AI PCs
  • Roll out Copilot across the organization, upgrade client devices where needed, and add endpoint security and management.
  • Convert to managed services and continuous improvement
  • Offer governance tuning, content curation, model monitoring, and Copilot interaction audits as a subscription.
This stepwise approach reduces risk, creates sequential billable milestones, and converts pilots into long-term managed revenue.

Opportunities for resellers and distributors​

  • Infrastructure sales: storage arrays, backup appliances, HCI, cloud object storage and hybrid connectors.
  • Security and compliance: Purview integration, DLP tuning, sensitivity labeling projects and compliance reporting.
  • Professional services: data cleanup, content de-duplication, taxonomy and metadata projects.
  • Device refresh: Copilot+ PC sales, trade-in programs, device-as-a-service (DaaS) financing.
  • Managed services: ongoing governance, prompt-tracking audits, model usage analytics and continuous training.
D&H’s own results reflect this pattern: the distributor reports rapid growth in data center and services categories and has packaged enablement (Cloud Marketplace, Go Big AI, Success Path) to help partners capture these adjacent sales. That alignment between a distribution go-to-market and the partner playbook is why distributors are positioning Copilot as a channel accelerator.

Risks, limits and caveats partners must sell honestly​

Data quality and hallucinations​

AI copilots are highly sensitive to the quality of the underlying content. Low-quality, stale or contradictory documents can produce confidently wrong outputs. Partners must manage expectations and document the limits of generative AI — model hallucinations remain a practical risk in production deployments.

Cost and complexity​

Indexing large corporate archives, running continuous RAG queries, licensing premium Copilot tiers and increasing storage and network egress can add unexpected costs. Partners should present a total-cost-of-ownership model that includes recurring storage, compute and governance personnel costs.

Regulatory and privacy concerns​

In regulated industries, data residency, consent and auditability are non-negotiable. Some customers will need on-premise, non-ingested RAG patterns or strict connector policies; these requirements change architectures and pricing.

Vendor and model lock-in​

Tightly coupling a customer to a single stack (Copilot + specific cloud storage + proprietary connectors) simplifies implementation but can create migration headaches later. Where possible, recommend modular architectures and escrowed metadata strategies.

Change management and adoption​

Even the best Copilot pilot will deliver limited value without user training, governance, and a change plan. Partners who ignore this will see weak adoption and churn.
Microsoft documents and third-party readiness vendors all stress governance-first rollouts — partners who sell the promise without operational rigor risk failed projects and reputational damage.

Tactical checklists — what to configure first​

  • Enable tenant-level Copilot admin controls and define who can publish agents.
  • Deploy Purview classification and map sensitivity labels to business processes.
  • Run a content hygiene sweep: archive or delete stale SharePoint sites and unused Teams channels.
  • Plan storage tiers: hot index storage for active search, warm/cold for archival and cost control.
  • Configure Copilot interaction export and logging for audit and troubleshooting.
  • Bundle training and a 90-day post-deployment tuning engagement as a managed service.
These items transform a pilot into a repeatable, auditable service offering.

How distributors like D&H change the equation​

Distributors play a unique role in this cycle by bundling hardware, soft- ware, finance and partner enablement into cohesive offers. D&H’s marketplace, training programs and vendor relationships help solution providers:
  • Shorten procurement cycles for combined infrastructure + Copilot bundles.
  • Access vendor promotions and financing that make higher-ticket AI PC and infrastructure sales feasible.
  • Gain enablement and professional services playbooks to accelerate deployments.
D&H’s stated growth in infrastructure and professional services demonstrates that channel ecosystems built for integrated sales — not just hardware reshipments — capture the highest-margin opportunities in AI deployments.

Bottom line and next steps for partners​

Microsoft Copilot is the conversational handhold partners can use to take customers from curiosity to a structured AI program. But the real and recurring revenue is in the work that turns that conversation into an operational system: data readiness, storage design, governance, device refresh and managed services.
A practical partner GTM should:
  • Lead with a Copilot workshop that surfaces business outcomes.
  • Sell governance and storage as prerequisites, not optional extras.
  • Bundle Copilot pilots with an AI PC upgrade path for users who require the best desktop experience.
  • Convert pilots into managed services that monitor, tune and justify ongoing spend.
The window of opportunity is time-limited: Windows 10’s end of support creates a natural calendar for device and client migrations, and vendors and distributors already report stepped-up shipments and demand. Partners who get the data, storage and governance pieces right — and who tie device refresh to measurable productivity metrics — will win the lion’s share of the revenue that follows the Copilot conversation.

D&H’s pitch to the channel is straightforward: use Copilot as the doorway to AI, but sell the infrastructure and governance that keep that door open — and make every Copilot sale the start of a longer, recurring managed-services engagement rather than a one-off license or laptop sale.

Source: CRN Magazine D&H’s Jason Bystrak To Partners: Microsoft Copilot Great Way To Talk AI, Storage And PC With Customers
 

Microsoft's latest Copilot Labs experiment is pushing the assistant further down the road from utility toward companionship: a new feature called "Portraits" lets you speak to an animated 2D portrait while Copilot listens and responds. The announcement—part of ongoing Lab tests rolled out to limited geographies and to Copilot Pro subscribers—signals a deliberate move to add nonverbal cues to voice interactions, with the explicit aim of making conversations feel less awkward and more natural.

Holographic video-chat overlay with a smiling woman avatar in a modern office.Background​

Over the last year Microsoft has been steadily expanding Copilot beyond text output into voice, vision, memory and personalization. That shift accelerated through a series of experimental features grouped under Copilot Labs, a testing ground where Microsoft tries new interaction models with tighter guardrails and limited audiences before broader release. Copilot Labs already contains features such as Copilot Vision (which can analyze your screen or camera input in real time) and "Think Deeper" (which takes extra time to produce more reasoned answers). Portraits joins a family of experiments intended to make Copilot feel more like a partner and less like a faceless tool.
Two distinct UI threads are now visible in Microsoft’s consumer Copilot work:
  • Appearance / Avatars — more elaborate, often 3D or animated characters that emote in voice conversations (a blob-like avatar has been sighted in early previews).
  • Portraits — a simpler, voice-synced 2D portrait that offers facial reactions and lip-sync for conversational voice sessions.
Both are delivered through Copilot Labs and are currently experimental and regionally staged. Many of the Labs features — including Portraits — are gated behind Copilot Pro, Microsoft’s paid tier for consumers (the company’s store lists Copilot Pro at $20 per user per month).

What Portraits is (and isn't)​

A quick, practical description​

Portraits is essentially a voice-first UI skin for Copilot: when you speak, a static portrait animates in real time to match audio cues — lip movement, nods, smiles, slight head turns and emotional micro-expressions — producing a face that appears to be listening and reacting.
Key functional characteristics being tested:
  • The portrait is 2D rather than a fully manipulable 3D avatar.
  • Animation is driven by audio input in real time so lip-sync and timing feel immediate.
  • The experience is opt-in and limited through Copilot Labs, not a default on all Copilot sessions.

How Portraits differs from Copilot Appearance​

The company is testing multiple visual approaches. The broader “Appearance” experiments have included more whimsical or 3D avatars — animated characters that can emote and gesture in a richer way. Portraits seems to be a sibling feature: simpler, faster to render, and conceptually closer to the idea of "talking head" interfaces rather than a fully embodied 3D companion.
Practical implications:
  • Portraits will likely be cheaper to compute and easier to deliver on a wide range of devices.
  • Appearance/avatars can be more expressive but may require heavier rendering and stricter policy controls for misuse.
  • Portraits may act as a stop‑gap: a lower-friction way to add the psychological benefits of a face without building an entire avatar ecosystem.

The technology under the hood: VASA‑1 and real‑time animation​

The animation capabilities being tested are rooted in recent research out of Microsoft Research: a model family called VASA-1 (Visual Affective Skills Animator). VASA‑1 was built to generate lifelike talking faces from a single still image and an audio track, producing synchronized mouth shapes, natural head motion and subtle affective behaviors at interactive frame rates.
Technical highlights of VASA‑1 worth noting:
  • It operates from a single image plus audio, rather than requiring a corpus of video of the same person.
  • The model is optimized for low latency and can generate 512×512 video at interactive frame rates (research demonstrations reported up to ~40 FPS).
  • It is designed to add affective behaviors — micro‑expressions and head gestures — that improve the sense of naturalness in conversation.
  • Microsoft has emphasized caution with the public release of raw VASA capabilities because of impersonation and deepfake risks; the research was published with limitations on public tooling.
That research background explains why Portraits can feel fluent: the generation is audio‑driven, allowing lip-sync and emotional cues to be tightly aligned to the user’s speech. But the very strengths that make VASA‑style animation convincing are the same that raise safety and abuse concerns.

Why Microsoft is trying this: UX, social friction, and the psychology of faces​

There’s a long literature in human-computer interaction showing that people respond to faces and nonverbal cues at speed. Microsoft’s internal user feedback and product leadership have indicated a consistent observation: many people find voice-only interactions with an invisible assistant slightly awkward. A face — even a stylized one — provides immediate social signals:
  • It cues turn-taking and listening behaviors naturally.
  • It provides visual reassurance that the system is engaged.
  • It reduces the cognitive load of interpreting voice-only responses and can modulate perceived warmth and trustworthiness.
From a product point of view, adding a lightweight portrait is a low-friction way to make voice interactions feel more conversational and approachable, particularly for moments that benefit from coaching, practice or emotional expression (for instance, interview coaching, language practice, or role-play).

Privacy, safety and misuse: the uncomfortable trade-offs​

Animating a face in real time raises serious concerns that need clear guardrails. The same technology that enables a friendly portrait can be repurposed to impersonate, deceive or harass.
Primary risk vectors:
  • Impersonation and deepfakes: A single photo plus audio can create convincing speaking footage of a real person. That ability is precisely what prompted caution in the research community when VASA‑style models were introduced.
  • Unauthorized likeness use: If a user can upload or select a portrait that resembles a real person, that likeness could be misused to create false statements or simulate interactions without consent.
  • Emotional manipulation: Animated faces can subtly influence how people feel and behave. A design that overplays empathy cues might lead users to treat Copilot as a human advisor in situations where it’s not appropriate.
  • Privacy leakage: Voice and portrait sessions may contain sensitive data. Depending on where animation and speech processing occur (on device vs cloud), there are different exposure surfaces for that data.
  • Normalization of synthetic presence: As users become accustomed to friendly faces for assistants, there’s a risk of substituting genuine human contact with synthetic interactions for vulnerable individuals.
Safety mitigations that should be required:
  • Default opt‑out; explicit per‑session consent for portrait use.
  • Strict prohibitions on uploading real people’s images without documented consent.
  • Technical watermarking or provenance signals so synthesized video is identifiable as synthetic.
  • Age gating and stricter controls for minors.
  • Rate limits and usage caps to prevent mass generation of impersonations.
  • Heavy policy enforcement around likenesses of public figures.
Microsoft’s cautious Copilot Labs approach — limited rollouts, small test groups, and experimental gating behind a paid tier — suggests it is attempting to iterate with conservative guardrails. But that sandboxed testing doesn’t remove the need for robust, baked-in controls when a feature scales.

Accessibility and inclusion: design pitfalls and opportunities​

Portraits could be a net positive for accessibility if done right. Nonverbal cues can help deaf‑adjacent users or people with cognitive differences by making turn-taking clearer. But there are pitfalls:
  • Faces can encode cultural signals and biases; a limited set of portraits risks stereotyping or excluding identities.
  • Lip-sync quality and speech recognition need to support diverse voices and accents; otherwise the portrait will “misread” certain users and produce awkward or incorrect animations.
  • Motion or flashing effects may cause discomfort or trigger seizures in sensitive users; accessible options must be available.
Design recommendations:
  • Provide a broad and diverse portrait library with inclusive representation and adjustable expressions.
  • Offer a “low‑motion” or “static” option for users sensitive to animation.
  • Ensure speech processing and lip-sync have high accuracy across accents and speech patterns, and make transcription visible to the user.

Product and business implications​

Portraits being tested inside Copilot Labs and behind Copilot Pro signals two things: Microsoft is treating this as an experimental premium capability, and it sees customization/personalization as a monetizable axis of Copilot.
Business implications:
  • Gating experimental UI features behind paid tiers helps limit early exposure and funds R&D costs, but it also concentrates risk among paying users and might fuel perception that personalization is a premium commodity.
  • If animated faces improve engagement metrics (session length, voice usage), Microsoft stands to lock more daily interactions into Copilot, which strengthens the platform’s position in consumer AI.
  • There’s an ecosystem opportunity for third‑party portrait styles, skins or licensed character packs — provided policies can manage impersonation risk.
From a policy standpoint, monetization should never be used as an excuse to delay strong safety features. If something is high-risk, it must be mitigated regardless of revenue considerations.

Open questions and unverifiable claims​

Some details circulating about the Portraits experiment have not been officially confirmed and should be treated cautiously:
  • Reports of a fixed catalogue size (for example, “40 portraits”) and hard daily time caps (for example, “20 minutes per day”) come from preliminary or leaked summaries and are not yet confirmed by official product documentation.
  • Availability windows and regional rollout specifics are being phased; expectations for immediate broad availability are likely premature.
When reading early reports, assume Microsoft may change feature counts, limits and guardrails rapidly as it collects user feedback.

Best practices Microsoft should adopt (and what users should demand)​

If Portraits and similar visual companions are to ship at scale, they should follow a safety-first checklist:
  • Consent by design: Every portrait session must be opt-in with clear explanation of what data will be used and where it will be processed.
  • On‑device processing where possible: Keep raw audio and animation local to reduce exposure risk and limit server-side retention.
  • Provenance watermarking: Produce a visible or encoded signal in the animation that marks it as computer-generated.
  • Likeness protections: Disallow uploads of real people’s photos without robust consent flows and identity checks.
  • Transparent privacy settings: Users should be able to delete portrait-related data and review any stored clips or transcripts.
  • Accessibility modes: Provide simplified, low-motion, and captioned experiences.
  • Independent audits: Submit models and pipelines to third‑party audits for bias, safety and privacy compliance.
  • Clear escalation paths: Provide easy reporting for misuse and fast takedown for impersonation complaints.
Users should demand transparency about how portraits are generated, how long data is retained, and whether any generated content is stored or used to further train models.

What this means for Windows and Copilot as a platform​

Portraits is emblematic of Copilot’s strategic pivot: Microsoft is building an assistant that is multimodal, persistent, and — increasingly — personalized. For Windows users, this trend suggests Copilot will not remain a text box in a browser but will be woven into the desktop experience as a more social agent.
Potential platform impacts:
  • A face for Copilot can increase voice adoption on Windows, especially for tasks where hands‑free interaction is advantageous.
  • Integration with Windows features like accessibility, notifications and the taskbar will require careful UX work to avoid distraction and preserve user control.
  • Enterprise adoption will lag consumer experimentation unless enterprise-safe controls (data governance, Entra/IT overrides) are in place; Microsoft historically segments consumer features from enterprise-approved experiences for this reason.

The cultural and ethical angle: are we comfortable talking to synthetic faces?​

This is not purely a UX problem — it's a cultural one. Humans are wired to anthropomorphize. Adding facial animation to AI assistants leverages that wiring for engagement; it also complicates boundaries between machine and personhood. Product teams must balance emotional engagement with clear signals that the assistant is non-human and its outputs are computationally generated.
Companies should avoid intentionally deceptive design: avatars should not feign emotions in a way that obscures the assistant’s limitations, nor should they encourage users to disclose sensitive information under the impression they are interacting with a human confidant.

Conclusion​

Portraits represents a logical, technically feasible step for Copilot: adding a visible listening face reduces conversational friction, increases perceived warmth, and can make voice interactions more natural. Behind the scenes, advances like Microsoft Research’s VASA‑1 make such animation compelling and real‑time.
But the benefits come with clear responsibilities. Real-time talking portraits raise the specter of impersonation, emotional manipulation and privacy leakage. Microsoft’s current approach — testing in Copilot Labs, limiting access, and gating parts of the work behind Copilot Pro — is a pragmatic early posture. It must now be matched with durable technical safeguards, transparent policies and accessible controls before a broader release.
For Windows users, this is the next frontier of Copilot: not only smarter answers, but a face that listens. The crucial questions are not whether the technology can animate a portrait convincingly — it can — but whether companies will ship it with the protections that keep people safe, informed and in control.

Source: Windows Central Microsoft thinks animated portraits will make talking to Copilot feel less awkward
 

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