Zack Glaser’s conversation with Ben M. Schorr on the Lawyerist Podcast cuts through the hype and delivers a pragmatic roadmap for putting Microsoft Copilot to work in law firms today, emphasising immediate productivity gains, the critical role of tenant-aware governance, and the non‑negotiable need for human verification before any AI‑assisted material is relied upon or filed.
Microsoft 365 Copilot is positioned as a productivity assistant embedded directly into the Microsoft 365 applications lawyers already use—Word, Outlook, Teams, SharePoint and OneDrive—so it can synthesize mail, calendar events and document content the same way a human employee would, subject to the same access permissions. That combination of deep app integration and tenant‑aware access is what makes Copilot practically attractive to law firms, and it is also what demands careful governance. Ben Schorr, an innovation strategist at Affinity Consulting Group and a former Microsoft content lead, frames Copilot as an aid for four everyday legal workflows: create/edit (drafting and co‑authoring), ask/summarize (rapidly priming a lawyer on a long or complex document), extraction (deadlines, clauses, obligations), and business‑of‑law tasks (inbox triage, meeting prep). His core message: use Copilot to accelerate first drafts and low‑risk tasks, not to replace lawyer judgment on legal research, filings or authoritative citations.
Source: Legal Talk Network From Hype to Practice: Using Microsoft Copilot in Your Law Firm, with Ben Schorr - Legal Talk Network
Background / Overview
Microsoft 365 Copilot is positioned as a productivity assistant embedded directly into the Microsoft 365 applications lawyers already use—Word, Outlook, Teams, SharePoint and OneDrive—so it can synthesize mail, calendar events and document content the same way a human employee would, subject to the same access permissions. That combination of deep app integration and tenant‑aware access is what makes Copilot practically attractive to law firms, and it is also what demands careful governance. Ben Schorr, an innovation strategist at Affinity Consulting Group and a former Microsoft content lead, frames Copilot as an aid for four everyday legal workflows: create/edit (drafting and co‑authoring), ask/summarize (rapidly priming a lawyer on a long or complex document), extraction (deadlines, clauses, obligations), and business‑of‑law tasks (inbox triage, meeting prep). His core message: use Copilot to accelerate first drafts and low‑risk tasks, not to replace lawyer judgment on legal research, filings or authoritative citations. What the Podcast Shows — Clear, Verifiable Takeaways
- Copilot is Microsoft’s productivity AI built on Azure OpenAI models and integrated tightly with Microsoft Graph; it uses tenant data (what a user already has access to) to ground responses, rather than exposing firm content to arbitrary public LLM endpoints. This means Copilot inherits Microsoft 365 access controls and enterprise protections—but those protections must be configured correctly by the tenant admin.
- Tenant data handling and retention are configurable but non‑trivial. Microsoft documents make explicit that prompts, retrieved data and generated responses are processed inside the Microsoft 365 boundary, use Azure OpenAI services, and are subject to retention and deletion policies the tenant can influence; some Copilot telemetry or derived data may be retained according to product policies unless explicitly configured otherwise. These are implementation details IT must confirm before subject matter data is used.
- Practical value is immediate, measurable and role‑dependent. Routine, document‑heavy work—first drafts, summaries, transcription digestion, and triage—shows the most reliable time gains. Creative, discretionary legal research relying on proprietary services (Lexis, Westlaw) is still best done witsearch tools rather than Copilot alone.
- Risk is real and consequential. Courts and commentators have documented multiple incidents where AI hallucinations produced fabricated authorities and led to court sanctions or disciplinary attention—this transforms AI hygiene from “nice to have” to an ethical, professional duty.
- Governance and training are the primary levers that determine whether Copilot is an accelerant or an exposure. Tenant grounding, Purview labeling, Conditional Access/Entra policies, Endpoint DLP and exportable logs are foundational; human‑in‑the‑loop verification and role‑based competency gates are operationally essential.
Why Copilot Fits Law Firms — Strengths and Immediate Use Cases
Deep Microsoft Stack Integration
Copilot’s integration with Microsoft Graph and the Office applications means it can synthesize an attorney’s mailbox, meeting transcripts and matter files to produce context‑aware drafts, brief summaries and task lists without switching platforms. For firms already standardised on Microsoft 365, that reduces friction and amplifies value fast.High‑Frequency, Low‑Risk Wins
- Rapid first drafts of letters, non‑substantive memos, client updates and internal status reports.
- Meeting prep and post‑meeting minutes from Teams transcripts, with action items mapped to owners.
- Inbox triage: prioritising and summarising email threads to accelerate time‑to‑response.
- Extraction tasks: deadline tables, key obligation lists, and contract clause inventories.
Democratization of Expertise
Copilot can level the starting point for juniors by providing polished first drafts and syntheses that enable earlier, higher‑value reviews with partners. Firms that pair Copilot with verification training find juniors can add value faster—provided the firm redesigns learning so juniors still gain essential reasoning experience.Where Copilot Must Be Treated with Caution
Hallucinations and Fabricated Authorities
Generative models can produce fluent but false facts—including invented case citations—that have led to real judicial fallout. Courts have rebuked or sanctioned lawyers for subake authorities; these incidents make verification an ethical and compliance issue, not merely a best practice. Relying on Copilot for primary legal research without cross‑checking against validated databases invites malpractice exposure.Shadow AI and Data Exfiltration Risk
Shadow or consumer AI use remains a persistent problem. Pet tools like free chatbots or personal AI subscriptions can be used by staff outside governance, creating uncontrolled data flows. Even with Copilot’s tenant protections, improper connector settings or lax DLP can expose sensitive matter data. Recent industry analysis also warns that many organisations expose millions of sensitive records through poor sharing practices—Copilot will surface and process that data if it is accessible.Deskilling and Training Erosion
When drafting and redlining become AI‑assisted, junior lawyers may lose formative experiences that build legal judgment and citation craft. Firms must intentionally redesign training curricula and create competency gates so automation augments learning rather than replacing it.Cost and Consumption Surprises
Copilot licensing and metered agent/message models can create unexpected costs if consumption is not monitored. Firms must model low/medium/high consumption scenarios during pilot and include agent/message costs and inference compute in TCO calculations.Technical Verification: What IT Should Confirm Before Enabling Copilot on Matter Data
The following claims are technical and must be verified against your tenant and contractual documentation before matter‑level use:- Copilot processes prompts and retrieved Microsoft 365 data within the Microsoft 365 service boundary and Azure OpenAI services; ensure your tenant settings, Purview policies and Copilot opt‑ins align with firm data protection rules.
- Microsoft’s enterprise commitments state that Microsoft 365 Copilot won’t use customer content to train foundational models; nevertheless, telemetry and some session metadata have retention policies that vary by product—confirm deletion guaranteand whether any telemetry may be used for product improvement unless explicitly opted out.
- Uploaded files used in some Copilot experiences may be stored in the tenant’s chosen workspace geo, but extracted content used during session generation can be stored and processed according to product retention policies—confirm this behaviour for the specific Copilot SKU you plan to deploy.
- Agents and third‑party connectors can extend Copilot outside the tenant scope; review the privacy statements of any agents and enforce connector‑level controls for matter‑sensitive work.
A Practical Implementation Roadmap for Law Firms
Use a staged playbook that treatts Copilot as both a technical and people‑change project.Phase 0 — Preparation (0–4 weeks)
- Establish a cross‑functional steering group: partners, IT/security, procurement, KM, ethics counsel and pventory content sources: SharePoint sites, Teams channels, OneDrive stores and their access lists; classify matters by sensitivity and client confidentiality.
- Map legal/regulatory constraints for clients and jurisdictions (data residency, PD laws).
- Confirm licensing needs with procurement.
Phase 1 — Pilot (4–12 weeks)
- Select 3–10 representative users and a single low‑risk workflow (meeting prep, transcript summarization or inbox triage).
- Configure tenant controls: Conditional Access, Entra view sensitivity labels and Copilot grounding in admin console.
- Enable Copilot in monitor‑only or read‑only mode where possible; collect prompts/responses for QA.
- Require mandatory human sign‑off for any outward‑facing draft; document vthe matter file.
Phase 2 — Evaluate & Harden (3 months)
- Measure KPIs: average partner review time, time to first‑draft, error rate on AI‑assisted docs, and verification competency pass rates for associates.
- Harden contracts: insist on no‑retrain/no‑use clauses for matter data, deletion guarantees, exportable logs and SOC/ISO attestations.
- Build playbooks for common prompts and approved templates (approved prompt library).
Phase 3 — Scale (3–12 months)
- Expand to additional practices only after audit logs, telemetry and DLP meet security requirements.
- Introduce role‑based competency gates so that only certified users may sign off on AI‑assisted filings.
- Integrate Copilot telemetry with SIEM for anomaly detectintOps runbook with a kill switch for misbehaving agents.
Governance: Policies, Contracts and Auditing
- Policy must be explicit: Define permitted workflows, banned activities (unredacted PII into chats), mandatory human review points, and disciplinary steps for violations. Make policy part of onboarding and annual CLE.
- Procurement redlines to insist on: no‑retrain/no‑use for matter data, deletion within defined windows, exportable prompts/responses logs, model version metadata and contractually stipulated breach notification and audit rights.
- Audit trails: capture prompt tmp, model version and provenance references for any output used externally or relied upon in client advice. These artifacts will be essential for eDiscovery and regulatory enquiries.
- Connector and agent governance: maintain an approved connectors list; no external web grounding for sensitive matters; require agent privacy reviews before production use.
Training, Competency and the Human‑in‑the‑Loop
Training converts tool access into safe, productive use. Key elements:- Prompt hygiene and hallucination detection must be taught and tested in hands‑on labs.
- Mandatory verification demonstrations: Associates should pass a competency check where they identify and correct hallucinations and document verification steps.
- Role design: create AI verifier and prompt‑engineer roles to manage playbooks and QA; rotate juniors through authentic tasks to preserve experiential learning.
Measuring Success: Concrete Metrics to Track
iew time per class of document (pre‑AI vs post‑AI).- Turnaround time for first draft delivery.
- Post‑submission correction rate attributable to AI‑assisted content.
- Verification competency pass rate for junior lawyers within 90 days.
- Consumption and cost telemetry (agent messages, Copilot seat usage) against budget scenarios.
Real‑World Incidents: Why Caution Is Not Theoretical
High‑profile incidents where AI generated fabricated citations and led to sanctions show the stakes. Multiple courts and disciplinary bodies have rebuked lawyers who failed to verify AI‑inserted authorities, underlining that courts expect the same professional diligence whether research was carried out by hand or AI. These events have pushed firms to implement stricter AI policies and deploy verification tooling. This legal reality validates Ben Schorr’s central emphasis: Copilot accelerates routine legal work, but human verification is an ethical requirement, not an optional guardrail.A Short Checklist for Windows‑centric IT Leaders
- Inventory: Map SharePoint, OneDrive and Teams stores and apply Purview sensitivity labels before Copilot is enabled.
- Identity: Enforce Entra Conditional Access and MFA for any Copilot use.
- Endpoint: Apply Endpoint DLP policy to block copying of privileged content into non‑tenant chat sessions.
- Logging: Route Copilot logs into SIEM; enable exportable prompt/response logs for high‑stakes matters.
- Pilot: Start with a 30–90 day pilot, low‑risk workflows and explicit KPIs.
- Contract: Require no‑retrain/no‑use and deletion guarantees in writing.
Final Assessment — From Hype to Practicality
The Lawyerist episode with Ben Schorr offers a pragmatic, grounded approach: Copilot delivers credible business value today in document‑heavy workflows and meeting capture—but that value is conditional on solid governance, technical controls, procurement diligence and human verification. Firms that treat Copilot as just another productivity feature risk regulation, malpractice exposure and reputational harm. Firms that treat it as a governed capability—piloted, measured and taught—will likely reap durable time‑to‑value and new career paths for lawyers fluent in AI‑augmented workflows.Conclusion
Microsoft Copilot is not a silver bullet, nor is it vapor; it is a powerful productivity engine that lives where most law firms already work—inside Microsoft 365. Ben Schorr’s practical counsel is straightforward: start small, protect client data with tenant grounding and Purview, train your people on verification and prompt hygiene, harden contracts with vendors, and measure outcomes that matter (quality and speed, not hours saved as an abstract number). When those elements are in place, Copilot shifts from a hyped novelty to a dependable assistant that amplifies lawyer productivity without surrendering professional responsibility.Source: Legal Talk Network From Hype to Practice: Using Microsoft Copilot in Your Law Firm, with Ben Schorr - Legal Talk Network


