MinterEllison’s AI Leap: Copilot in Daily Law Firm Work

Virginia Briggs, chief executive of Australia’s MinterEllison, says she uses Microsoft 365 Copilot “for every task, every day,” and the firm’s experience — from boardroom demos to bespoke legal drafting tools — offers an early, high‑profile case study of what enterprise generative AI looks like when leadership commits to using it as a daily operational assistant. The firm’s rollout combines the basic Copilot chat features inside Outlook, Teams and Word with higher‑capability agents such as Researcher, internal GPT‑backed drafting tools, and tenant controls that aim to keep client data secure while accelerating routine legal work. (news.microsoft.com)

Background​

MinterEllison is one of Australia’s largest law firms, with roughly 2,500 staff and multiple offices across the country. Its leadership publicly committed to broad workplace AI adoption, setting a target that a large majority of the firm’s people would incorporate AI into their daily work within a specified timeframe. That ambition sits alongside pilot programs with Microsoft’s Copilot and internally developed generative AI tools hosted in the firm’s Azure environment. (news.microsoft.com)
The practical context matters: law firms are document‑heavy, deadline‑driven environments where repetitive drafting, literature review and meeting follow‑ups consume substantial partner and junior lawyer time. Vendors and early adopters argue Copilot and companion agents can reclaim hours per user per week — by summarizing long threads, producing draft documents, generating meeting transcripts and surfacing relevant precedents from archives. MinterEllison’s internal data cited in the firm’s early rollout reports indicate meaningful time savings across cohorts of users. (news.microsoft.com)

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What Virginia Briggs is saying — the claim and the context​

Virginia Briggs’s summary of her usage is striking for its simplicity: she describes Copilot as indispensable, used for research before meetings, generating instant transcripts, helping craft messaging for town halls and even rehearsing strategic conversations. She credits the Researcher agent in particular with producing quick, tailored scripts and meeting approaches that helped her appear exceptionally well‑prepared to external executives. Those anecdotes illustrate the kind of human‑AI partnership Microsoft is pitching: AI as a preparatory, analytical and productivity multiplier.
These are leader‑level anecdotes, not peer‑reviewed studies. The concrete results Briggs highlights — immediate meeting prep, real‑time boardroom demos, and weekend advice drafts — are powerful examples of how Copilot can accelerate senior decision‑making. At the same time they are inherently contextual and rely on the user’s domain expertise to validate and refine AI outputs. That human‑in‑the‑loop element is central to responsible use in regulated professions like law. (news.microsoft.com)

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Overview of the technology Briggs uses​

Microsoft 365 Copilot: the product stack in play​

Microsoft 365 Copilot integrates generative models into Word, Excel, PowerPoint, Outlook and Teams, and can be run in tenant‑aware mode that respects permissions and the Microsoft Graph. That means Copilot can reason over emails, calendar items, files and meeting transcripts stored inside an organisation’s Microsoft 365 environment — provided the tenant has purchased the premium Copilot seats and enabled the relevant controls. Administrators can also govern whether Copilot records and uses meeting audio/transcripts in Teams meetings. (microsoft.com)
Key on‑the‑ground features MinterEllison is using include:

• Meeting transcription and meeting‑summary generation inside Microsoft Teams, enabling rapid catch‑ups and actionable follow‑ups.
• Email summarization and prioritization in Outlook, so a returning executive can triage a large inbox quickly.
• Document drafting and editing assistance in Word and PowerPoint.
• Tenant‑aware agents such as Researcher and Analyst that are designed for deeper, multi‑step research and data analysis. (learn.microsoft.com)

The Researcher agent — what it does and why it matters​

Researcher is an agent inside Microsoft 365 Copilot built to perform structured research: it asks clarifying questions, gathers and synthesizes data from work content and the web, and produces a cited, editable report. Microsoft positions Researcher as a “supercharged research partner” capable of integrating tenant data with web sources and third‑party connectors (for example, Salesforce or ServiceNow) where those connectors are authorised. In practice, users can task Researcher to prepare meeting briefs, evaluate potential client collaborations, or pull together a concise briefing paper from a mass of email threads and documents. (support.microsoft.com)
Independent reporting and technical summaries confirm Microsoft has deployed Researcher and a companion agent, Analyst, to licensed Copilot customers as part of the broader push to add “deep reasoning” capabilities to the workplace. These agents use dedicated reasoning models and orchestration logic that are different from the lighter chat features in free Copilot experiences. (theverge.com)

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Real use cases at MinterEllison — what leaders and partners are doing​

The firm’s public narrative — illustrated by Briggs’s account — reveals several recurring Copilot use cases in a legal practice:

• Executive meeting prep: type in a few sparse facts and let Researcher build a meeting script, potential collaboration angles and suggested questions. Executives report appearing more prepared to clients and counterparties.
• Rapid weekend or after‑hours advice drafting: partners can use Researcher to assemble an initial foundation for legal advice which the partner then enhances and verifies with their expertise. This compresses time‑to‑client for urgent matters. (news.microsoft.com)
• Post‑meeting processing: Copilot transcribes meetings and, where enabled, generates summaries, action items and suggested next steps — saving the time of manual note‑taking and distribution. Admin controls allow organisations to require transcription or limit Copilot access to particular meetings. (learn.microsoft.com)
• Email triage and follow‑ups: after a day packed with meetings, Copilot helps flag priority messages and draft replies in the user’s tone, reducing cognitive load and inbox inertia. (news.microsoft.com)
• Training and graduate education: the firm has experimented with Copilot to help graduates acquire skills, using AI to automate some repetitive tasks while redesigning training so juniors still learn necessary legal judgement. This addresses a common concern that AI could remove essential learning opportunities; MinterEllison’s approach is to pair tool use with tailored training led by the firm’s talent team. (capitalbrief.com)

These use cases combine horizontal productivity features with bespoke tools the firm has developed — for instance, internal generative assistants that draft first versions of legal letters, running inside an Azure‑hosted environment to retain tighter data controls. (news.microsoft.com)

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Quantifying impact — the numbers MinterEllison is publishing​

MinterEllison’s early internal measurements and Microsoft’s case reporting have been emphatic: survey responses and usage snapshots indicate that many users report saving hours per day since adopting Copilot features. In one public Microsoft Australia feature about the firm, the published results included:

• At least half of users reporting savings of 2–5 hours per day.
• One in five users saying they save at least five hours per day.
• High user satisfaction metrics: roughly 89% finding Copilot intuitive and ~90% willing to recommend it. (news.microsoft.com)

Those figures are self‑reported and come from internal surveys during a period of early rollout. They are suggestive rather than definitive; independent audits and longitudinal productivity studies would be needed to confirm persistent, firm‑wide financial impact. Still, the numbers align with broader enterprise reports of substantial time‑savings when Copilot is deployed inside heavily document‑driven workflows. (crn.com)

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Governance, security and the legal‑sector test​

Law firms operate under stringent client confidentiality, privilege and professional responsibility obligations. The practical question for MinterEllison — and for any firm considering Copilot — is how to get the productivity upside without compromising client data or professional standards.
Key governance elements in play:

• Tenant grounding and Microsoft Graph controls: Copilot’s tenant mode reads only data the user or service account can access, and Microsoft exposes admin controls for transcription and agent availability that allow an organisation to limit where and how Copilot acts. Administrators can turn Copilot for Teams meetings on/off or require transcripts to be saved for auditing. (learn.microsoft.com)
• Internal guardrails and approvals: MinterEllison has reportedly built internal gateways — such as bespoke “Chat with ME” services in Azure — that allow certain generative tasks to run within the firm’s secure cloud environment, limiting external leakage and retaining provenance for outputs. (news.microsoft.com)
• Human validation: senior lawyers and partners remain responsible for reviewing and validating any advice generated with AI assistance; the AI output is treated as a first draft or research summary, not final legal advice without human sign‑off. This human‑in‑the‑loop stance helps preserve ethical and professional standards. (news.microsoft.com)

These controls are necessary but not sufficient. Independent journalism and legal‑sector reporting have documented cases where organisations using generative AI have relied on flawed outputs. That reinforces the need for explicit audit trails, model provenance and a disciplined sign‑off culture — all issues that enterprises now demand from AI vendors. (ft.com)

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Adoption and organisational change: Mandate vs. enablement​

MinterEllison’s leadership has signalled that AI adoption is a partnership between executive mandate and supporting training. The firm publicly set an 80% usage target for staff to be using AI at least weekly by a target date in early 2025 — an objective reported in mainstream business press and reiterated in firm communications. That level of explicit expectation makes clear that the firm is moving beyond pilot status into business‑as‑usual adoption. (afr.com)
The rollout approach includes:

• Executive sponsorship and board‑level visibility.
• Role‑based training and hands‑on practice for partners and juniors.
• Internal Champions and a Teams channel for knowledge‑sharing.
• Technical guardrails (tenant controls, connector governance, secure internal models).

This combination — top‑down targets with bottom‑up enablement — maps to best practices for digital transformation. Yet it also raises difficult workforce questions: how to redesign junior training when routine drafting tasks are accelerated or automated, and how to tie productivity gains to client pricing and partner remuneration fairly. (capitalbrief.com)

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Strengths and immediate benefits​

• Time recovered for high‑value work. Early reported savings show lawyers spending less time on rote work and more on legal strategy and client engagement. (news.microsoft.com)
• Executive acceleration. Copilot’s meeting prep and Researcher outputs enable faster decision cycles for senior leaders who must process a high volume of incoming information.
• Scaleable knowledge reuse. Agents and tenant‑hosted models allow firms to turn firm precedents, past matters and proprietary templates into searchable, reusable assets.
• Competitive positioning. Early adopters gain speed advantages in urgent client matters and can better market quicker turnaround on routine outputs. (blogs.microsoft.com)

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Risks and open challenges​

• Hallucination and factual errors. Generative models can produce plausible but incorrect statements. For legal work, those errors can be consequential unless robust human validation and traceability are enforced. Public and private reporting has documented hallucination incidents that make cautious governance essential. (reddit.com)
• Training and talent displacement. Accelerating routine tasks risks hollowing out opportunities for junior staff to learn foundational skills; firms must redesign training to ensure skill transfer and ethical practice. MinterEllison acknowledges this tension and places talent leaders at the centre of the rollout. (capitalbrief.com)
• Data governance and compliance. Client confidentiality, cross‑border data flow, and regulatory scrutiny demand strict tenant controls, connector governance and auditing. Organisations must treat Copilot updates and model changes as part of their security and patching lifecycle. (learn.microsoft.com)
• Over‑reliance and deskilling. Leaders must avoid substituting critical legal judgment for machine recommendations — AI should augment, not replace, professional judgement. (news.microsoft.com)

Where precise claims are made about model internals or specific throughput numbers, caution is warranted: model routing, vendor partnerships and which underlying model powers which Copilot feature have been evolving and reported differently across outlets. Treat such vendor‑level engineering claims as provisional unless confirmed by Microsoft’s technical documentation. (learn.microsoft.com)

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Practical takeaways for law firms and knowledge organisations​

• Start with high‑value, low‑risk pilots: meeting summaries, document search and draft structuring often deliver early ROI with manageable risk.
• Build governance into day‑one: admin policies for transcription, connector permissions, and agent installation must be explicit.
• Treat outputs as drafts: enforce partner sign‑off and maintain provenance records for auditability and privilege considerations.
• Rewire training: remove monotonous tasks from the junior learning curve only after redesigning experiential learning to preserve skill development.
• Track metrics beyond time saved: measure quality, client outcomes and professional development impact to ensure long‑term value. (news.microsoft.com)

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Conclusion​

Virginia Briggs’s decision to make Microsoft 365 Copilot a daily tool is more than a personal productivity story: it’s an example of leadership signalling that AI should be woven into knowledge work, not tacked on as an experimental sidebar. MinterEllison’s experience shows both the upside — faster meeting prep, email triage, rapid drafting and demonstrable time savings — and the institutional work required to manage risk: governance, training, and rigorous human oversight.
For legal firms weighing Copilot, the headline is pragmatic: generative AI can be a force multiplier when deployed with secure tenancy, work‑aware agents (like Researcher), and disciplined human validation. The technology is not a magic bullet, nor a replacement for professional judgement; it is a tool that, used well, can restore time for higher‑value legal work while demanding robust policy and cultural change from firms that decide to adopt it. (news.microsoft.com)

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Source: Microsoft Source MinterEllison CEO Virginia Briggs uses M365 Copilot for every task, every day - Source Asia