Enterprise AI Transformation Lead

About this role

About Everlaw

At Everlaw, our mission is to promote justice by illuminating truth. We're changing how legal teams at law firms, corporations, government agencies, and nonprofits find the information they need to achieve their truth-finding goals. We believe technology should be a force multiplier for human intellect, and we see AI as an important part of how Everlawyers can work more effectively and thoughtfully.

The Role

Everlaw is building a deliberate, company-wide approach to AI—not simply to help people work faster, but to transform how we operate: redesigning workflows, improving the speed and quality of decisions, and creating new ways for teams to deliver meaningful outcomes.

Reporting to the VP of IT & Security, you’ll own Everlaw’s horizontal Corporate AI program end to end across governance, shared tooling strategy, adoption, measurement, and cost and vendor management. You’ll drive AI transformation by mobilizing department AI owners and champions and partnering closely with Learning & Development, Legal, and IT & Security.

This is a deeply hands-on role. You’ll get deep into enterprise AI platforms, agents, connectors, and workflows—evaluating tools, building and testing practical solutions, and translating what works into reusable capabilities that scale. You’ll move promising ideas from exploration to adoption, partner with Legal and Security to establish the guardrails needed to scale them responsibly, and measure whether they are changing how work actually gets done.

This is not an AI research or production engineering role, nor is it a traditional program-management or consulting role. It is a builder-operator role for someone who can work deeply in the systems while running the program with rigor—connecting systems, people, and execution so AI becomes a durable part of how Everlaw operates.

What You’ll Do

1. Own the enterprise AI operating model and governance

Keep Everlaw's federated AI efforts coherent, secure, and aligned to business priorities.

• Own and operate Everlaw’s federated AI framework: run its monthly and quarterly cadence, convene department AI owners, maintain clear accountability across the program, and report progress and risks to the leadership.

• Mature the operating model as Everlaw learns—including its principles, decision rights, ownership boundaries, and RACI across Enterprise AI, IT, Security, Legal, and department AI owners.

• Partner with Legal and Security on data-use governance, including data classification, acceptable use, autonomy limits, and agent guardrails—enabling low-risk work to move quickly while applying appropriate scrutiny to higher-risk uses.

2. Own the enterprise AI stack — expertise, landscape, and evaluation

Be Everlaw’s resident expert on its enterprise AI platforms and the market around them, shaping what enters the stack, what scales, and what exits.

• Build deep, hands-on expertise in Everlaw’s enterprise AI platforms. Use them regularly, understand their strengths, limitations, integrations, and roadmaps, and determine which capabilities are worth piloting, promoting, or standardizing.

• Stay ahead of the AI landscape by proactively researching and shortlisting tools and capabilities that could materially improve how Everlaw works—while filtering out noise and deciding what merits formal evaluation.

• Lead structured, evidence-based evaluations using rubrics, baseline tasks, scorecards, and business-value criteria. Build and test with the tools directly rather than relying on vendor demonstrations, and own recommendations on whether to extend existing platforms, buy new capabilities, or build internally.

• Maintain a coherent shared stack by preventing duplicative or fragmented adoption where an approved platform already meets the need. Advise departments on specialized tools while respecting their ownership of domain-specific applications.

• Coordinate procurement, implementation, rollout, and launch change management with IT, Procurement, Security, Legal, and other partners that own the relevant approval and delivery mechanics.

3. Drive adoption and practical enablement

Turn the tools Everlaw already owns into changed workflows and measurable use — most companies use a fraction of what they pay for; you close that gap.

• Build and maintain the central enablement playbook and template library—including intake, POC, change-management, and training patterns—so teams can move quickly without reinventing the basics.

• Provide hands-on guidance for high-value use cases: work directly with teams to redesign workflows and build agents or templates alongside them where targeted support is more effective than a formal engagement.

• Partner with Learning & Development to build practical AI fluency across Everlaw, including tool and model selection, effective AI collaboration, and cost-conscious use.

• Lead the AI champion community of practice, working with department AI owners and champions to surface adoption barriers, training needs, and reusable patterns—and feed what is learned back into playbooks and guidance.

4. Measure value and manage the AI portfolio

Own the methodology that shows whether the Enterprise AI program is creating real value — and the discipline to act on what it shows.

• Own and mature the measurement system behind Everlaw's AI adoption framework — standards for pre-AI baselines, metric targets, and measured results — moving from adoption and activity metrics toward outcomes tied to workflow improvement, quality, risk reduction, and business value.

• Partner with department AI leaders to define success measures for function-specific initiatives, and validate value claims as initiatives graduate through the funnel, so reported impact holds up.

• Run regular portfolio reviews and manage the path from experiment to sustained adoption, with clear criteria for what should scale, consolidate, pause, or stop.

5. Manage AI spend, vendors, and external partners

Ensure Everlaw’s AI i

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