AI Readiness Assessment
Assess strategy, data, security, governance, workflows, people, and technology.
Positioning
An operating decision, not a technology purchase.
AI should improve the way a firm operates. Koers helps organizations decide what to adopt, what to automate, what to govern, and what not to buy.
In legal work, the measurable value sits in specific places. Intake that captures the right facts the first time. Research and drafting that start from the firm’s own precedent. Knowledge that can be found when it is needed. Routine operational tasks that no longer wait on a person. Each can be measured against a baseline. Where there is no baseline, there is no case for the tool.
Governance comes first because the risks are specific to the profession. Confidentiality, privilege, professional responsibility, and client expectations set limits on what a tool may do and who reviews its output. Settling those limits before adoption is faster than repairing an incident after it. It also makes the decision defensible when partners or clients ask how it was made.
Services
Seven services, from assessment to measurement.
Each service has a defined scope and a deliverable. Engagements can combine several, from assessment through evaluation.
AI Strategy
Prioritize use cases and develop a practical roadmap.
AI Governance
Policies, controls, approved-use models, vendor review, confidentiality, and human oversight.
Vendor & Platform Selection
Evaluate platforms against use cases, risk, integration, and economics.
Workflow Automation
Design AI-enabled intake, research, drafting, knowledge, and operational workflows.
Pilot Implementation
Build and evaluate controlled pilots before full deployment.
Evaluation
Measure quality, risk, adoption, time savings, and business impact.
Framework
Koers AI Readiness & Governance Framework
Ten domains structure the readiness assessment and the roadmap that follows it.
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Business Objectives
What the firm is trying to improve, stated in terms that can be measured.
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Use Cases
Where AI could apply in the practice, ranked by value, risk, and readiness.
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Data Readiness
Whether the documents, matter data, and knowledge a tool depends on are accessible, accurate, and permitted for the purpose.
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Security & Confidentiality
How client information is protected as it moves through prompts, models, vendors, and outputs.
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Governance
Who decides what is approved, how policy is set, and how exceptions are handled.
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Model / Vendor Risk
How each platform and model is evaluated for accuracy, contract terms, data handling, and dependence.
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Human Oversight
Where a qualified person reviews AI output before it is relied on, and how that review is recorded.
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Workflow Integration
How approved tools fit the firm’s actual intake, matter, and drafting workflows rather than sitting beside them.
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Evaluation
How quality, risk, adoption, time savings, and business impact are measured against a baseline.
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Change Management
How staff are trained, how adoption is supported, and how the operating model changes as tools are introduced.
Independence
What Koers does not do
Advice is only worth acting on if it is independent of the vendor, the trend, and the wish to call a pilot a success.
- Recommend AI simply because it is new
- Push a preferred vendor without disclosure
- Treat pilots as successful without measurement
- Ignore confidentiality, security, or professional responsibility
- Automate high-risk workflows without appropriate human review
Where to start
Three entry points.
The right first step depends on where the firm is. Each of these leads to a conversation, not a proposal.
AI readiness assessment
Start here if the firm has not yet decided what to do. The assessment covers the ten domains and produces a prioritized roadmap.
AI governance
Start here if tools are already in use. The work sets policy, approved-use models, vendor review, and human oversight around what is already happening.
Pilot implementation
Start here if a use case is chosen. A controlled pilot with defined success measures, evaluated before any wider deployment.