AI Strategy & Readiness Assessment
Get AI strategy consulting and a readiness assessment. Prioritize use cases, assess feasibility and risk, and get a roadmap. No build or data cleanup.
Typical duration: 2 to 4 weeks. Deliverables: readiness findings, a ranked AI opportunity portfolio, a measurable baseline for the leading workflow, and a first-project technical and cost outline. No AI system build or data cleaning is included.
概览
An AI strategy and readiness assessment helps you decide where to apply AI, what to tackle first, and what needs to be true for the work to succeed. We review your business goals, current AI use, workflows, systems, data, people, and relevant risks. We compare candidate use cases by expected value, feasibility, readiness, risk, and dependencies. For the leading workflow, we define a measurable starting point where the available evidence supports it. You leave with a clear recommendation and a roadmap your team can use to make its next investment decision.
我们提供什么
The assessment combines business and technology discovery into one decision process. We map the current state with the people responsible for the work, identify opportunities across teams, then evaluate each candidate against its expected benefit, data and system requirements, delivery effort, operational fit, and risks. For the leading workflow, we capture a baseline where records allow, such as volume, manual effort, cycle time, errors, rework, or exceptions. We mark missing evidence and assumptions instead of presenting estimates as measured facts. The first-project outline can include likely systems and data connections, deployment assumptions, key dependencies, indicative implementation effort, and ongoing model or platform costs. These are planning ranges based on information available during the assessment, not a fixed implementation quote. The recommendation may be to run a bounded pilot, address a process or data gap first, sequence several opportunities, or hold off on AI. This engagement does not build software, configure agents, clean or restructure data, or implement the roadmap. Those activities can be scoped separately if you choose.
核心能力
Business goals, workflows, and AI readiness review
AI opportunity discovery across relevant processes
Workflow baseline, value, feasibility, risk, and dependency assessment
Prioritized AI strategy and implementation roadmap
业务价值
对你的业务真正重要的可见成果。
Know where AI may help and where it may not
Make investment decisions with constraints and assumptions in view
Give decision-makers a sequence, owners, and success measures
理想应用场景
Use this assessment when leaders have AI ideas but no confident first step, when pilots are stalled, when teams need to compare AI with standard automation or process redesign, or when an investment needs a business case. Scope can focus on one workflow, a department, or a broader portfolio. Common assessment areas include customer support, sales, finance, marketing, operations, internal knowledge, and employee or customer experience.
我们驱动的成果
A prioritized portfolio of AI use cases with the reasons behind the ranking
A readiness view across workflows, data, systems, people, and governance
A clear recommendation to pilot, prepare, sequence, or not build yet
A roadmap showing owners, dependencies, decision gates, and success measures
A record of evidence, assumptions, and unanswered questions
A measurable workflow baseline and a defined first validation step
我们的方法论
Four phases from business goals to an evidence-aware AI roadmap.
We agree the decision to be made, map business goals and current workflows, assess opportunities by value, feasibility, readiness, and risk, then test assumptions with the people who own the work. We deliver a prioritized roadmap and clearly identify what evidence should be gathered in a later pilot.
成效与经济回报
在你做出决定之前，先看清能得到什么。
Typical duration
2 to 4 weeks
Final timing depends on scope, access, and stakeholder availability.
Prioritization
Evidence and assumptions
Compare expected value with feasibility, readiness, risk, and effort.
Decision output
Roadmap and measures
Define how a selected opportunity should be evaluated if you proceed.
合作方式
限定周期、明确责任人、成本可控。
AI Strategy Assessment
2 to 4 weeksA time-boxed assessment to review readiness, rank opportunities, and decide what to do first. No AI system is built and no data is cleaned in this service.
交付物
Current-state findings, a measured baseline for the leading workflow where records allow, prioritized opportunities, a preliminary technical and cost outline, feasibility and risk assessment, and a recommended roadmap.
Optional Build & Operate
3 to 6 monthsA separate engagement, scoped only if you choose to implement a recommended opportunity. The assessment does not commit you to this work.
交付物
A separately agreed implementation scope, delivery plan, owners, and success measures.
Optional Run & Scale
Ongoing monthlySeparate ongoing support after an AI system is implemented. Monitor outcomes and reprioritize improvements under an agreed scope.
交付物
Periodic reviews, value tracking, and recommendations for next steps after launch.
Illustrative assessment snapshot
Example onlyExample: assessing customer-support request triage
- Baseline: measure request volume, handling time, rework, and exception rates from available records. Mark unavailable data as a gap, not a result.
- Technical outline: identify likely helpdesk and data connections, deployment assumptions, key dependencies, and where a person reviews uncertain or sensitive cases.
- Decision and estimate: compare a bounded pilot with rules-based automation, process changes, or no build. Include indicative implementation effort and ongoing technology costs with assumptions. This is not client data, a measured result, or a fixed quote.
风险与合规
Review privacy, security, governance, and human-oversight questions relevant to the agreed use cases.
Document dependencies, evidence gaps, assumptions, and unresolved questions.
Define owners, decision points, and controls to consider before a later pilot or implementation.
The assessment does not include a system build or data cleanup, and it does not guarantee financial returns.
是否适合你？
先看清楚，再做决定适合
- You need to decide where AI is worth exploring before committing to a build or platform.
- Your decision-makers and people who understand the work can take part in discovery.
- You want a practical, evidence-aware recommendation with owners and next steps.
不适合
- You are looking for code, an agent, or a production system to be built in this engagement.
- You need us to clean, restructure, or label data before AI can use it.
- You expect guaranteed ROI or a predetermined technology recommendation before discovery.
项目结束之后
我们不会做完就撒手不管The handover documents the recommendation, evidence, assumptions, and named owners.
You can take the roadmap to your own team or choose a separately scoped implementation engagement.
Optional ongoing reviews can track outcomes and reprioritize opportunities as your needs change.
关键交付物
Executive summary of current state, readiness, and the leading workflow baseline
Ranked opportunity portfolio with use cases and prioritization rationale
Readiness findings across workflows, data, systems, skills, and governance
Feasibility, risk, assumption, and dependency assessment
First-project technical outline with indicative implementation effort, ongoing technology costs, and assumptions
Sequenced roadmap with owners, decision gates, and next steps
我们如何合作
Six steps from business question to a prioritized recommendation.
你可以期待
- Align on the business decision, stakeholders, and assessment scope.
- Keep owners, evidence, assumptions, and open questions visible.
- Receive a clear recommendation, roadmap, and next-step options.
Agree on the decision
Define the business goal, the questions to answer, the people to involve, and the boundaries of the assessment.
Map the current state
Review relevant workflows, systems, data, roles, performance measures, and constraints with the people who know the work. For the leading workflow, capture available volume, manual effort, cycle time, errors, rework, and exception rates. Flag any measures the available evidence cannot support.
Identify opportunities
Find candidate use cases across the agreed scope, including options for AI, standard automation, process change, or no change.
Assess readiness and feasibility
Review expected value, data and system needs, delivery effort, operational fit, risks, and dependencies. Outline likely system connections and deployment assumptions, and estimate implementation effort and ongoing technology costs as indicative ranges. Separate measured evidence from assumptions.
Prioritize with stakeholders
Compare the options, validate the ranking with business and technical owners, and agree what should happen first.
Present the roadmap
Deliver the recommendation, owners, decision gates, success measures, and evidence to validate if you choose to proceed.
常见问题
点击展开答案01What is an AI strategy and readiness assessment?+
02What does the assessment review?+
03What will we receive at the end?+
04Does the assessment include building or implementing AI?+
05Does the assessment include data cleaning or preparation?+
06Can the recommendation be not to use AI?+
07How long does an AI readiness assessment take?+
08How much does the assessment cost?+
Ready to decide where AI is worth it?
Tell us about your goals and the process you are considering. We will discuss whether an assessment is the right next step and what it should cover.