AI WORKSHOP
Rapidly ideate, align leadership, and co‑create an actionable 6–12‑month AI strategy and prioritize use‐case roadmap via design thinking.
Two consecutive days (plus brief pre‑ and post‑workshop activities).
A structured, executive-ready engagement to identify the right AI use cases and build a clear 6–12 month roadmap.
Most AI initiatives stall because they start with technology instead of business outcomes.
The AI Immersion Workshop aligns leaders and stakeholders on where AI will deliver measurable value, what it will take to execute, and what to do next.
What You Will Achieve
• Shared understanding of highest-impact AI opportunities tied to business goals
• Prioritized portfolio of AI use cases evaluated for value, feasibility, and readiness
• Practical 6–12 month roadmap from idea to pilot and implementation
• Clarity on data, governance, architecture, and investment requirements
Customer Deliverables
• Executive Summary
• Current-State Assessment
• Prioritized Use Case Portfolio
• RICE Scoring / Impact-Feasibility Details
• AI Maturity Assessment
• Architecture Recommendations
• 6–12 Month Roadmap
• Proposed Next Steps
• Investment Recommendations
Why This Works
This engagement aligns people, process, data, technology, governance, and ROI into one executable plan. Organizations leave with clarity on what matters most, what is achievable
now, and how to move forward with confidence.
Workshop Structure
Day 1: Align on outcomes and identify use cases
• Confirm business objectives, KPIs, and success criteria
• Identify pain points and operational bottlenecks
• Map AI capabilities to business needs
• Generate and refine candidate use cases
Day 2: Evaluate, prioritize, and roadmap
• Assess feasibility, risk, data readiness, and time-to-value
• Prioritize using structured scoring (RICE / impact-feasibility)
• Define execution path and operating model considerations
• Draft 6–12 month roadmap and align next step
Workshop Timeline and Phases
Week 1: Intake & Discovery
Internal alignment, quote processing
Week 2: Workshop Preparation
AI readiness questionnaire, engagement pack distribution
Week3: Delivery & Handoff
2-day intensive workshop, report drafting, executive briefing, CRM updates
Stakeholder Roles and Responsibilities
Sales: Initiates opportunity, aligns with manager deal registration
Channel Manager: Coordinates client engagement and resource allocation
Services: Validates scoping, prepares deliverables, leads workshop delivery
Delivery Team: Facilitates workshops, draft reports, update CRM Collaboration across these roles ensures an effective AI workshop experience
Outcomes of a design thinking led workshop:
• Existing solutions
• Adoption and challenges
• AI priorities for the next one year
• High-level roadmap for the next 6 months
• Quick win themes
• Art of the possible use cases
• Prioritization frame work to prioritize top 5 use cases
• AI maturity and GenAI readiness index.
AI ASSESSMENT
Diagnose current AI maturity, readiness, and prioritize high‑value use cases — establishing a data‑driven roadmap and requirements for AI deployment.
Three Weeks AI Use Case Assessment
Feeling overwhelmed by AI? You're not alone.
Every business leader knows AI is the future, but many struggle with the same fundamental question: "Where do we even start?" The AI landscape is vast, and without a clear starting point, it's easy to get stuck.
That's why Arrow created the ECS-AI Assessment. This isn't just another test; it's the critical first step of the Arrow AI Accelerator Program—a global initiative designed to turn AI confusion into a clear, actionable roadmap.
What You Gain by Taking the First Step
through the identification, prioritization, and implementation of AI solutions. This helps establish a clear AI roadmap by assessing maturity and readiness, and by identifying key business areas where AI can provide immediate and impactful value. This is a structured
and fixed-scope project dependent on initial discovery and assessment phases, focusing
on delivering AI based solutions aligned with specific organizational goals and measurable outcomes.
From Assessment to Acceleration
• Existing solution performance
• User’s pain points
• Tech stack report
• Solution consumption report
• Processa nd governance
report
• Vision for the upcoming year
• Key objectives and results
• Tech and talent requirement
In this phase, we analyze organizational challenges, evaluate potential AI use cases, and prioritize those offering the highest value. By examining data, insights, model feasibility, and adoption readiness, we clarify technical requirements, projected outcomes, and integration strategies.
Week 1 – Data Readiness Assessment
Objective:
Evaluate your data environment to ensure that data quality, integration, and governance are sufficient to support AI initiatives.
Key Tasks:
- Data Discovery & Flow Mapping: Identify key data sources and map how data moves through your systems.
- Data Quality & Governance Assessment: Review data completeness, accuracy, timeliness, and governance practices.
Deliverables:
- Data Readiness Report: Detailed insights from the data discovery process and quality evaluation.
- Data Flow Diagram: Visual mapping of your data sources, flows, and any
integration gaps.
- Data Governance & Compliance Report: Findings on data stewardship,
compliance gaps, and recommendations.
Week 1 – Data Readiness Assessment
Objective:
Evaluate your data environment to ensure that data quality, integration, and governance are sufficient to support AI initiatives.
Week 1 – Data Readiness Assessment
Objective:
Evaluate your data environment to ensure that data quality, integration, and governance are sufficient to support AI initiatives.
Evaluate your data environment to ensure that data quality, integration, and governance
are sufficient to support AI initiatives.
Key Tasks:
- Data Discovery & Flow Mapping: Identify key data sources and map how data
moves through your systems.
- Data Quality & Governance Assessment: Review data completeness, accuracy,
timeliness, and governance practices.
Deliverables:
- Data Readiness Report: Detailed insights from the data discovery process and
quality evaluation.
- Data Flow Diagram: Visual mapping of your data sources, flows, and any
integration gaps.
- Data Governance & Compliance Report: Findings on data stewardship,
compliance gaps, and recommendations.