AI Readiness Assessment
A strategic framework inspired by modern agile practices, helping mid-market companies transform AI potential into tangible business outcomes.
Strategic Visioning
We leverage a structured assessment to identify high-impact AI opportunities that directly align with your business goals and market position.
Agile Experimentation
Transition from concept to working prototype rapidly (4-6 weeks), applying iterative cycles to test, learn, and adapt for optimal results.
Pragmatic Roadmapping
Develop a clear, actionable AI roadmap that prioritizes value delivery, technical feasibility, and responsible AI practices from day one.
Our proven approach helps you build a realistic and adaptive AI action plan for 2025, ensuring initiatives fit your current capabilities and deliver real, sustainable business value.
Strategic AI Evolution for Mid-Market Leadership
Unlock continuous business value through a pragmatic and evolutionary approach to AI, designed for rapid adaptation and sustainable growth in the mid-market.
Iterative Value Delivery
Achieve measurable outcomes quickly through our agile and iterative deployment cycles. We prioritize delivering continuous business value, adapting to your evolving needs and building momentum for strategic AI initiatives.
Value-Driven Investment
Ensure every AI investment maximizes business impact. Our approach focuses on pragmatic solutions that deliver tangible ROI, optimizing resource allocation for sustainable and meaningful transformation.
Evolutionary Architecture
Build your AI capabilities for future readiness. We design solutions that are inherently adaptable, allowing you to start with foundational elements and scale seamlessly as your strategic objectives and AI maturity evolve.
Pragmatic Adoption Process
Demystify AI implementation with our clear, outcome-focused methodology. We provide transparent steps and continuous feedback loops, ensuring practical guidance and accelerated, sustainable success.
Join other forward-thinking mid-market companies who are enhancing their operations through our practical, results-focused AI solutions.
Week 1: Setting Your AI Foundation
The journey to successful AI implementation begins with a structured discovery phase, leveraging proven frameworks to align your strategic objectives with AI's transformative potential.
1
Holistic AI Readiness Assessment
We initiate a comprehensive assessment to understand your organization's current landscape and future aspirations. This phase includes:
  • Evaluating your existing technology ecosystem and infrastructure.
  • Assessing data maturity, quality, and accessibility.
  • Mapping current organizational capabilities and identifying skill gaps.
  • Defining strategic business objectives and key performance indicators.
This foundational understanding allows us to identify and frame high-potential AI opportunities tailored to your unique context.
2
Collaborative Opportunity Framing Workshop
Our interactive 90-minute session brings together key stakeholders for a focused co-creation exercise:
  • Establishing clear roles and fostering cross-functional alignment.
  • Identifying critical business challenges and their root causes.
  • Exploring innovative AI solutions and their potential impact.
  • Prioritizing high-value use cases based on feasibility and strategic alignment.
  • Defining initial Proof of Concept (POC) parameters and success metrics.
Through agile and iterative discussions, we capture insights and decisions in real-time, ensuring a shared vision across your team.
3
Developing an Evolutionary AI Roadmap
Following our workshop, we lay the groundwork for a flexible and adaptive implementation journey:
  • Strategic data collection and documentation for selected use cases.
  • Executive validation and refinement of prioritized AI initiatives.
  • In-depth technical feasibility review and architectural considerations.
  • Development of a comprehensive POC proposal with clear objectives.
  • Establishing an iterative timeline and defining resource allocation.
  • Setting measurable success metrics and early milestones for continuous value delivery.
This structured approach prepares us for Week 2's strategic planning and agile execution phases.
Week 1 Meeting Agenda
1
Set Foundation and Vision with Agile Principles
Launch meeting with focused team introductions and clear role definitions. Assess client's current position on the AI Maturity Model through an interactive discussion, leveraging a ThoughtWorks-inspired readiness assessment. Establish specific, measurable objectives for the engagement with clear success criteria and timeline expectations, aligning with agile planning principles.
2
Identify Strategic Opportunities through Value Stream Mapping
Map existing business challenges to potential AI solutions through a structured discovery session, utilizing a value stream mapping approach. Share relevant industry case studies and success metrics from organizations at similar maturity stages. Focus on identifying opportunities that align with client's current capabilities and growth objectives, emphasizing business value streams.
3
Select High-Impact Initiatives with Pragmatic Prioritization
Utilize an Impact-Feasibility Framework to evaluate and score potential AI initiatives, considering key factors: business value, technical requirements, data readiness, and implementation complexity. Build consensus on 2-3 priority use cases for proof of concept through a collaborative assessment, guided by ThoughtWorks' pragmatic prioritization approaches.
4
Design Iterative POCs and Evolutionary Architecture
Create a comprehensive POC framework with clear success metrics and a timeline, emphasizing iterative development cycles. Map technical requirements including data needs, system integrations, and infrastructure dependencies, with a view towards evolutionary architecture. Develop a risk assessment matrix and preliminary mitigation strategies to ensure smooth execution and continuous learning.
5
Plan Week 2 Activities with Continuous Collaboration
Assign specific preparation tasks to client and mbAI teams with clear deadlines, fostering continuous collaboration. Define data collection requirements and a stakeholder engagement plan. Establish agile project communication protocols and schedule key follow-up meetings. Document and distribute detailed action items with designated owners, promoting transparency and shared understanding.
Session 2: AI Solution Design and Implementation Planning
1
Quick Assessment Review
Review Week 1 insights, focusing on high-impact AI opportunities. Identify critical enterprise systems and data ecosystems for AI enhancement. Analyze current operational workflows to determine strategic AI integration points for rapid value delivery.
2
Stakeholder Alignment
Facilitate cross-functional stakeholder workshops to align on AI priorities and urgent business needs. Assess current data governance, quality, and accessibility for AI readiness. Co-create measurable and impactful success metrics, directly aligned with strategic business outcomes.
3
Solution Design
Develop streamlined solution blueprints for selected use cases, emphasizing ethical AI principles and responsible design. Create a lightweight, iterative implementation plan with clear, value-driven milestones. Outline core technical requirements for scalable architecture and rapid deployment.
4
Action Planning
Proactively identify potential implementation challenges, technical debt, and establish agile mitigation strategies. Refine the Proof of Concept (POC) scope to focus on delivering maximum incremental value. Develop an adaptive AI roadmap for continuous delivery and business integration.
Week 2 Meeting Agenda
Our structured agenda ensures we build upon Week 1's foundation and chart a clear path forward.
1
Recap & Validated Learning
Review key findings and validated insights from Week 1 discovery sessions. Iteratively reassess current AI maturity based on evolving understanding of technical capabilities, data infrastructure, and organizational readiness. Identify emergent gaps or opportunities for continuous improvement.
2
Iterative POC Scope Definition
Collaboratively define specific, measurable POC objectives aligned with strategic business outcomes. Establish clear, testable deliverables and success metrics for rapid validation. Develop an agile resource allocation plan, focusing on cross-functional teams and iterative technical requirements. Proactively address evolving constraints and dependencies for lean implementation.
3
Evolutionary AI Roadmap Development
Co-create an adaptable implementation strategy aligned with an evolutionary AI Maturity Model. Plan dynamic resource allocation across continuous delivery phases, emphasizing infrastructure elasticity, talent development, and technology adoption. Establish robust risk management for data ethics, privacy, and continuous organizational change. Design a feedback-driven monitoring and evaluation framework for value realization and continuous ROI.
4
Continuous Feedback & Next Iterations
Facilitate an open dialogue to gather client input on proposed evolutionary approach and adaptive timeline. Address any concerns or questions regarding the agile implementation strategy. Assign clear action items and shared responsibilities to cross-functional team members with agreed-upon iteration goals. Schedule regular syncs for continuous progress tracking and iterative reviews.
By following this structured agenda, we'll ensure all key aspects of the AI implementation are thoroughly addressed and next steps are clearly defined.
AI Adoption Journey & Strategic Deliverables
Leveraging ThoughtWorks' principles, our iterative approach ensures clear milestones and tangible outcomes, guiding your organization through a robust AI implementation journey.
1
Discovery & Foundation (Week 1)
  • Comprehensive AI maturity assessment aligned with organizational capabilities
  • Identified AI opportunities with clear business value and feasibility analysis
  • Initial Proof-of-Concept (POC) scope and success metrics
  • Resource allocation and risk identification
  • Strategic stakeholder alignment and communication plan
2
Iterative Planning & Design (Week 2)
  • Detailed POC blueprint with agile development considerations
  • Evolving AI roadmap focused on iterative value delivery
  • Defined success criteria and phased milestone markers
  • Targeted maturity advancement strategy
  • Responsible AI principles and ethical risk mitigation framework
  • Resource and investment allocation plan for immediate next steps
3
Continuous Evolution & Scale (Post-POC)
  • Performance metrics and actionable insights for continuous improvement
  • AI/MLOps playbook for robust deployment and management
  • Recommendations for scaling AI solutions with architectural adaptability
  • Refined maturity progression and capability building plan
  • Long-term AI strategy blueprint with future-proof considerations