Enterprise AI Planning Workshop
Transform Al Ambitions into Measurable Business Impact
Why this workshop matters
85% of enterprise Al projects fail-don't be one of them. Pinnacle Al equips you with the strategy, structure, and tools to succeed.
Data Engineering Consulting Practice - 4 Category Framework
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Objective:
Understand the client's current position in their data and AI journey, establish baselinecapabilities, and identify readiness for advanced data initiatives.
Key Discovery Areas:
AI Journey & Maturity
Where are you currently in your AI/ML journey? (Exploring, Piloting, Implementing, Scaling)
What AI or ML initiatives have you attempted or considered?
Do you have dedicated data science or AI teams?
What's driving your interest in AI/ML capabilities?
Current Data Usage & Practices
How does your organization use data today?
What decisions are currently data-driven vs. intuition-based?
Who are your primary data consumers across departments?
What's your current data culture like?
Process Automation
Do you currently automate any business processes?
Which processes are still manual that could benefit from automation?
What tools do you use for automation (RPA, workflows, etc.)?
How do you measure the success of automated processes?
Productivity Measurement
How do you currently measure productivity across teams/departments?
What KPIs or metrics matter most to leadership?
Do you have baseline metrics to compare improvements against?
How often are productivity metrics reviewed and acted upon?
Data Quality & Transformation
Is your data clean and standardized?
What data transformation processes are currently in place?
How do you handle data quality issues?
Do you have data governance practices?
What's your data lineage and audit trail like?
Data Visualization & Dashboards
Is your data currently loaded in dashboards or BI tools?
How do you visualize data today? (Excel, BI tools, custom apps)
Who has access to dashboards and reports?
How real-time is your data visualization?
Are visualizations self-service or IT-dependent?
AI/ML Goals & Success Metrics
What are your specific goals for utilizing AI/ML?
How would you measure success of AI/ML initiatives?
What business problems are you hoping AI will solve?
What's your expected ROI or timeline for AI investments?
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Objective:
Evaluate current technical capabilities, identify infrastructure gaps, and design scalable dataarchitecture.
Key Assessment Areas:
Current Data Infrastructure
Where does your data currently reside? (Cloud, on-premise, hybrid)
What databases, data warehouses, or lakes are you using?
How is data currently ingested and processed?
What's your current ETL/ELT process?
Integration & Connectivity
How well are your systems integrated?
What APIs or connectors are currently in use?
Are there data silos between departments or systems?
How do you handle third-party data sources?
Scalability & Performance
Can your current infrastructure handle increased data volumes?
What are your current performance bottlenecks?
How do you handle peak data processing loads?
What's your disaster recovery and backup strategy?
Security & Compliance
What data security measures are currently in place?
Do you need to comply with specific regulations (GDPR, HIPAA, etc.)?
How do you manage data access and permissions?
What's your data retention and deletion policy?
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Objective:
Assess organizational capacity for data transformation, identify skill gaps, and plan changemanagement approach.
Key Assessment Areas:
Skills & Capabilities
What data skills exist within your organization?
Are there knowledge gaps that need to be filled?
How do you currently handle data training and education?
Do you have change champions within departments?
Organizational Structure
How are data responsibilities currently distributed?
Who owns data quality and governance decisions?
What's the reporting structure for data initiatives?
How are cross-functional data projects managed?
Culture & Adoption
How receptive is your organization to data-driven decision making?
What resistance to change do you anticipate?
How do you typically handle technology adoption?
What communication channels work best in your organization?
Resource Allocation
What budget is allocated for data and AI initiatives?
How do you prioritize data projects vs. other IT investments?
What internal resources can be dedicated to data projects?
Are you open to external partnerships or outsourcing?
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Objective:
Create actionable implementation plan with defined phases, timelines, and success criteria.
Key Planning Areas:
Prioritization & Phasing
Which data initiatives will deliver the highest business value?
How should projects be sequenced for maximum impact?
What are the dependencies between different initiatives?
Which quick wins can demonstrate early value?
Implementation Approach
What's the preferred implementation methodology? (Agile, Waterfall, Hybrid)
How will you handle pilot projects vs. full-scale rollouts?
What's your risk tolerance for new technology adoption?
How will you measure progress and success along the way?
Timeline & Milestones
What are your target timelines for key deliverables?
What external deadlines or business events should we consider?
How will we structure project phases and checkpoints?
What contingency planning is needed?
Success Criteria & ROI
How will you define and measure project success?
What metrics will indicate ROI achievement?
How will you track adoption and user satisfaction?
What post-implementation optimization is planned?
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FinOps meets Cloud Intelligence.
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| Plan Details | Business | Professional | Enterprise | Large Enterprise |
|---|---|---|---|---|
| Annual Spend | $0.00 – $150,000 | $150,000 – $600,000 | $600,000 – $1,500,000 | $1,500,000+ |
| "My Cloud Architect" Service Monthly Charge | $485.00 | $975.00 | $1,699.00 | Custom |
| "My Cloud Architect" One Time Set up Fee | $749.00 | $1,499.00 | $1,999.00 | Custom |
| Plan Details | Business | Professional | Enterprise | Large Enterprise |
|---|---|---|---|---|
| Cloud Spend Optimization Recommendations | ✔ | ✔ | ✔ | ✔ |
| Detailed Product Utilization Reporting | ✔ | ✔ | ✔ | ✔ |
| Cloud Economics Report | ✔ | ✔ | ✔ | ✔ |
| AI-ML Trained Data | ✔ | ✔ | ✔ | ✔ |
| Number of Accounts Supported | Up to 3 | Up to 3 | Up to 5 | Custom |
| Infrastructure Modernization Recommendation Engine | ✔ | ✔ | ✔ | ✔ |
| Cloud Analytics and Trend Analysis | ✔ | ✔ | ✔ | ✔ |
| Architectural Design and Blueprint Creator | ✔ | ✔ | ✔ | ✔ |
| Ongoing Technical QA Support | ✔ | ✔ | ✔ | ✔ |
| NLP Feature Set | ✔ | ✔ | ✔ | ✔ |
| End User Portal (UI) | ✔ | ✔ | ✔ | ✔ |
| Quarterly Cloud Operations Review | — | — | ✔ | ✔ |
| Account Manager | — | — | ✔ | ✔ |
My Cloud Architect™ Pricing
Flexible pricing tailored to your cloud footprint. Choose the plan that fits your organization, from startups to large enterprises.
