Why Organizations Like Cummins Are Exploring AI Now
The convergence of mature AI technologies and enterprise-scale problems has created unprecedented opportunities for operational transformation. For organizations like Cummins with complex, multi-regional operations spanning Latin America, this moment represents a critical inflection point. The question is no longer whether to adopt AI, but how to do it strategically and effectively.
Organizations operating across diverse markets face unique operational challenges that AI is uniquely positioned to address. These challenges compound across geographical boundaries, creating significant drag on efficiency and growth.
Process Fragmentation
Different systems, workflows, and business processes across countries and business units create operational complexity and inefficiency
Compliance Complexity
Varying regulatory requirements including OEA certifications, fiscal reporting standards, and data governance rules across jurisdictions
Knowledge Silos
Critical institutional knowledge and expertise trapped within individual subject matter experts, creating vulnerability and bottlenecks
Manual Bottlenecks
High-value professionals spending significant time on repetitive analytical tasks and data processing instead of strategic work
The Challenge
Most organizations recognize AI's transformative potential but struggle to identify where to start. Without a structured approach, companies risk investing in low-impact initiatives or creating technical debt through poorly planned implementations. The complexity of enterprise systems, combined with the rapid evolution of AI capabilities, makes prioritization difficult.
Leaders need clarity on which AI opportunities will deliver measurable ROI, align with strategic priorities, and can be implemented successfully within existing technical and organizational constraints.
Our Approach
VAS delivers structured discovery that cuts through the noise. We identify high-impact opportunities specifically aligned with your strategic priorities, operational realities, and technical infrastructure.
Our methodology ensures AI initiatives deliver real business value, not just technological innovation for its own sake.
Discovery-Driven AI Implementation
Our Methodology: From Assessment to Action
Successful AI transformation requires a systematic approach that balances business vision with technical reality. Our three-phase methodology ensures comprehensive assessment while maintaining focus on actionable outcomes. Each phase builds on the previous one, creating a clear path from current state to implementation.
01
Discovery & Assessment
Timeline: Weeks 1-2
02
Opportunity Analysis
Timeline: Weeks 2-3
03
Solution Design
Timeline: Week 4
1
Discovery & Assessment
Weeks 1-2
Stakeholder interviews across business units and regions to understand pain points and priorities
Current-state process mapping for key workflows and systems
Pain point prioritization using business impact scoring methodology
Technical infrastructure assessment covering Oracle Applications, legacy systems, and data sources
Quick-win identification for immediate value delivery
2
Opportunity Analysis
Weeks 2-3
AI capability mapping to specific business problems and use cases
Technical feasibility assessment for each opportunity
ROI modeling for top opportunities with clear metrics
Risk and compliance review addressing regional regulations
Roadmap development with sequenced initiatives and dependencies
3
Solution Design
Week 4
Detailed design specifications for priority initiative(s)
Proof-of-concept planning with success criteria
Implementation roadmap with milestones and resource requirements
Change management strategy for organizational adoption
Comprehensive Deliverable
The engagement culminates in a comprehensive assessment report with an actionable roadmap and executive-ready business case. This document provides everything leadership needs to make confident investment decisions and begin implementation immediately.
Potential AI Opportunities for Cummins LATAM
Example Applications Across Key Business Functions
Based on common enterprise challenges in regional operations and our experience with similar organizations, we've identified potential high-impact opportunities across four critical business domains. These examples illustrate the breadth of AI applications possible within Cummins' operational context.
These are illustrative examples to guide thinking. The discovery process will identify the specific opportunities with highest impact for your organization, considering your unique priorities, constraints, and technical environment.
HR & Talent Management
Automated resume screening and candidate matching for regional hiring across diverse markets
Predictive analytics for retention risk identification and succession planning
Training needs assessment and personalized learning path recommendations
Multi-language employee sentiment analysis across LATAM operations
Security & Compliance
Intelligent access control with anomaly detection for OEA compliance
Automated OEA compliance monitoring and documentation generation
Risk scoring algorithms for vendor and partner relationships
Predictive maintenance scheduling for security infrastructure
Supply Chain & Logistics
Demand forecasting for ReCon operations and PDC inventory optimization
Intelligent routing and shipment optimization across Colombia and Brazil
Automated customs documentation and trade compliance management
Predictive analytics for parts availability and strategic allocation
IT Operations & Project Management
Automated ticket triage with intelligent resolution recommendations
Project risk prediction based on historical patterns and current indicators
Resource allocation optimization across regional initiatives
Natural language interfaces to Oracle and legacy system data
Each of these opportunity areas represents potential for significant operational improvement and cost savings. During the discovery phase, we'll work with your teams to identify which specific applications align best with strategic priorities and offer the highest return on investment given current capabilities and constraints.
Why VAS?
Deep Expertise in Enterprise AI Implementation
Selecting the right AI implementation partner is critical to success. VAS combines deep technical expertise with pragmatic business focus and regional understanding. We don't just build AI systems—we deliver measurable business outcomes.
Our approach balances innovation with practicality, ensuring solutions work within your existing technical ecosystem and organizational culture.
Proven Track Record
Successfully delivered AI solutions for enterprise clients across manufacturing, logistics, and compliance domains. We have extensive experience integrating AI with Oracle Applications, ERP systems, and complex legacy infrastructure. Our focus is on pragmatic, ROI-focused implementations that deliver measurable value.
Technical Excellence
Full-stack AI capabilities spanning from data engineering and infrastructure to custom model development and deployment. Platform-agnostic approach means we work with your existing technology investments rather than forcing platform changes. Security-first design ensures compliance with enterprise and regional data governance requirements.
Business-Focused Methodology
Discovery-driven approach ensures perfect alignment with strategic priorities and business objectives. Change management expertise supports successful organizational adoption and user engagement. Transparent pricing and clearly defined deliverables eliminate surprises and ensure accountability.
Regional Understanding
Direct experience with LATAM regulatory environments including fiscal requirements, trade regulations, and labor laws. Multilingual team fluent in English, Spanish, and Portuguese. Deep understanding of regional operational challenges, cultural considerations, and business practices across Latin American markets.
Our team brings together world-class AI expertise with practical implementation experience in complex enterprise environments. We understand that successful AI transformation requires more than just technical capability—it demands business acumen, change management skills, and cultural sensitivity.
Engagement Structure & Next Steps
AI Discovery & Opportunity Assessment
Engagement Overview
4
Weeks Duration
Comprehensive assessment from kickoff to final presentation
$16.25K
Investment
Credited toward implementation if you proceed within 6 months
Team Composition
Lead AI Consultant & Project Manager (dedicated throughout engagement)
Technical Architect (as needed for infrastructure assessment)
Domain Specialists (based on focus areas identified during discovery)
1
Discovery Report
Comprehensive assessment of current state, organizational pain points, and opportunity landscape
2
Opportunity Portfolio
Ranked initiatives with detailed ROI projections and technical feasibility analysis
3
Implementation Roadmap
Phased approach with clear milestones, resource requirements, and timeline
4
Executive Presentation
Business case and strategic recommendations formatted for leadership review
5
Proof-of-Concept Design
Detailed implementation plan for highest-priority initiative
Schedule & Logistics
1
Kick-off Workshop
2-3 hours with key stakeholders to align on objectives and approach
2
Weekly Progress Reviews
30-minute check-ins to ensure alignment and address questions
3
Final Presentation
90 minutes with extended leadership team to review findings and recommendations
We offer flexible scheduling to accommodate regional time zones and stakeholder availability across your Latin American operations.
What Happens Next?
Initial Conversation
1-hour discussion of strategic priorities, current challenges, and areas of interest to customize the discovery approach
Proposal Refinement
We adjust the engagement scope based on your specific needs and stakeholder input
Rapid Kickoff
Once approved, we begin within one week and maintain momentum throughout