The executive conference room falls silent when the CIO presents the IBM i transformation proposal. The CFO leans forward: “How do we know this won’t become another multi-year project that consumes budget without delivering value?” It’s the question every technology leader dreads, and for good reason.
Traditional modernization efforts consistently disappoint. Organizations spend years and millions manually rewriting code, only to recreate the same business logic on a different platform without gaining meaningful competitive advantage.
The problem isn’t ambition. It’s approach. Modernization focuses on technology refresh, essentially translating old code into newer languages while preserving the same constraints. Futurization takes a fundamentally different path — leveraging automated and agentic coding approaches to not just convert applications but enhance them for future capabilities.
Modern tools like CoderFlow help run autonomous engineering agents that compile, test, validate, and fix changes end-to-end inside your infrastructure, delivering verified outcomes rather than draft suggestions. This capability enables teams to move beyond manual cycles and toward reviewing ready-to-commit results with confidence.
The organizations that succeed with IBM i futurization share a critical trait: they asked the hard questions before committing resources. They understood that futurization isn’t a one-off project but rather a strategic capability requiring disciplined planning, measurable outcomes, and realistic expectations about complexity and timelines.
The checklist below transforms ambiguous intentions into concrete action plans. Each question addresses a critical decision point that will determine whether your IBM i futurization initiative becomes a competitive advantage or an expensive lesson in what not to do.
1. What Business Outcomes Will Define Success?
Technology initiatives that begin with “we need to modernize” rather than “we need to achieve X business result” rarely deliver satisfactory returns. This is why we talk about futurization, not modernization. Futurization focuses on evolving your business capabilities while respecting the institutional knowledge embedded in your custom-built systems.
Before evaluating any transformation approach, define the specific business metrics that will determine success:
- Revenue velocity: Reducing order processing time by 40% to enable same-day fulfillment
- Development capacity: Increasing feature delivery by 3x through AI-assisted development
- Cost reduction: Decreasing maintenance costs by 30% through automated refactoring
- Customer experience: Achieving 95% self-service completion with modern interfaces
- Integration speed: Connecting to new partners in days instead of months via APIs
- Risk reduction: Eliminating dependence on retiring developer skills
Traditional modernization vendors focus on technical conversion. Our futurization approach addresses the business outcomes that actually matter: faster innovation, reduced risk, and enhanced competitive positioning. The systems you built represent your competitive advantage. The question isn’t whether to preserve them, but how to evolve them for what’s next.
2. Which IBM i Applications and Dependencies Are in Scope?
The systems you built over decades represent institutional knowledge and competitive advantage. Legacy applications rarely exist in isolation; they connect through interfaces developed over years, trigger batch processes that downstream systems depend upon, and share data through methods that create complex interdependencies.
Traditional modernization vendors often underestimate this complexity, leading to significant project delays. Organizations that discover dependencies during transformation rather than before consistently face extended timelines and budget overruns.
Our automated capabilities identify these dependencies systematically rather than relying on manual documentation or tribal knowledge. Our AI-enhanced analysis tools map:
- Core applications: Customer-facing systems, financial processing, inventory management
- Interface points: Real-time integrations, and scheduled data exchanges
- Batch processing: Nightly jobs, month-end processing, regulatory reporting
- Data dependencies: Which systems write to shared databases, who consumes the data
- External connections: EDI partners, API consumers, third-party data providers
This comprehensive inventory isn’t just cataloging what exists. It reveals where complexity hides, identifies the critical path for transformation, and enables intelligent sequencing that minimizes risk while delivering continuous value.
3. Do We Want Coexistence, Phased Transformation, or Full Rewrite?
Here’s where most modernization projects go wrong: they force an all-or-nothing choice that maximizes risk. We pioneered coexistence technology specifically to eliminate this false choice. Our approach allows legacy and futurized components to operate simultaneously, enabling you to transform incrementally while maintaining business continuity.
Coexistence means your green-screen applications work alongside modern web interfaces. RPG business logic continues processing transactions while new Node.js services handle API requests. Data flows seamlessly between old and new. Most importantly, you can prove the approach works with lower-risk applications before tackling mission-critical systems.
Phased transformation converts applications incrementally using our algorithmic refactoring combined with AI orchestration. This autonomous approach completes entire conversion tasks without constant human intervention, dramatically accelerating timelines while maintaining accuracy. Organizations build internal capabilities, refine processes, and demonstrate value continuously rather than waiting years for a big-bang cutover.
Full rewrite carries the highest risk and rarely makes business sense for custom-built systems where your competitive advantage lives in the business logic. When necessary, Profound AppEvo’s automated conversion preserves this logic while transforming the implementation.
Define the criteria that trigger each phase. Document the business conditions, technical milestones, or risk factors that determine when to accelerate or adjust. This adaptive approach turns transformation from a high-stakes gamble into a managed capability.
4. What Is Our Data Posture: Access, Quality, and Timeliness?
Modern capabilities like AI analytics, real-time APIs all depend on one fundamental requirement: accurate, accessible, timely data. Your transformation plans can only be as sophisticated as your data infrastructure allows.
Assess your current data reality:
- Data Access: Can you expose data to new applications without compromising security? Do you have standardized methods for data retrieval, or does each integration require custom development?
- Data Quality: How accurate is the information in your core systems? Research from IBM indicates that poor data quality costs organizations an average of $12.9 million annually. Issues that seem minor in batch processing environments become critical when powering real-time decision systems.
- Data Timeliness: How fresh does information need to be for your use cases? Overnight batch updates might work for reporting, but customer-facing applications often require real-time access.
- Master Data Management: Where do authoritative records live? When customer information exists in multiple systems, which one represents the truth? Resolving these questions before transformation prevents architectural problems that are expensive to fix later.
Organizations often discover during transformation that their data isn’t ready to support modern applications. Addressing data quality, governance, and access patterns upfront prevents costly rework when new systems go live.
5. How Will We Secure Data, Models, and APIs?
Security and governance cannot be an afterthought in enterprise transformation. The capabilities that make modern applications valuable, such as API access, AI model integration, and cloud connectivity, also create new security considerations requiring proactive planning.
Your security framework must address:
Data Protection:
- Encrypted connections
- Field-level security for sensitive information
- Compliance with industry regulations (HIPAA, PCI DSS, GDPR)
Access Control:
- Authentication mechanisms for users and systems
- Role-based access to ensure appropriate data visibility
- API keys and token management
- Comprehensive audit trails for compliance and forensics
Model Governance:
- Controls for AI model selection and deployment
- Granular data access control for models
- Model version management and rollback capabilities
- Monitoring for model drift and performance degradation
Vendor Transparency:
- Understanding where your data resides when using external services
- Contractual guarantees about data usage and retention
- Compliance certifications from third-party vendors
- Exit strategies if vendor relationships change
According to IBM Security research, the average cost of a data breach reached $4.4 million. Ensure compliance requirements specific to your industry and geography are identified and addressed up front. Retrofitting security into completed transformations costs significantly more than building it into the foundation.
6. Do We Have the Right People, Skills, and Operating Model?
This question reveals the fundamental difference between modernization and futurization. Traditional modernization requires armies of manual converters who understand both legacy and modern languages. Futurization leverages AI-powered refactoring to dramatically reduce this dependency while simultaneously building internal capabilities.
63% of executives cite skills gaps as the primary barrier to transformation. The traditional solution involves expensive hiring battles for scarce RPG developers or costly offshore or near shore teams. Our approach transforms this challenge into an opportunity.
How AI-Powered Futurization Changes the Equation:
With our algorithmic precision combined with AI orchestration, your existing team gains leverage they’ve never had. Autonomous completion of conversion tasks means fewer specialists required for transformation. Automated discovery eliminates months of manual analysis. AI-assisted refactoring handles complexity that would require deep expertise in traditional approaches.
Successful futurization requires new ways of working. Profound Logic provides comprehensive support throughout:
- Knowledge transfer from our 25+ years of IBM i transformation expertise
- Architectural guidance for API enablement and cloud readiness
- Change management support for affected user communities
The Build-Buy-Partner Decision:
Most organizations lack experience with modern architectures, AI-assisted development, and enterprise-grade API platforms. Rather than spending years building these capabilities internally or depending entirely on external consultants, our model combines technology platforms with implementation expertise. You accelerate transformation while simultaneously developing internal capabilities for long-term self-sufficiency.
7. What Does "Live Production" Look Like: Rollback, SLAs, and Monitoring?
Coexistence technology fundamentally changes production deployment strategy. Instead of high-risk big-bang cutovers that keep executives awake at night, we enable gradual rollouts where legacy and futurized components operate side-by-side. This approach transforms “go-live” from a moment of maximum risk into a series of controlled transitions.
Release Gates with Coexistence:
- Parallel operation validation (legacy and futurized components)
- Data consistency verification across old and new systems
- Rollback procedures that don’t disrupt ongoing operations
- User training for components as they futurize
Service Level Agreements:
- Uptime commitments maintained during transition periods
- Response time parity between legacy and futurized components
- Transaction throughput during peak periods
- Batch processing windows honored throughout transformation
Monitoring and Observability:
- Comparative metrics tracking (old vs. new performance)
- Business metric validation (confirming functional equivalence)
- User experience monitoring across all interfaces
Risk Mitigation Through Phased Deployment:
Organizations using traditional modernization face all-or-nothing pressure. One problem can force rolling back months of work. Profound AppEvo’s coexistence capability eliminates this exposure. Deploy individual components, validate behavior in production, and proceed at a pace that matches your risk tolerance.
This controlled approach enables continuous improvement rather than hoping everything works perfectly on day one. Issues get identified and resolved incrementally rather than becoming project-threatening crises.
8. What Is Our Integration and API Strategy?
This question separates organizations positioning for the future from those stuck in the past. Legacy integration patterns (point-to-point connections, direct database access, file-based exchanges) worked adequately when systems changed slowly. Today’s business velocity demands something fundamentally different.
APIs and AI represent the new value layers that transform custom-built IBM i systems from isolated applications into strategic business platforms. Rather than viewing your decades of business logic as technical debt, futurization positions these systems as engines for innovation.
Why APIs Matter for Futurization:
API-driven architectures significantly reduce time-to-market for new capabilities compared to traditional integration. More importantly, APIs enable your futurized applications to participate in modern ecosystems: partner integrations, cloud services, mobile applications, and AI platforms all depend on robust API infrastructure.
Profound API: Purpose-Built for IBM i Integration
While Profound AppEvo transforms your application code, Profound API provides the integration layer that connects your IBM i systems to the modern enterprise. Rather than forcing you to build custom integration code or expose your databases directly, Profound API creates secure, standards-based REST APIs from your existing RPG programs and database tables.
This approach delivers immediate value:
Rapid API Creation:
- Generate REST APIs from RPG programs without rewriting code
- Expose database tables as secure web services
- Create APIs in minutes rather than weeks of custom development
- Maintain your existing business logic while enabling modern access patterns
Enterprise-Grade Security:
- Authentication and authorization built into every API
- Role-based access control protecting sensitive data
- Comprehensive audit trails for compliance requirements
- Rate limiting and throttling to protect backend systems v
Standards-Based Integration:
- RESTful principles for intuitive resource access
- OpenAPI/Swagger documentation generated automatically
- JSON responses compatible with modern applications
- Versioning strategy that doesn’t break existing consumers
Operational Excellence:
- Real-time monitoring of API usage and performance
- Error tracking and troubleshooting capabilities
MCP: Secure AI Integration for IBM i
Beyond traditional API integration, our Model Context Protocol (MCP) server capabilities enable secure, standardized connections between your IBM i and external AI tools. Rather than building custom integrations for each AI platform, MCP provides a universal standard that leading AI providers like OpenAI, Microsoft, and Anthropic have adopted.
This means your IBM i systems can now communicate directly with ChatGPT, Claude, and other cutting-edge AI platforms without exposing sensitive data or compromising security.
MCP server capabilities make it easy to:
- Connect IBM i data securely to external AI tools using industry-standard protocols
- Enable AI assistants to query your business data without direct database access
- Maintain complete control over what data AI platforms can access
- Leverage your decades of business logic in AI-powered workflows
- Future-proof your AI strategy as new platforms emerge
Moving from legacy integration to modern API architectures represents a significant shift in how systems communicate. The combination of Profound AppEvo’s automated refactoring, Profound API’s integration capabilities, and MCP support for AI platforms positions your futurized applications for agility that traditional modernization cannot deliver. Your IBM i systems become accessible to cloud applications, mobile apps, AI platforms, and partner ecosystems without compromising security or performance.
9. How Will We Manage Third-Party AI Models and Vendor Risk?
As organizations incorporate autonomous coding and advanced tooling, vendor management becomes strategic. Rather than locking into a single model provider, prioritize platforms that support multiple model options and flexible execution strategies. CoderFlow, for example, enables secure agentic coding inside your environment while working with multiple cloud models — minimizing lock-in and operational risk as technologies evolve
10. What's Our Phased Roadmap: Milestones, Funding, and Executive Sponsors?
Strategy without execution is theoretical. A structured roadmap with defined milestones, phased funding tied to value delivery, and executive sponsorship ensures transformation progress continues even through organizational challenges. Embed measurable objectives such as pilot wins, capability scaling, and longer-term architecture goals.
Develop a structured transformation roadmap:
Short-Term Wins (3-6 months):
- Demonstrate value through focused pilot projects
- Prove technical approach with lower-risk applications
- Build team capabilities and confidence
- Generate momentum and stakeholder buy-in
Mid-Term Consolidation (6-18 months):
- Scale successful patterns to broader application portfolio
- Standardize processes and tooling
- Develop internal expertise and best practices
Long-Term Transformation (18-36 months):
- Complete migration of mission-critical systems
- Achieve target architecture for future capabilities
- Establish continuous improvement processes
- Realize full business value from transformation investment
The roadmap itself, however, only succeeds when supported by the organizational elements that enable execution. Your timeline means nothing without the people, budget, and authority to make it happen.
Critical Success Factors:
- Executive Sponsorship: Transformation initiatives face competing priorities, resource constraints, and organizational resistance. Executive sponsors must actively champion the initiative, remove obstacles, and make difficult trade-off decisions when conflicts arise.
- Phased Funding: Rather than requesting multi-year budgets upfront, structure funding in phases tied to delivered value. This approach reduces financial risk while demonstrating returns that justify continued investment.
- Measurable Milestones: Define concrete deliverables for each phase that stakeholders can evaluate. Vague promises of “improved architecture” don’t sustain support during inevitable challenges. Specific metrics like “reduce order processing time by 25%” create accountability and demonstrate progress.
- Course Correction Mechanisms: No transformation plan survives contact with reality unchanged. Build in regular review points where you assess progress, evaluate lessons learned, and adjust approach based on results. This adaptive mindset prevents small problems from becoming project-threatening crises.
Organizations often underestimate the organizational change management required for successful transformation. Technical conversion represents only part of the challenge. User adoption, process changes, and cultural shifts require sustained attention throughout the transformation lifecycle.
Turning Futurization From Risk Into Repeatable Capability
The questions outlined above transform IBM i futurization from a daunting endeavor into a strategic capability you can execute with confidence.
The difference between initiatives that deliver value and those that stall lies in:
- Understanding what futurization means
- Choosing partners and platforms with complete capabilities
- Focusing relentlessly on business outcomes
Modern tools that support governed, agentic coding alongside robust transformation technology help teams accelerate delivery while reducing risk.
Your Next Step: From Questions to Action
The checklist above gives you a framework to plan your IBM i futurization initiative with confidence. These questions separate transformation programs that create competitive advantage from those that consume resources without meaningful returns.
Ready to explore how platforms like CoderFlow and Profound Logic’s complete futurization continuum can accelerate your journey? Reach out to learn how autonomous, governed engineering automation helps turn planning into measurable results: Futurization@ProfoundLogic.com