Rudi Mohamed

Impact

Evidence, not adjectives.

Three bodies of work, each written the same way: the problem, the constraints, the decisions, and what measurably changed. Where an outcome belongs to a team or the organization, I say so.

These case studies omit confidential and security-sensitive details about government systems. Metrics are published only when verified and approved for release.

Modernization

Modernizing mission-critical public-sector systems

The challenge
Modernize statewide tax systems that administer more than 40 state and local taxes and support the collection of over $23 billion in annual tax revenue—all without disrupting essential services.
Why it mattered
Reliable, secure tax systems are essential to protecting government revenue, sustaining critical public services, and preventing disruptions that affect residents, businesses, and government operations.
Constraints and risks
Modernize mission-critical tax systems while ensuring uninterrupted revenue collection, coordinating across 87 counties and government agencies, meeting regulatory deadlines, and protecting sensitive data and system integrity.
Decisions and interventions
Led phased, risk-managed tax system modernization using Scaled Agile and DevSecOps to maintain uninterrupted operations, strengthen security, increase electronic filing adoption, and accelerate payment and tax-return processing.

Implementation approach
Applied a phased modernization strategy using Scaled Agile and DevSecOps to balance delivery speed, operational stability, and risk management.
Measurable outcome
Increased electronic filing adoption from 20% to 80%, reduced tax payment distribution time from 30 to 7 days, and achieved a 95% increase in business and fiduciary electronic returns processed within 30 days.
My role vs. team
Enterprise Architect
Lessons for executives
Successful modernization is not simply about replacing legacy technology; it is about improving performance while preserving the services people depend on.
Technology Value

Turning technology investments into measurable value

The challenge
Transform fragmented technology spending into a coordinated investment strategy that aligns IT resources and investments with enterprise priorities, reduces duplication, and delivers measurable societal value.
Why it mattered
The opportunity was to move beyond managing technology costs toward making informed investment decisions based on public value, operational risk, and long-term sustainability.
Constraints and risks
Fragmented accountability: Technology investment decisions required coordination across agencies and their divisions, executive leadership teams, and MN.IT.
Decisions and interventions
Shifted investment decisions toward public value, strengthened investment governance that prioritizes investments, and identified opportunities to reduce unnecessary spending.
Implementation approach
Applied a structured, enterprise-wide technology investment management approach built around five disciplines: Assess, Prioritize, Govern, Execute, and Optimize.
Measurable outcome
Improved enterprise-wide investment discipline and visibility to better align technology spending with societal value and agency priorities.
My role vs. team
Technology Investment Strategist: Enterprise Technology Investment and Value Optimization.
Lessons for executives
Technology spending creates cost. Strategic investment creates value. Decide up front what will change, who owns it, and how you'll measure it.
AI in the Real World

Moving AI from experimentation toward responsible performance

The challenge
Modernize mission-critical housing finance systems, migrate legacy applications and data to modern platforms, and accelerate technology delivery—all without increasing staffing.
Why it mattered
Legacy systems, manual processes, and limited delivery capacity constrained the agency's ability to respond quickly to changing business needs.
Constraints and risks
Increase solution delivery capacity without adding headcount, while maintaining regulatory compliance, protecting sensitive information, and ensuring AI-generated outputs are secure, accurate, and reliable.
Decisions and interventions
Established risk-based AI governance and integrated GitHub Copilot into existing Agile and DevSecOps workflows to increase development capacity, accelerate modernization, and ensure secure, accountable AI adoption.
Implementation approach
Applied a phased approach that combined enterprise modernization, AI-assisted development, and responsible governance.
Measurable outcome
The initiative successfully achieved a 40% increase in solution delivery capacity without additional staffing while maintaining security, quality, and operational reliability. More measurements are in progress.
My role vs. team
Chief Information Officer — Enterprise Modernization, AI Governance, and Technology Value
Lessons for executives
AI creates measurable value when it is responsibly integrated into mission-critical workflows through strong governance, human accountability, and disciplined execution, increasing organizational capacity without introducing unacceptable risk.

Framework

Five questions before an AI workflow ships

  1. OwnerWho is accountable for the result?
  2. BaselineHow does the work perform today?
  3. DataIs the data ready, permitted, and trustworthy?
  4. VerificationWhere does a human check the output?
  5. MeasureWhat number should move, and by when?

Proposed framework by Rudi Mohamed. Opinion, not a standard.

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