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Optimizing government spending with AI
Why governments don't fail due to a lack of money - but due to decision-making logic
In almost all industrialized countries, the pressure on public budgets is increasing dramatically. Climate protection, infrastructure, defence, education, demographics, digitalization - everything is important, everything is urgent, everything is competing for the same budget.
Nevertheless, the key bottleneck is not the money available. The bottleneck is the way in which government decisions are made.
The structural problem of state budgets
State budgets today are managed according to a principle that dates back to a time when systems were manageable:
- Individual projects are evaluated in isolation
- Departments optimize for themselves
- Political priorities override mathematical effects
- Synergies remain invisible
- Opportunity costs are ignored
The result:
Billions are correctly distributed - but incorrectly combined.
In reality, projects are not just competing for money. They compete for impact within an overall system.
Why classic budget logic fails
A modern state does not manage 10 or 20 projects. It manages hundreds to thousands at the same time.
Even with 50 projects
250 ≈ 1.125.899.906.842.624
possible combinations of how they could be put together.
No ministry, no committee, no court of auditors can cover this decision-making space.
Instead, it is simplified:
- according to political lines
- according to departmental logic
- according to historical budgets
- according to media attention
This is not a control system. It is a heuristic system.
The real cost factor: unseen alternatives
Every euro that flows into project A is missing in B, C, D or a better combination of all of them.
These suppressed alternatives are the largest invisible cost block of state budgets.
Not:
"How expensive is this project?"
but:
"What are we losing by choosing this combination?"
This question is practically never systematically answered today.
Modern governance is an optimization problem
A state is not an accountant. It is a portfolio manager with a social mandate.
Every project has:
- Costs
- Risks
- Effects
- Interactions
- Side effects
- Time profiles
And these parameters do not have a linear effect.
More money does not generate proportionally more effect. The right combination generates exponentially more impact.
What "optimizing expenditure" really means
Optimization does not mean:
"Spend less"
but:
"Achieve more social impact with the same budget."
This means:
- Infrastructure + housing ≠ separate effects
- Education + social policy ≠ additive effects
- Digitalization + administration ≠ isolated effects
The effect arises in the portfolio.
Why StratePlan is creating a new category here
This is exactly where StratePlan comes in.
StratePlan does not calculate individual projects. It calculates the entire decision space of a government portfolio.
Mathematically, this means
- Billions to trillions of possible project combinations
- evaluated simultaneously
- under real budget, risk and impact restrictions
- with mathematically optimized selection of the combination with maximum overall impact
This is not simulation. This is global portfolio optimization.
The effect on public budgets
Real government portfolios typically generate:
- 20-60 % more impact
- with the same budget
- without new taxes
- without new debt
- without changing political majorities
Simply by making better decisions.
Conclusion
State budget problems are not financial problems. They are decision-making problems.
Those who continue to try to control billions with Excel, committees and departmental logic will inevitably remain suboptimal - no matter how competent those involved are.
The future of government management is decision intelligence.
And those who master it will not govern harder. But smarter.
Dr. Igor Kadoshchuk is a computer scientist, algorithm architect, and one of the leading minds behind mAInthink's optimization and decision-making algorithms. As scientific director of the StratePlan™ and DeepAnT platforms, he combines in-depth mathematical research with practical applications in project portfolio optimization, business, finance, and public administration.
He holds a PhD in computer science from the renowned Moscow Institute of Physics and Technology (MIPT), where he also taught as a professor of computer engineering and mathematics. He has decades of experience developing highly complex mathematical models for project portfolio optimization and financial systems, investment planning, and strategic decision-making. His professional career includes leading positions such as Head of IT at Gazprombank and Director of Project Management at TransTeleCom.
Dr. Kadoshchuk writes on the mAInthink AI Blog. Kadoshchuk on:
- Algorithmic strategy optimization
- New methods for calculating ROI and impact
- Project portfolio optimization beyond traditional tools
- The limits of human decision-making – and how AI overcomes them
His aim: to calculate strategy, not estimate it.
His contributions combine scientific precision with clear, understandable language – always with the goal of making complex decision-making spaces transparent, manageable, and measurable.