Building the Infrastructure for the MI Era
The future of Machine Intelligence will not be built on algorithms and chips alone. It will depend on where we build, how we power, and whether we build the infrastructure responsibly.
We are entering a new technological age. Artificial intelligence is moving rapidly from research labs and specialized applications into nearly every part of our economy and daily lives. We often call this the AI era. But at Department of Technology, we believe a broader term better describes what is unfolding: the MI era—the Machine Intelligence era.
This is more than a change in terminology. It reflects the scale of the transformation underway. Intelligent machines, increasingly capable computing systems, and the networks connecting them are becoming foundational infrastructure for business, science, education, national security, healthcare, and public services.
But there is a critical reality that can get lost in the excitement over new models, faster chips, and extraordinary software: Machine Intelligence requires physical infrastructure.
It requires data centers—large, sophisticated facilities filled with computing equipment that must operate continuously. Those facilities require enormous amounts of electricity, dependable transmission lines, cooling systems, water or other cooling resources, communications networks, skilled workers, secure sites, and communities willing to host them.
Building this infrastructure will be one of the defining challenges of the MI era.
That is why we are launching a dedicated Data Centers series.
The questions America and the world must answer
We intend to examine the data center challenge through the essential questions that should guide every major infrastructure decision:
- Who is building these facilities, financing them, operating them, regulating them, and benefiting from them? Who is responsible when costs or consequences fall on local communities?
- What should a modern data center include—not only in computing capacity, but in power systems, cooling, cybersecurity, physical security, resilience, and environmental performance?
- When should facilities be built, and how should construction be coordinated with the availability of electricity, transmission capacity, equipment, workers, and other essential resources?
- Where should data centers be located? Proximity to users and fiber networks matters, but so do available power, transmission access, land, water, climate, permitting, and the needs of surrounding communities.
- Why are these facilities necessary, what public and economic value can they create, and how do we distinguish essential infrastructure investment from projects that shift costs and risks onto others?
- How can we build, connect, operate, and expand data centers reliably, affordably, securely, and responsibly?
These questions are connected. A site that looks attractive because land is available may not have sufficient electrical capacity. A region with abundant generation may lack the transmission infrastructure to deliver power where it is needed. A project that makes sense on paper may encounter public opposition if residents are not given clear information about electricity costs, water use, construction impacts, and long-term commitments.
There is no single answer that works everywhere. The right approach will depend on local conditions, technology, energy resources, infrastructure, and community priorities.
The electric grid is part of the AI story
One of the central themes of this series will be the relationship between data centers and the electrical grid.
The MI era cannot advance at the speed of software if the infrastructure supplying its electricity cannot keep pace. Generation capacity, transmission lines, substations, interconnection processes, energy storage, backup systems, and grid reliability all matter.
We must look beyond whether enough electricity exists in the abstract. We must ask whether it can be delivered to the right location, at the right time, at a predictable cost, and with the reliability that modern computing demands.
We must also examine how new demand affects existing customers. Data center development should not automatically mean higher electricity bills, strained local infrastructure, or reduced reliability for households and established businesses. The costs and benefits must be understood, disclosed, and fairly allocated.
Building with communities, not simply in them
Technology leadership cannot be measured only by the number of facilities announced, the amount of capital invested, or the computing capacity installed.
It must also be measured by whether projects are responsibly planned, whether communities have meaningful information and a voice in decisions, whether infrastructure costs are fairly assigned, and whether the benefits extend beyond the companies operating the facilities.
Public trust is not an afterthought. It is part of the infrastructure.
That means transparency about power requirements, water and cooling strategies, environmental impacts, tax arrangements, utility investments, and emergency planning. It means recognizing that communities are not merely locations on a map. They are partners whose long-term interests deserve consideration.
A practical guide to the infrastructure of the MI era
In this series, we will explore the data center ecosystem from the ground up: site selection, electricity generation, transmission and distribution, grid connections, cooling, water, energy storage, renewable and other energy sources, reliability, cybersecurity, construction, financing, regulation, workforce development, and the relationship between technology companies and the communities that host their facilities.
We will look at the roles of federal, state, and local governments, utilities, developers, technology companies, investors, engineers, regulators, and residents. We will examine emerging solutions as well as the obstacles that could slow development or undermine public confidence.
Our goal is not to advocate for building every proposed data center, nor to oppose development simply because it is large or energy-intensive. Our goal is to help readers understand what responsible development requires—and what questions should be asked before decisions are made.
America’s ability to lead in Machine Intelligence will depend on more than inventing the next generation of chips and software. It will depend on whether we can build the power systems, networks, facilities, policies, and public partnerships that allow those technologies to operate at scale.
The MI era needs more than computing power. It needs a plan for the infrastructure that makes computing power possible.
That is what this series is about.
Our Data Centers Series
Where we build, how we power, and whether we build the infrastructure for Machine Intelligence responsibly.
Introducing Our New Data Centers Series
Machine Intelligence needs physical infrastructure. Our new Data Centers series asks who builds, finances, powers, and regulates data centers, where they belong, and how local communities can truly benefit. Learn what responsible development requires, from electricity, cooling, and site selection to water use, sustainability, security, workforce needs, and public trust in the Machine Intelligence era.
Read the introduction →Ten Questions Every Candidate and Elected Official Should Answer About Data Centers and AI
Voters deserve clear, specific answers about who pays for data centers, who is accountable, and what happens if AI does not deliver. This nonpartisan scorecard gives voters, reporters, and candidates ten questions for any office, with evidence, signs of strong and evasive answers, a simple scoring guide, and a print-ready list to send to everyone.
Read article →Isn’t This Just Another Bureaucracy? Answering the Hardest Questions About Elected Technology Leaders
Skeptics ask whether elected technology leaders would just add another layer of bureaucracy. It is a fair question. This FAQ answers nine of the hardest objections, from overlap with utility regulators to capture by industry, cost, politics, and speed, using real precedents like elected utility commissions and honest limits on what our proposal can promise.
Read article →What Every County Treasurer Should Model Before AI Layoffs
AI could shrink the labor income that funds local government, while data center revenue can concentrate budgets in one fragile industry. This guide shows county treasurers how to build a simple, practical scenario worksheet: map revenue, run displacement and bust scenarios, set reserves and triggers, and publish the results before layoffs or valuation drops arrive.
Read article →A Technology Leader’s First Year: A Guide for Counties and Cities
Counties and cities are approving data centers faster than they can possibly study them. This first-year guide for local technology leaders covers what to do each quarter: ending by-right approvals, writing water, noise, and decommissioning rules, joining utility rate proceedings, negotiating community benefit agreements, ending secret deals, and preparing the budget for what comes next.
Read article →Preemption Without an Owner: Why the Federal-State AI Fight Needs Someone Accountable
Washington is fighting over whether federal law should override state AI rules. Both sides have real arguments. But whoever wins, someone must enforce the result and answer to voters. This analysis lays out the strongest case for and against preemption, what the record actually shows, and three simple tests any national AI standard should meet.
Read article →A Briefing for the New Congress: What the Last Two Years Got Wrong, and What to Do Differently
The last Congress agreed on almost nothing about AI policy, then watched its one bipartisan data center bill pass the House 417-3 and stall in the Senate. This briefing for new members explains five costly mistakes to avoid, from back-door preemption to election-year gamesmanship, and what a single accountable technology office could realistically do differently.
Read article →How a Data Center Deal Actually Gets Made, and Where the Public Gets Left Out
From shell companies and code names to secret NDAs and quiet utility requests, most data center deals are usually shaped long before residents hear a word. This step-by-step guide shows how a typical deal gets made, who decides at each stage, where the public is shut out, and what an accountable technology leader would change.
Read article →The First 100 Days: A Technology Agenda for the Next Congress
A new Congress has 100 days to govern the technology buildout instead of reacting to it. This practical agenda for members of both parties covers ratepayer protection, ending secret data center deals, preparing for AI’s impact on federal revenue, and creating a single point of accountability, with the evidence and key objections behind each step.
Read article →The Data Center Casino: Why America Needs Elected Technology Leaders Now
America needs more data centers, but both parties have treated them like a casino: chasing tax breaks and investment while ignoring grid strain, bubble risk, China’s power advantage, and AI job losses that threaten the tax base. See why elected technology leaders at every level are needed right now to build smarter, safer, and fairer.
Read article →Voters Didn’t Reject AI. They Rejected Building It Backward
Voters didn’t reject AI. They rejected building it backward. After 40 of 41 data center ballot measures favored limits on November 3rd, see how rising power bills, strained grids, and secret deals fueled the backlash, how China’s energy buildout compares, and what transparent, accountable planning could do to restore public trust in America’s AI future.
Read article →Powering the AI Revolution
Discover why America’s AI data center future depends on a reliable electrical grid. Explore how data center location, electricity generation, transmission infrastructure, grid capacity, energy storage, backup power, and renewable energy shape the next generation of AI infrastructure. Learn why reliable electricity, responsible planning, and community impact are essential to powering the Machine Intelligence era.
Read article →An Open Letter to Every Elected Official in America: Put the Country First
An open letter urging Democrats, Republicans, and every elected official to start a nationwide public discussion on creating a Department of Technology at the local, county, state, and federal levels. Learn why AI data centers, secret NDAs, and conflicts of interest demand accountable, nonpartisan technology leadership before the next major data center contracts are signed.
Read article →America Won’t Lose the AI Race to China’s Chips. It Will Lose It to Distrust.
America won’t lose the AI race to China’s chips. It will lose it to distrust. After nearly 40 data center ballot measures in 2026, voters are demanding transparency, accountability, and reliable, affordable power. Learn how conflicts of interest, grid limits, and secret deals threaten U.S. AI leadership, and what a Department of Technology could change.
Read article →