Everything you need to build, govern, and scale AI across your agency—from product updates and case studies to expert guidance.
General
Data centers have become the face of America's AI infrastructure boom. But the real fight isn't about buildings. It's about who gets access to limited power, water, land, and public trust and who pays the cost of expanding them.
Healthcare
More than 60% of local health departments have no dedicated informatics staff, so AI governance has to run on the people already on payroll. Three roles, four impact tiers, and 90 days to get there.
Generative AI did not create new legal obligations for local public health. It shortened the time it takes to breach the ones you already have — and three sets of rules apply at once.
Official surveys put AI use in local health departments at 5%. Ask the staff and it is closer to 75% here is the plain-language literacy and the five guardrails that close the gap.
Product Updates
Configuring an AI governance policy is the easy part. Proving it's actually working, on every endpoint, against every user, is where most agencies get stuck. Turn on a Block rule. Is it firing? On which machines? Against which users? When an employee reports that ChatGPT stopped working, is that Darwin, or something else? Darwin's new Activity Log answers those questions.
PR
Awarded under Carahsoft Bulk Purchase Agreement BP2026-0015, the agreement gives every eligible public organization pre-negotiated pricing on Darwin's AI governance platform with no competitive procurement required — one of only four active bulk purchase agreements statewide.
AI governance has always drawn the line at identity: work email = governed, personal email = shadow. But there's a gap that identity alone can't catch. An employee signed in with their agency email, working inside a personal ChatGPT workspace. The account checks out. The workspace doesn't. And every session flows outside the agency's data processing agreements, with no record in the tool's admin console. Darwin's new Workspace Detection closes that gap.
Policy enforcement doesn't happen in a boardroom; it happens in the pop-up an employee sees when they try to paste PII into ChatGPT or upload a Confidential file to an unapproved tool. That moment is where governance either becomes clear or becomes a help-desk ticket. Darwin's new Customizable End-User Messages lets admins rewrite every enforcement pop-up—Title, Subtitle, Body—in the agency's own voice and branding, with dynamic parameters for the tool name, user, and links to internal policies or request forms.
Case Studies
As artificial intelligence became embedded across everyday workplace tools, CapMetro moved early to establish policy before expanding AI adoption. With Darwin AI, the agency gained real-time visibility into how AI was actually being used across departments, replacing assumptions with data.
Most agencies have already done the work: files classified in Microsoft Purview, labels embedded into every document, policy decisions built into the data itself. Inside Microsoft, those labels work. Outside Microsoft, they stop mattering. A Confidential file uploads to ChatGPT as easily as a public one. Darwin's Sensitivity Labels Enforcement changes that.
Every day, governance teams miss events that need a fast response. Not because Darwin isn't catching them, but because catching them has meant logging into the platform to check. A critical alert sits unseen. An access request waits days for a decision. A newly discovered shadow AI tool operates for a week before the right person notices. Darwin's Notification Center changes that.
Government
More than half of government organizations now use AI, but fewer than half have a formal AI policy. Here's the legal and security case for closing that gap and how to write an AI policy your agency will actually follow.
New enterprise capabilities advance Darwin Enterprise, the company's offering for governing AI across large-scale, multi-agency government.
Across state and local government, the number of AI tools employees can access has exploded. But governing that reality has been stuck at an all-or-nothing decision: either everyone can use a tool, or no one can. Darwin's User-Level Access Controls changes that.
Across state and local government, AI tools are processing more sensitive information every day. Protecting that data comes down to one thing: knowing exactly what to detect, and what to leave alone. For most compliance teams, that's harder than it sounds. Generic detection flags too much, drowning teams in false positives. And the data that matters most to a specific agency; permit IDs, case numbers, internal identifiers, often goes unprotected. Darwin's Custom Data Protection solves both sides.
AI is often called a "black box," but Anthropic's researchers have begun mapping how these models actually work—suggesting the mystery isn't permanent. And the more we decode AI, the less artificial it looks: it's less an alien intelligence than a reflection of our own. The real challenge isn't making AI smarter, but making it accountable.
From governed AI to agentic workflows, starting with Fire & EMS scheduling.
Employees aren't just prompting AI anymore—they're uploading files. Darwin's File Upload Controls close this critical governance gap by giving agencies visibility into file uploads, detecting PII within documents, and enforcing policies based on tool trust levels. The result: secure AI adoption without slowing down the workforce.
Pope Leo XIV's AI encyclical isn't regulation, it's moral agenda-setting. The real test: can our institutions govern AI before profit and power override ethics?
Most California agencies are no longer asking whether to use AI. Employees are already pasting work into chatbots, and vendors are already embedding models into the products agencies buy. The real challenge has shifted: how do you take the experiments already running across your organization and move them into production, safely, defensibly, and at scale?
Most AI governance happens too late, after a tool is already in use and the risk is already live. Darwin's AI Tool Explorer flips that, letting security and IT admins evaluate and classify AI tools before they ever reach the environment. Here's how it closes the gap between first use and real oversight.
The conversation about AI and work has mostly focused on replacement. Which jobs will disappear? Which workers will be displaced? Which companies will use AI to cut headcount? That conversation is no longer theoretical. It is showing up in how companies hire, reorganize, and decide what work still requires people.
Georgia Technology Authority selects Darwin AI to anchor its statewide AI strategy, combining governance and infrastructure to lead public-sector AI nationally.
Texas cities, counties, and agencies can now procure Darwin's AI governance and agentic workflow platform through a cooperative contract — no separate RFP required.
Across state and local government, AI tools are processing more sensitive information every day; citizen records, case files, agency-specific identifiers. Protecting that data starts with knowing exactly what to detect and what to leave alone. Custom Data Protection gives compliance and policy admins one place to manage every detection pattern Darwin uses: inspect the built-in ones, tune them to fit their agency, and create new patterns for the data that's unique to them.
Darwin is incredibly proud to announce that our Co-Founder and CEO, Noam Maital, has been named to Constellation Research’s Business Transformation 150 (BT150). This prestigious global list recognizes the top executives leading innovative business transformation initiatives and actively shaping the future of enterprise technology.
As AI adoption surges across the public sector, many agencies are facing a growing governance gap. This article outlines the risks of inaction and practical steps leaders can take to regain control.
For the past few years, the conversation around AI has focused on what’s visible. Bigger models, better benchmarks, faster gains. It’s an easy story to follow and an even easier one to sell. But that surface view misses where the real constraints are starting to show up. Not in the models themselves, but in the systems underneath them.
5 Takeaways from the InnovateUS Series on What Public AI Actually Means for Government
AI Adoption and Compliance Solutions Now Available to the Public Sector.
Darwin’s AI Risk Center gives government teams a single place to see, prioritize, and act on AI risk across their organization. It turns fragmented alerts into clear, one-click remediation actions, helping teams move from detection to resolution quickly and at scale.
GovAI Podcast
In this episode of the GovAI Podcast, Noam Maital and Dustin Haisler are joined by Benjamin Palacio, Senior IT Analyst for Placer County, California and a longtime practitioner on the frontlines of government AI. Ben has been building AI solutions since 2018, well before the current wave of generative AI, and brings a rare, hands-on perspective on how AI has evolved inside government over the past several years. They explore what’s actually changing (and what isn’t), from early rule-based chatbots to today’s real-time, dynamic AI systems and what that means for agencies trying to move from experimentation to real deployment. The conversation dives into how AI is being applied today, including chatbots, automation, and citizen-facing tools, as well as the operational realities of adoption: procurement challenges, data governance, validation, and the risks of vendor lock-in. They also tackle one of the biggest questions in government today: Will AI replace workers or fundamentally change how work gets done?
RAG has become the default way to make AI systems useful, but it was never a true solution to reasoning. As new approaches emerge—from structured retrieval to world models—it’s becoming clear where RAG works, where it breaks, and what comes next.
California just gave agencies 120 days to embed AI governance into procurement. Vendors must now prove safeguards around bias, civil rights, and content safety and agencies need a clear inventory of every AI tool they use. AI governance isn’t optional anymore. It’s becoming a requirement.
Federal policy may shift who regulates AI development—but it doesn’t change your responsibility to govern its use. State and local agencies still own procurement, data security, and the fast-growing shadow AI problem inside their organizations.
China’s AI ecosystem is entering its industrial phase: faster, cheaper, and increasingly competitive with the frontier. In some domains, it may already be pulling ahead. The question is no longer whether Chinese models can match Silicon Valley. It’s whether structural limits on openness, trust, and global adoption will keep the AI market split into two parallel systems—powerful at home, but constrained abroad.
Season 2 of the GovAI Podcast is here. AI is evolving faster than government policy, procurement, and regulation can keep up and that gap is creating both massive opportunity and real risk. In this kickoff episode, Noam Maital and Dustin Haisler break down what’s happening right now across the AI landscape: from federal and state regulation battles to the race between frontier models like OpenAI, Gemini, and Copilot. They also explore what agencies actually need to be doing today to prepare for the next wave of AI adoption. From shadow AI inside agencies to agentic systems and citizen-facing AI, this conversation looks ahead to where government AI is heading in 2026 and beyond.
Darwin AI joins NVIDIA Inception to accelerate governed AI for state and local government, advancing compliant, secure AI workflows and infrastructure.
“Vibe Governing” applies the idea of vibe coding to the public sector: when AI lowers the barrier to building, governments can focus on clearly defining problems rather than managing complex execution. With strong governance and oversight in place, they can move from stalled pilots to fast, accountable deployment—turning public intent into real solutions.
As one of Washington’s fastest-growing cities, Lake Stevens moved early to address the risks of Shadow AI and ungoverned generative tools. With Darwin AI, the city gained visibility, enforced policy guardrails, and ensured full auditability to meet public records requirements.
Darwin’s CEO Noam Maital reflects on OpenClaw as a preview of AI’s next phase: embedded, always-on, and woven into daily workflows. The real shift isn’t technical, it’s structural. As AI quietly handles more decisions across messages, files, and schedules, the risk isn’t failure, but fading oversight. The piece explores why visibility and user control will determine which systems people ultimately trust.
Darwin AI has been named to Government Technology’s 2026 GovTech 100, recognizing the most innovative companies serving state and local government. One of only eight new additions this year, Darwin was honored for its leadership in AI governance, helping agencies scale AI safely with visibility, compliance, and trust through its Govern™ and LaunchPad™ platforms.
Darwin’s CEO Noam Maital explores how AI’s massive appetite for DRAM is monopolizing global supply and diverting critical silicon away from traditional consumer electronics. This structural shift is set to drive up costs for smartphones and laptops as the rising price of semiconductor "intelligence" eventually hits the consumer’s wallet.
The AI boom is often framed as a race for bigger models and faster chips, but the real bottleneck is far more basic: power. AI runs on compute, compute runs on electricity, and electricity is constrained by grids, permitting, and infrastructure that move at government speed. As demand for AI data centers explodes, delays in transmission, interconnection, and approvals are shaping where and how AI can scale—sometimes pushing capital to consider extreme alternatives like space-based compute. The takeaway for governments is clear: responsible AI leadership is no longer just about policy.
AI Guides
The Trump administration’s new Executive Order seeks to preempt strict state regulations on private AI development to reduce compliance burdens, but it explicitly leaves state & local government authority over internal AI use and procurement intact. While federal agencies look to challenge provisions of state laws on private sector use of AI, impacted public agencies retain full responsibility for managing their own AI tools, making internal governance a critical and immediate priority.
Darwin’s CEO and Co-Founder, Noam Maital, explores how the evolution of writing tools, from early keyboard systems like China’s Wubi method to modern AI-powered prediction, reveals the quiet but powerful ways technology shapes how we communicate. Noam argues that as AI becomes more involved in finishing sentences, drafting language, and guiding ideas, the real priority is preserving human intent and authorship. What is critical, however, is intentional design that gives users control, ensures transparency, and protects diverse voices, positioning language technology as essential civic infrastructure. His message is clear: AI should accelerate our work, not define it, and trust is built when people remain firmly in the author’s seat.
Darwin AI achieves TX-RAMP Level 2 Certification, enabling Texas agencies to meet TRAIGA AI governance standards ahead of 2026.
Darwin AI has been named to the 2025 AI Disruptors 60 by TechCrunch and Greenfield Partners, following its $15M Series A, which was announced last week.
Darwin AI has raised $15 million in Series A funding led by Insight Partners to help governments adopt artificial intelligence safely, transparently, and at scale.
Governments are shifting from chatbots and productivity tools to agentic AI that can act on behalf of staff and citizens. To use this moment wisely, agencies must build the infrastructure, governance, and accountability needed to keep pace and manage risks.
In this GovAI podcast episode, Vermont CIO Denise Reilly-Hughes shares her journey from the private sector to government, stressing a human-first approach to technology. She discusses the need for AI ethics, learning through failure, challenges in managing public records, AI’s role in disaster response, and building strong vendor partnerships.
Innovation
AI can rebuild the Consumer Price Index, turning one outdated “average basket” into real-time, people-centered inflation data.
Starting January 1, 2026, the Texas Responsible Artificial Intelligence Governance Act—TRAIGA—sets new ground rules for how AI can be used in high-stakes decision.
Listen in to Anthony Fisher, Department of Revenue Data Governance and Artificial Intelligence Lead at the State of Colorado, and Jiri Rutner, Homelessness Solutions Enterprise Manager at the City of San Jose, discuss their involvement as founding board members of the GovAI Coalition, and how to approach innovating from within government.
Listen in to Noam Maital and Micheal Pegues discussing Michael's transition from the private to the public sector, and how he is making Aurora IL "America's smartest city."
Listen in to Noam Maital and Dustin Haisler discussing the push for AI legislation across the United States and how to responsibly regulate AI use in government without discouraging innovation.
In this episode, Noam Maital and Mayor of Lake Stevens, Brett Gailey, explore how AI is reshaping public service by improving efficiency, enhancing decision-making, and preserving institutional knowledge, all while emphasizing the importance of data quality, governance, and workforce education.
In this episode of the GovAI Podcast, host Noam Maital speaks with Chris McMasters, the CIO of Corona, California, about the transformative role of AI in government. Chris shares his journey from the private sector to local government, emphasizing the importance of innovation and the challenges of integrating AI into public service. The conversation explores the cultural shifts needed to foster innovation, the complexities of vendor relationships, and the balance between risk management and creativity in adopting new technologies.
In this conversation, Noam Maital interviews Sophia Moore, Chief Innovation and Technology Officer at COTA, about the integration of AI and technology in public transit. They discuss the challenges and opportunities of using AI to enhance customer service, the importance of data governance, and the cultural changes required to upskill the workforce. Sophia shares insights on the future of COTA and how technology will play a crucial role in providing better public transit services in Central Ohio.
In this episode of the GovAI Podcast, Noam Maital speaks with Rachel Stern, founder and CEO of GovTech Venture, about the transformative role of AI in government technology. They discuss Rachel's journey in the GovTech space, the challenges faced by government agencies in adopting new technologies, and the unique dynamics of selling to government entities. The conversation also explores the implications of AI on public services, the importance of understanding product market fit, and the future of AI in government operations.
AI is bifurcating along a new “Wallace Line”: the U.S. champions an open, chaotic swarm of competing models, while China embeds state-aligned mega-platforms into its super-apps. As with past e-commerce and SaaS splits, hybrid regions will choose sides—but history suggests the adaptable, open approach tends to spread farther.
Cities today face a critical challenge: despite rapid technological advancements, many residents feel increasingly disconnected from their local governments.
In late 2023, a story surfaced revealing that OpenAI had created a tool called Whisper, allegedly used to transcribe the entire YouTube library. This raised serious copyright concerns.
What should I eat this week? How should I cut my hair? Where should I take my family on vacation? What’s the best way to fix my shower grout? These are just some of the questions journalist Kashmir Hill handed over to generative AI in an experiment she documented in The New York Times—an attempt to see just how well artificial intelligence could handle everyday decisions.
It’s 2025. Everyone’s buzzing about AI, especially when it comes to public safety or transportation in the public sector.
In the 1980s, a government job in Saudi Arabia wasn’t just common—it was expected. Over 70% of Saudi citizens were employed by the state, anchoring an economy built almost entirely on oil.
This guide provides a structured framework for agencies to comply with the law while enabling centralized, scalable governance, designed to uphold innovation and continuity of service.
In 1930, John Maynard Keynes warned that the world was heading toward a future of “technological unemployment”—a state where machines would render human labor obsolete. He predicted that within a century, advances in technology could reduce the average workweek to 15 hours, as productivity soared and economies became self-sustaining. Spoiler alert: we’re five years away from his hundred-year horizon, and most of us are still burning through 40–60 hour weeks while texting ChatGPT to summarize our meetings.
Budget cuts at federal agencies and a deregulatory push from the Trump administration are changing the dynamics of government oversight. Instead of Washington setting the rules, state and local governments are being asked to step up.
"The kids are not alright," a recent podcast episode from Honestly focusing on gentle parenting, struck a chord with me—not because of its insights into parenting, but because it perfectly captures the unease I feel about our education system in the age of AI.
If you’ve been following federal budget news, it’s no secret that the United States is facing a ballooning deficit.
Artificial Intelligence (AI) is rapidly becoming ubiquitous in our daily lives. Yet, as remarkable as these advancements are, AI scientists themselves admit a disturbing truth: they do not fully understand how AI "thinks."
Government is here to stay, and if we can find ways to introduce technology that fosters efficiency, transparency, and equitable access, we’ll have taken a massive step toward reimagining how society functions at its most fundamental levels.
One of the harshest criticisms of generative AI (GenAI) has been its tendency to fabricate information when it doesn't know the answer - a phenomenon often labeled "hallucination."
In the classic "trolley problem," you're forced to decide: divert a train to save multiple children at the cost of one adult's life, or do nothing and allow the children to die.
AI has the power to revolutionize women’s healthcare.
The Grand Canyon stretches before us as a testament to nature's relentless power—a chasm carved over millions of years by the persistent flow of the Colorado River.
Artificial Intelligence isn't just a buzzword or the latest tech fad; it's becoming an integral part of our everyday lives
Crossing the Chasm of Mistrust: Unraveling Public Perception of AI Imagine standing at the edge of a vast canyon. On one side lies the promise of artificial intelligence — a land of streamlined public services, efficient governance, and unprecedented innovation.
Consider the US healthcare programs, Medicare and Medicaid. Some 65,748,292 million are enrolled in Medicare; and 74,640,222 are enrolled in Medicaid.
It’s a question that’s been asked for years: will AI replace jobs? The answer isn’t as clear as we might hope — yes and no. Recent reports paint a complex picture.
Embracing the AI-Driven Industrial Revolution In 2005, entrepreneur Ray Kurzweil predicted the occurrence of a ‘singularity’ — when machine intelligence surpasses that of humans. He said it would happen in 2045. He now thinks it may be close at hand.
To streamline and speed up the government procurement tango, it takes three. Government (demand); Business (supply); and AI.
AI at a Crossroads: What the Biden-to-Trump administration change could mean for State and Local Agencies The federal approach to AI policy is shifting, and for state and local agencies, it may be time to fasten their seatbelts.
Building AI for the People: A Call to Action “...that government of the people, by the people, for the people shall not perish from the Earth.”
Build It and They Will Come? Not Anymore. For a while, the dominant approach to AI language models has been “Field of Dreams”—build it, and they will come.
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