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Articles by Gregory Dawson
From governance to execution in federal AI policy
Global artificial intelligence spending is forecasted to reach $2.5 trillion in 2026, according to one estimate, marking a 44% increase year-over-year. In 2027, spending is expected to reach $3.3 trillion, reflecting another 32% increase year-over-year. The majority of this money has funded AI infrastructure, followed by AI services and AI software (representing about 54%, 23%, and 18% of spending, respectively, for 2026).
From governance to execution in federal AI policy
Global artificial intelligence (AI) spending is forecasted to reach $2.5 trillion in 2026, according to one estimate, marking a 44% increase year-over-year. In 2027, spending is expected to reach $3.3 trillion, reflecting another 32% increase year-over-year. The majority of this money has funded AI infrastructure, followed by AI services and AI software (representing about 54%, 23%, and 18% of spending, respectively, for 2026).
Where does federal AI spending stand in 2026?
In July 2025, the Trump administration released its blueprint for artificial intelligence—America’s AI Action Plan—with a focus on deregulation and infrastructure investment to achieve “global AI dominance.” The plan represents a notable shift from previous, more cautious AI policies of the Biden era and emphasizes removing regulatory barriers and “ideological” bias in AI.
Where does federal AI spending stand in 2026?
In July 2025, the Trump administration released its blueprint for artificial intelligence (AI)—America’s AI Action Plan—with a focus on deregulation and infrastructure investment to achieve “global AI dominance.” The plan represents a notable shift from previous, more cautious AI policies of the Biden era and emphasizes removing regulatory barriers and “ideological” bias in AI.
Analyzing the passage of state-level AI bills
Artificial intelligence (AI) continues to dominate headlines, spanning chip supremacy and job losses to AI actresses and U.S. national security. These articles demonstrate that AI is top of mind across industries, and the technology is touching virtually every aspect of government and society.
Balancing Digital Transformation and Modernization: Pathways for Public Managers
1 Introduction The public sector continues to invest heavily in digital technologies. Despite significant investment and attention, studies have found that 55% of the public sector's digital projects fail to scale, and that fewer than 20% are considered successful (Fakhoury 2018; Gartner 2021). While the terms digital modernization and digital transformation are often used interchangeably, these terms refer to different strategies, each with distinct goals and methodologies.
Why AI policy thrives in some states and fades in others
Discussions on AI are occurring at all levels of government, including federal, state, and local, as each entity tries to understand, leverage, and protect from AI. In August 2025, we identified the states leading and lagging on AI governance, along with the salience of different issues associated with the technology. In this analysis, we unpack what factors lead to the introduction of bills at the state level and, more importantly, what factors might constrain these efforts.
Why AI policy thrives in some states and fades in others
Discussions on AI are occurring at all levels of government including federal, state, and local as each entity tries to understand, leverage, and protect from AI. In August 2025, we identified the states leading and lagging on AI governance along with the salience of different issues associated with the technology. In this analysis, we unpack what factors lead to the introduction of bills at the state level and, more importantly, what factors might constrain these efforts.
SOC Level 1 - MITRE
ATT&CK® Framework https://attack.mitre.org/ The ATT&CK Framework is a globally accessible knowledge base of adversary tactics and techniques based on real-world observations. Originally focused on Windows, it has since expanded to macOS and Linux. Who it's for: Both red teamers (attackers) and blue teamers (defenders). On the ATT&CK site, you'll find categories that cover the seven-stage Cyber Attack Lifecycle, from reconnaissance through impact.
SOC Level 1 - Diamond Model
Summary The Diamond Model provides analysts with a structured way to study intrusions by breaking them into four connected elements: Adversary, Victim, Capability, and Infrastructure. By examining the relationships between these features, SOC analysts and threat hunters can better attribute attacks, understand adversary behavior, and identify weak points in their operations.
SOC Level 1 - Unified Kill Chain
Summary The Unified Kill Chain gives us a detailed, 18-phase map of how cyberattacks unfold, from the first signs of reconnaissance to the attacker's ultimate objectives. What makes it powerful is its level of detail - it blends elements of the Cyber Kill Chain and MITRE ATT&CK to provide defenders with a holistic view of the entire attack lifecycle. By breaking attacks down into such specific phases, the framework helps defenders see not just what the attacker did, but why and how.
SOC Level 1 - Cyber Kill Chain
In summary: The Cyber Kill Chain is a way of breaking down how cyberattacks usually happen, step by step. It starts with attackers gathering information and ends with them reaching their final goals, like stealing data or causing damage. What makes the framework powerful is that it shows us where we can stop them. Attackers need to move through every stage of the chain to succeed, but as defenders, we only need to block them once to throw off the entire attack.
SOC Level 1 - Pyramid of Pain
Hash Values A hash value is a fixed-length numeric value that uniquely identifies data. It's the result of a hashing algorithm. As SOC analysts, we use hash values to: Gain insight into specific malware samples. Identify malicious or suspicious files. Uniquely reference malicious artifacts. Common tools: VirusTotal, Metadefender Cloud (OPSWAT). There are also different hashes that have been used in the past and present, including but not limited to...
Junior Security Analyst Introduction
Hello! Welcome to my Medium page! My name is Gregory Dawson, and I'm a Security Analyst currently sharpening my skills by completing various TryHackMe rooms and other cybersecurity challenges. I'll be sharing walkthroughs, lessons learned, and practical insights along the way. My goal is not only to track my own progress but also to help others who are learning, studying for certifications, or just curious about how security analysts approach problems.
How different states are approaching AI
It is no surprise that nations are embracing and legislating artificial intelligence. At last count, 54 countries’ governments, ranging from China, India, and the United States to Uganda, Armenia, and Latvia, have published their own national AI plans. These plans have run the gamut from plans that are highly focused on defense-related initiatives (e.g., China) to those who are more focused on societal betterment (e.g., Switzerland).
The evolution of artificial intelligence (AI) spending by the U.S. government
In April 2023, a Stanford study found rapid acceleration in the U.S. federal government spending in 2022. In parallel, the House Appropriations Committee was reported in June 2023 to be focusing on advancing legislation to incorporate artificial intelligence (AI) in an increasing number of programs and third-party reports tracking the progress of this legislation corroborates those findings.
A cluster analysis of national AI strategies
In a series of papers, the authors have explored comparative differences in the design, deployment, and governance of artificial intelligence (AI) technologies among countries. Our previous papers have explored how different countries viewed their adoption of AI, their relative spending on technology versus human capital, and what the United States needs to do to win the AI race. In our most recent paper, we shifted our analysis to focus on the commonalities of different plans across countries.
WEIRD AI: Understanding what nations include in their artificial intelligence plans
In 2021 and 2022, the authors published a series of articles on how different countries are implementing their national artificial intelligence (AI) strategies. In these articles, we examined how different countries view AI and looked at their plans for evidence to support their goals.
NIST’s AI Risk Management Framework plants a flag in the AI debate
The National Institute of Standards & Technology (NIST) issued Version 1.0 of its Artificial Intelligence Risk Management Framework (AI RMF) on January 26, 2023 – a multi-tool for organizations to design and manage trustworthy and responsible artificial intelligence (AI).
Can data portability happen on video-sharing platforms?
Today videos and their watchers are stuck. Large video-sharing companies like YouTube and TikTok seek to ensure that users watch and share videos (as much as possible) on their platforms alone. Technically, videos are collections of various data that together contribute to the viewing experience. The most basic of this data—titles, descriptions, and recordings—is usually shared, but a myriad of other metadata is not often disclosed.
Managing the risks of inevitably biased visual artificial intelligence systems
Scientists have long been developing machines that attempt to imitate the human brain. Just as humans are exposed to systemic injustices, machines learn human-like stereotypes and cultural norms from sociocultural data, acquiring biases and associations in the process. Our research shows that bias is not only reflected in the patterns of language, but also in the image datasets used to train computer vision models.
Understanding artificial intelligence spending by the U.S. federal government
Understanding artificial intelligence spending by the U.S. federal government Brookings Institution | September 22, 2022 In our prior series of papers for Brookings, we explored the rise of national artificial intelligence (AI) strategy documents and sought to make sense of what each country was trying to do and how effectively they were doing it. In our concluding paper, we focused on where the U.S. was lagging behind and proposed options… By Gregory S. Dawson, Kevin C. Desouza, James S.
Understanding artificial intelligence spending by the U.S. federal government
In our prior series of papers for Brookings, we explored the rise of national artificial intelligence (AI) strategy documents and sought to make sense of what each country was trying to do and how effectively they were doing it. In our concluding paper, we focused on where the U.S. was lagging behind and proposed options to remedy the lagging.
Research and development for the public good: Strengthening societal innovation
Investments in research and development (R&D) are important keys to future prosperity. What countries spend on generating new knowledge, products, services, and processes is important for economic development and technology innovation. Yet currently there are a number of barriers to R&D support in the United States. There exist limitations in terms of vision, strategy, and policies that could keep America from achieving vital national goals.
Surviving digital war
The shocking images of innocent civilians streaming out of Ukraine are a vivid reminder of war’s brutality, but also the need for preparation in a world where events can change quickly. Several years ago, I wrote a Brookings Press book entitled Megachange: Economic Disruption, Political Upheaval, and Social Strife in the 21st Century. It argued we live in an era of large-scale transformation and that we should expect surprising developments in the 21st century.
Two ways to improve Senator Klobuchar’s needed antitrust legislation
The Senate Judiciary Committee took a major step forward on January 20th by reporting out Senator Amy Klobuchar’s platform nondiscrimination bill with a bipartisan vote of 16-6. It is now up to Senate Majority Leader Chuck Schumer whether to bring it up for a vote on the Senate floor. The bill and its markup provide an almost-perfect illustration of the overlap of competition, privacy, and content moderation issues raised by attempts to regulate digital companies.
TechTank Podcast Episode 37: Rep. Ro Khanna on democratizing our digital transformation Original
Digital technology has transformed virtually every aspect of human existence. We have online education, telemedicine, remote work, and e-commerce. Many of us spend hours a day online either communicating with other people, reading or watching media, or engaging in digital transactions. Yet there are several problems we must confront as we make this transition to a digital world. Technology has divided us, fueled misinformation and disinformation, and accentuated inequality.
How the U.S. can dominate in the race to national AI supremacy
We have been publishing a series on TechTank called, “Winners and losers in the fulfillment of national artificial intelligence aspirations.” The research has evaluated 44 countries on how well-positioned each country was to achieve its national AI objectives.
How countries are leveraging computing power to achieve their national artificial intelligence strategies
Using finely tuned hardware, a specialized network, and large data storage, supercomputers have long been used for computationally intense projects that require large amounts of data processing. With the rise of artificial intelligence and machine learning, there is an increasing demand for these powerful computers and, as a result, processing power is rapidly increasing. As such, the growth of AI is inextricably linked to the growth in processing power of these high-performing devices.
The people dilemma: How human capital is driving or constraining the achievement of national AI strategies
In the early days of the COVID-19 pandemic (June 2020), LinkedIn released a report showing that the demand for AI skills had cooled down—but by October 2020, demand had already come roaring back. This is not surprising: according to the 2020 RELX Emerging Tech Executive Report, AI adoption soared during the pandemic, and a staggering 68% of companies increased their AI investment during the year. Further, 81% of companies now report using AI technologies, up 33 percentage points since 2018.
Winners and losers in the fulfilment of national artificial intelligence aspirations
The quest for national AI success has electrified the world—at last count, 44 countries have entered the race by creating their own national AI strategic plan. While the inclusion of countries like China, India, and the U.S. are expected, unexpected countries, including Uganda, Armenia, and Latvia, have also drafted national plans in hopes of realizing the promise.
Becoming a digital power: Japan’s path for domestic transformation and international influence
Twitter Join the conversation on Twitter using #DigitalJapan With the growing risk of the fragmentation of the international digital ecosystem, prioritizing digital transformation has never been more important for Japan.
Analyzing artificial intelligence plans in 34 countries
The belief that AI dominance is imperative for economic development, military control, and strategic competitiveness has accelerated AI development initiatives across countries. The release of national strategic plans has been accompanied by billions of dollars in investment as well as concrete policies to attract relevant talent and technology.
How different countries view artificial intelligence
The space race of our time is the quest for domination in artificial intelligence. As a result, countries around the world are investing significant resources to build and mature their AI capabilities. They are also crafting strategic national plans about how and where to invest in AI. Taken together, these plans provide a snapshot of the global state of AI investments and how national governments are thinking about how to best utilize their resources.
Learning from IT Centralization: Who Should Own the Data?
Learning from IT Centralization: Who Should Own the Data? Article Posted October 3, 2018 in Cutter Business Technology Journal The authors focus on a fundamental organizational question: in a medium-to-large organization, should data governance be centralized or decentralized (or, possibly, federated)? There are pros and cons for both centralization and decentralization.
Advice to freshmen from a professor
Gregory Dawson is a professor at Arizona State University. He wrote this list and it originally appeared on the Reddit community r/ASU. Disclaimer: While I am a professor, these views are entirely my own. Disclaimer 2: I teach mostly juniors/seniors/grad students and these things that my thousand plus students have said over time... Factor 1: Go to ASU orientation plus every other orientation you can think of (like Camp Carey). You will get insights and connections that you will get nowhere else.
Learning from public sector experimentation with artificial intelligence | Brookings Institution
Artificial Intelligence is not coming; it’s already here. AI tools are becoming an integral part of organizational decisionmaking in both the public and private sector by evaluating large amounts of data to quickly arrive at conclusions. What’s already here Public agencies are leveraging AI tools to become smarter, more efficient, and more responsive. For instance, the Cincinnati Fire Department is using data analytics to optimize medical emergency responses.
Disrupting work and workers in the age of cognitive computing systems | Brookings Institution
The rise of cognitive computing systems (CCSs) brings a potentially massive shift in the way that work is done, which could lead to an equally massive displacement of the workforce. Advanced automation is already reshaping low-skill and even medium-skill jobs, and tasks once done by so-called ‘knowledge workers’ are now done by machines (think of financial services). Given that up to 47 percent of current jobs are likely to be automated by 2034, this suggests massive labor market upheaval.
Key public policy issues for cognitive computing systems | Brookings Institution
Without a doubt, cognitive computing systems are a hot topic around boardrooms, executive suites, and conference tables at major technology firms, which are investing both financial and human resources to bring these systems to fruition. At the same time, government offices throughout the world are holding similar discussions, and these efforts are starting to come to fruition as well.
Modernizing public sector IT management
Editor's Note: Kevin Desouza will speak at a seminar titled #IdeasToRetire: Information Systems in Public Management, Public Policy, and Governance in Washington, DC on May 9. Over the past 10 weeks we have featured 22 ideas that represent outdated practices or modes of thinking when it comes to public sector information technology (IT) management. In this closing post, we would like to draw out five salient points to move the conversation ahead.
These ideas need to be retired: Technology practices that are stifling public sector success
Editor’s Note: TechTank is launching a new blog series titled Ideas to Retire that identifies outdated practices in public sector IT management and suggests new ideas for improved outcomes. This introduction will be followed by two new essays each week over ten weeks.
Federal agencies behind the curve: IoT and BYOD
The rate at which technology evolves has increased rapidly in past years. The pace of change presents a challenge to all levels of government that must quickly react to nascent technologies. Bring Your Own Device (BYOD) and the Internet of Things (IoT) are two such technological trends that have transformed how business operates in the United States and should change the way that government functions as well.
How state governments are addressing cybersecurity
News about successful hacks of large companies seem to have become common place. In the recent Anthem cyber attack, hackers accessed the names, birth dates, social security numbers, income, health status and many other details for companies’ customers. At present, Anthem does not even know the total number of records breached but estimates it to be “tens of millions”. At present, government has been less affected by security breaches than the private sector.
US State IT Plans: The Conspicuous Absence of Metrics
There is little disagreement about the value of good metrics: metrics provide an intelligent data-driven method for an agency to assess and achieve their goals. When done properly, metrics allow government agencies to set guideposts, establish priorities, and even make decisions on where to invest scarce resources. Additionally, metrics can also serve as a key tool to engage both internal and external stakeholders for the agency.
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