More than a Buzzword: AI as Strategy in the U.S. Army
Paul Funk, II
Throughout my 42-year career in the United States Army, I observed recurring patterns in the leaders, units, and organizations that consistently achieved extraordinary results. While technology, resources, and missions changed over time, the underlying principles of success remained remarkably constant. Trust. Accountability. Adaptability. Investment in people. A commitment to serving something larger than oneself. These are the principles that eventually became known as Funk’s Fundamentals.
Today, the Army stands at another transformational moment. Artificial Intelligence is rapidly becoming one of the most significant technological advances since the introduction of mechanized warfare, aviation, and cyber operations, changing how the Army prepares for, fights, and wins the nation’s wars.
It will influence everything from planning and logistics to training, leader development, and battlefield decisionmaking. Yet as significant as these technological advances may be, my experience suggests that the fundamentals of leadership and organizational excellence remain unchanged.
Technology can accelerate processes, improve decisionmaking, and increase efficiency, but it cannot replace trust, character, judgement, or human relationships. The Army’s greatest advantage has never been its equipment; it has always been its people.
The Department of the Army evaluates transformational change through the DOTMLPF framework: Doctrine, Organization, Training, Materiel, Leadership and Education, Personnel, and Facilities. Examining AI through
this framework reveals both tremendous opportunities and significant challenges. More importantly, it demonstrates that as technology evolves, the human dimensions of leadership become even more important.
AI is already influencing command and control, intelligence analysis, targeting, and logistics. As the Army advances MultiDomain Operations, AI will enable commanders to process information and synchronize effects faster than ever before. However, doctrine must ensure AI remains an enabler rather than a replacement for human judgement.
Mission Command is built on trust, disciplined initiative, and commander’s intent, and AI should strengthen these principles while preserving leader accountability for battlefield decisions. New capabilities require closer collaboration among operators, technologists, cyber professionals, and data specialists. Future formations must be designed to learn and adapt rapidly in increasingly complex environments. This aligns directly with a core principle of Funk’s Fundamentals: strong organizations are built through relationships and trust. Technology can improve performance, but people create culture.
AI has the potential to revolutionize Army training through adaptive learning, advanced simulations, and real-time performance feedback. Soldiers will be able to train in increasingly realistic environments tailored to individual and unit needs. At the same time, leaders must ensure Soldiers understand both the capabilities and limitations of AI systems, and the Army must continue developing critical thinkers who can challenge assumptions, operate under uncertainty, and make sound decisions when technology fails.
Leadership development may be the most important aspect of AI integration. Future leaders will operate in environments where AI continuously provides recommendations and analysis. However, maintaining independent judgement while leveraging technological advantages will remain as crucial as it ever was.
Funk’s Fundamentals emphasize authenticity, accountability, and genuine investment in people, and these inherently human qualities will become more valuable—not less—in an AI-enabled force as great leaders will use AI to inform decisions, rather than make technologically substituted decisions for them. And the greatest leaders of the future will not simply understand artificial intelligence; they will understand human beings.
Increasingly, AI is embedded in Army systems, from predictive maintenance programs to autonomous platforms and advanced command-and-control capabilities – which
improves readiness, reduces costs, and enhances operational effectiveness. However, these same things also introduce new vulnerabilities, including cyber threats and data manipulation. The Army must ensure AI-enabled systems remain secure, reliable, and resilient under combat conditions.
The Army’s future workforce will require greater proficiency in data literacy, cybersecurity, software systems, and humanmachine teaming, and we can anticipate the competition for technical talent will intensify, making recruitment and retention increasingly important.
Yet while technology evolves, the Army’s values remain unchanged as character, courage, commitment, and service cannot be automated. As such, AI should be viewed as a force multiplier that enhances human potential rather than replaces it, and this echoes one of the central themes of Funk’s Fundamentals: investing in people. As AI advances, the Army’s greatest investment must remain the development of soldiers, leaders, and army civilians who embody army values while embracing innovation.
Supporting AI requires modern infrastructure. Data centers, cloud environments, secure networks, simulation facilities, and testing centers are becoming as important as traditional training areas and operational headquarters.
Future Army installations must support both physical and digital readiness, enabling soldiers and leaders to train, experiment, and innovate at the speed required by modern warfare.
Artificial intelligence is now and will continue to influence every aspect of Army operations. Yet despite the speed and power of technological change, one truth remains constant: defense and warfare is ultimately a human endeavor.
So, as AI transforms the Army, the principles of Funk’s Fundamentals become increasingly relevant. Trust, accountability, adaptability, and investment in people will remain the foundation of effective leadership and organizational success.
Machines may process information faster and identify patterns more efficiently, but they cannot inspire commitment, build trust, or create purpose.
As such, the Army that combines the power of artificial intelligence with the enduring strengths of human leadership will not only succeed, but define the next generation of Army excellence. And, while AI may change how the Army fights, people will always determine how it leads and whether it wins.
Chad Pettit
The year was 1994, thirty years removed from the legal end of segregation. Nelson Mandela was elected in South Africa, Pulp Fiction premiered, and Kurt Cobain died. Thirty years earlier, the world was introduced to Pop-Tarts and the first computer mouse prototype.
In Mr. Becker’s keyboarding class, Pop-Tarts weren’t allowed, and the only mouse I ever saw was the one running around under the computer desks.
I was there to master the art of keyboarding because voice-to-text—although invented decades earlier—was still basically science fiction in my 1994 world.
Fast forward to 2024. I stood before a group of staff and faculty at A&M–Central Texas, trying to convince them I was the guy they should hire as their new director of tutoring services. I gave the presentation of my life, and at the end I confidently asked if there were any questions, knowing I could handle any thrown my way.
Then a hand shot up, and my heart dropped. A woman asked, “What’s your plan to address AI and student plagiarism?”
Nothing else. If there was a problem, his only response was a single word: troubleshoot.
When I teach my students grammar and punctuation, I don’t start with the rules; I start with language.
Rather than giving them a list of dos and don’ts, I show them how to empower their writing and apply the mechanics of writing to ensure their voices are heard the way they intend.
I was given the gift of being born into a generation that saw the world of typewriters and chalkboard calculations give way to word processing and pocket calculators. In just a few short years, Mr. Becker’s lessons about focus and troubleshooting gave me an advantage as that new world quickly evolved into the internet age.
“Our job is not to fight what’s coming; it’s to help our students adapt to the new world without losing their unique voices.”
I bumbled my way through an answer at first, as reactionary as the rest of higher education to the rapid introduction and evolution of AI. But then something happened. I remembered who I am, an educator who has seen the world change, for better or worse, time and time again.
What we focus on tends to take over the conversation. If we focus on plagiarism, guess what will increase? Thirty-plus years of standardized testing have taught us a lesson we refuse to learn: Teaching to the test does not increase test scores. See how the negative focus leads to negative results?
Mr. Becker’s class was stressful, but I finished that tedious semester with a new skill set, one that has served me well for 32 years. What was his secret?
He was always calm, and he kept his instructions simple. We were to focus only on the keys in the program.
While so many around me panicked and failed to adapt, my honed troubleshooting skills with dot-matrix printers and endless tangles of VHS cables made the transition to HTML and connectivity checks seamless.
Truth be told, I don’t recall ever learning touchscreen technology or using the cloud. One day, I was just using those things as second nature, much as I see writing as an intimate process that connects writers and readers.
The “I’m not good with technology” folks are the ones who refused to accept that the world around them was evolving.
Rather than adapt, they fought the rising tide. The same thing is happening with AI. Those who are resistant to or completely opposed to it want to figure out how to stop it, but that boat has already left the dock.
Our job is not to fight what’s coming; it’s to help our students adapt to the new world without losing their unique voices as writing formulas and templates threaten to make us all sound the same.
Our task is simple: keep our fingers on the keys and focus on what matters.
Where Are We Heading? Artificial Intelligence and Central Texas
Abdul B. Subhani, Founder | Technologist | Defense Innovator
Artificial Intelligence is now one of those topics that seems to swing between excitement and fear depending on who is talking. Some people see enormous opportunity. Others see disruption coming faster than communities can absorb it. Most people are somewhere in the middle, trying to understand what is real, what is exaggerated, and what all of this could mean for their work, families, and future.
In Central Texas, this conversation is no longer theoretical. AI is already influencing how businesses operate, how schools think about readiness, how healthcare systems function, how military operations evolve, and how communities think about economic growth and infrastructure.
Whether it is intentional or not, the truth is that many people are already interacting with AI every day without even realizing it. Phones predict our words. Navigation apps reroute traffic in real time. Banks monitor suspicious activity. Streaming platforms study viewing habits and recommend content. Technology is already woven into ordinary life.
What feels different now is the speed. Institutions that normally adapt over decades are being forced to think in much shorter timelines. School systems are trying to prepare students for careers that may look dramatically different by the time current elementary students graduate. Businesses are determining which tasks should be automated and which still depend heavily on human judgement, relationships, and trust.
VOICES FROM CAMPUS
In recent conversations with higher education leaders, we discussed the growing importance of clear communication and implementation guardrails for organizations of every size. Right now, expectations around AI vary dramatically.
For example, in one company, an employee may be recognized for finding ways to improve efficiency through AI. In another, that same employee could face disciplinary action for using it at all. Many employees are operating in uncertainty because organizational policies and leadership philosophies have not caught up with the pace of technological change, and that uncertainty creates risk.
During this period of rapid AI evolution, organizations need to determine how these tools should and should not be used. Leaders also need an honest understanding of how employees are already interacting with AI in their daily work because, in many cases, adoption is happening quietly whether organizations acknowledge it or not.
Employees need clear expectations, practical guidance, training, and decision-making frameworks that align with company values, security concerns, and operational goals. Those guardrails matter.
Central Texas sits in a particularly important position because our region connects so many sectors at once: military communities, public education systems, colleges and universities, healthcare networks, manufacturing, logistics, cybersecurity, and technology.
And while Austin often receives most of the national attention, none of our communities are exempt from navigating the same larger challenges: how to modernize and remain economically competitive without losing the human side of community in the process.
And it is, perhaps ironically, the humans asking the big questions: Both new graduates and seasoned employees worry about job displacement. Parents and teachers wonder whether students will become even more technologydependent before really learning how to think independently.
Others question whether constant automation eventually weakens creativity, communication, or critical thinking. These concerns are more than resistance to progress. They reflect uncertainty about how quickly society is changing and who benefits most from those changes.
What concerns me more than AI itself is the possibility that communities respond passively instead of thoughtfully. Technology has always reshaped society. The internet changed communication and access to information. Smartphones changed human behavior in ways few people fully anticipated.
And those who have been grappling with the issues created by those technologies would all but certainly urge forethought and caution. Which is why leadership becomes both more complicated and more crucial because decisions often have to be made before people feel fully prepared.
For years, many systems measured success primarily through degrees, certifications, standardized assessments, or technical expertise alone. Those things still matter, but employers increasingly value adaptability, communication, problem solving, collaboration, and the ability to continue learning.
Which ironically, and perhaps fortunately, it is feasible that AI could simultaneously increase the value of distinctly human skills. For example, students still need strong academic foundations, but they also need opportunities to practice judgement, creativity, communication, and resilience.
Adults already in the workforce need support as well. Some workers are excited about AI. Others feel overwhelmed or left behind. Most are still trying to determine what these changes actually mean for their industries and long-term stability.
AI has the potential to improve healthcare access, strengthen cybersecurity, accelerate research, support military readiness, and create efficiencies across industries. But it also has inherent risks. Misinformation can spread faster. Inequality can widen if access and training remain uneven. Overreliance on automation can weaken human judgement if people stop questioning what technology produces.
The future of AI in Central Texas will depend less on the technology itself and more on the decisions surrounding it. Communities approaching these changes thoughtfully will likely adapt far better than those that either ignore the shift or blindly chase every new trend without considering long term consequences.
Finally, it is crucial to note that Central Texas has strengths that matter in this moment. This region understands service, resilience, entrepreneurship, and adaptation. We do not need to become Silicon Valley to participate meaningfully in the future of AI.
But we do need to stay engaged, ask difficult questions, establish thoughtful guardrails, and remember that technology decisions eventually land somewhere real: in workplaces, schools, homes, and communities trying to adapt to rapid change. The future is already taking shape around us. The question is whether we are willing to help shape it intentionally.
Still, Again, and Forever: Our Libraries and AI
Bridgit McCafferty
As a millennial of a certain age, and a librarian at that, AI always makes me think of a lesson from Harry Potter: don’t trust anything that can think for itself if you don’t know where it keeps its brain.
It’s a given that AI will change the way we work and the way we live, but I think we will still need thoughtful leaders and professionals in the future to decide when we can and cannot, or should and should not, trust AI.
We’ll also need people that know how to protect populations from the worst risks we face in implementing it. There will be questions about how good AI needs to be to replace human judgement and whether AI should be used to solve a problem without any intervention from a real person. These questions will need to be answered by individuals in our militaries, educational systems, Fortune 500 companies, and a host of other contexts. The people in these roles will be so important because they are the ones who will ensure that we don’t trust too much, too soon.
The curious thing about AI is that it is a multiplier. It does not make somebody better at programming, medicine, or writing than they were to start with. A good writer will look at what AI has written and see where it doesn’t make sense, where the phrasing is off, or where it needs to be fixed. A savvy programmer will know the right prompt to get the exact code they need. A well-trained doctor will understand what to call the symptoms and how to relay the diagnosis to the patient. Somebody less capable will struggle to write meaningful directions that meet exactly the task at hand.
Moreover, if a person doesn’t know what they are doing from the start, they won’t spot when the mark is missed. This is the catch: if someone knows what they’re doing, they can guide it to do two, three, or four times the work they could before. But, if they don’t, they might produce more work, but without the wisdom to vet it. They must trust it has done what it should. Even though sometimes, it makes the silliest mistakes.
This is true in the library, too. It goes without saying, excellent researchers understand how to do research—AI makes them fly! It improves searching accuracy. A&M-Central Texas already has it running in some places in our databases. It can easily identify similar articles across resources, a task we’ve been trying to achieve through tagging and metadata for several decades. An excellent researcher knows when those articles are relevant and when they aren’t. AI can generate a reference list and citations in any style. Sometimes they are very good citations and sometimes they are very bad. Experienced researchers can tell the difference.
Some people are even using AI to find all their sources, sort them, and document them. One drawback of this approach is that AI is known to fabricate articles, especially if the prompt is written in a way that makes clear the researcher wants a particular point of view. AI will serve only what
someone wants to hear, and not the full academic discourse, if that’s what is asked of it. This doesn’t trip up proficient researchers because they know they cannot cite a source if they haven’t found and read it—doing that is called academic dishonesty. They also know they need to understand the whole debate, not just the part they agree with.
In the library, we see people every day that this does trip up: people who don’t plan to find or read the real sources and don’t understand why both sides in the debate are needed. They take it on trust that the AI is not leading them astray, but it cannot be trusted to do that job yet.
There’s a second problem when we can’t see where something keeps its brain. For AI, I wonder where all that data we are putting in it goes when we are done with it. Every query, every leisurely hour spent searching for a new pair of pants or a better kayak, every questionable symptom, goes somewhere.
Librarians are known as the people who answer questions, but we’re also avid defenders of the privacy of information. That’s at the heart of our professional code of ethics and our values. We are deeply committed to protecting the rights of our users to seek out information, even unflattering or embarrassing information, without fear of reprisal.
This doesn’t only mean information that’s mildly personal or unfortunate—a questionable mole or the forgotten name of a founding father. This also means information that could cause someone problems in their everyday life: how to kick a gambling addiction or a drug habit, how to escape an abusive marriage, or how to get out of crushing debt.
Librarians are trained, from the very first class, to approach every query with care and without judgement. We are taught to find accurate information and then, to forget. If I see a patron in the grocery store, I won’t say anything about that question they asked me last week. I wonder how long AI remembers and who has access to the questions users were too embarrassed to ask anyone else.
Still, AI is here. Its impact is just off in the distance, shaping the future in ways we can’t predict. It won’t be ignored.
There may be a day where the information that AI produces is so realistic that even an excellent researcher will not be able to tell the difference between an actual article and one written by AI using wholly fabricated data.
In that world, libraries will be more important than ever. In a sense, this has always been the promise of a library, because a library is an idea, one that pre-dates the internet, the printing press, the first universities, and the rise and fall of the Roman Empire. A place where the resources are vetted and there are people around to teach you how to use them. A place that molds excellent researchers. A place where information can be trusted still and again, and forever.
A Former Reporter’s Reckoning with Artificial Intelligence
The Tool That Worries Me—And Why I Teach It
Steve Hanik
I spent years chasing stories. I covered city councils and crime scenes, interviewed CEOs and grieving families, and filed copy on deadline using ink-stained notebooks, tape recorders, film and eventually video. The craft of journalism, I believed then and still believe now, is fundamentally human — an act of witness, of translation, of trust and truth.
When artificial intelligence began reshaping the media landscape I once inhabited and then crept into the classrooms where I now teach, I had to confront something uncomfortable: the tool that threatens so much of what I valued may also be the most significant shift in communication of a generation.
I am not a technophobe. I sat in smoke-filled newsrooms debating whether stories were worthy of thirty seconds or a series. I watched classified ads — the economic engine of local newspapers — collapse almost overnight when Craigslist arrived.
I watched television embrace mobile phones for capturing, editing, and instantly broadcasting news. I understand disruption. What concerns me about AI in media is not its existence but its application without accountability, and the alarming speed of adoption before ethical understanding can catch up.
VOICES FROM CAMPUS & COMMUNITY
The problems in journalism are real and pressing. AIgenerated content has already been published under mastheads of once-credible outlets — sometimes without disclosure, sometimes riddled with errors that no editor caught because no editor read it. Magazines faced significant backlash after publishing AI-generated articles under fake author profiles. Broadcasters quietly corrected dozens of AI-written financial stories.
These are not edge cases; they are symptoms of an industry under financial pressure reaching for a cheaper pen. When a revenue-driven algorithm replaces a reporter, what gets lost is not just a job. What disappears is the source relationship, the instinct to ask the follow-up question, the willingness to sit in a hard plastic chair for four hours because the story might be in the room. You cannot automate accountability journalism.
There is also the hallucination problem — a polite word for confident fabrication. AI language models generate plausible-sounding text, not verified truth. They have invented court cases, misquoted real people, and cited sources that do not exist. In a profession whose entire value proposition rests on accuracy, the introduction of a tool that invents facts with fluid prose and zero shame is not merely inconvenient. It is existential. The public’s trust in media was already fragile before AI; every synthetic news story and algorithmically generated local “report” widens the crack further.
The first draft is no longer the hardest part. Students who once labored over a blank page now generate one in seconds, then face a different challenge entirely: critical editing, voice, judgement. In some ways, AI has made the evaluative skill — knowing what is good, what is wrong, what is missing — more important than ever. The machine can produce competent prose. It takes a human to recognize that competent prose is not enough.
The deeper risk is not laziness. It is that students will outsource their thinking before they have fully developed it. Writing is not just communication — it is cognition. The act of wrestling an idea into a sentence forces clarity of thought in a way that prompting an AI and accepting its output simply does not. If students use AI to skip that struggle, they may arrive in the workforce fluent in a tool they do not understand and deficient in the judgement it cannot replicate.
“The deeper risk is not laziness. It is that students will outsource their thinking before they have fully developed it.”
My approach has been to reframe the creative process rather than police the technology. I ask students to show their thinking, not just their output, relate it to their real-world career or goals. I caution them to treat AI as a collaborator, not a ghostwriter. I point out where AI-generated content fails — where it sounds credible but is hollow, where it mistakes confidence for correctness.
And yet — here is where my former self and my current self part ways — I cannot tell my students to simply refuse this technology. That would be, to use a phrase they might appreciate, a spectacularly bad take.
I teach business communications at the university level. My students are preparing to enter organizations where AI writing tools are already embedded in the workflow — drafting emails, summarizing reports, generating proposals. Pretending otherwise would be like teaching them to write memos on a typewriter because keyboards felt like cheating. My job is not to preserve the tools of my generation. My job is to prepare them for theirs.
What I have observed, though, is that AI is changing the creative process in ways that deserve serious attention.
What I carry from my reporting days into this moment is a stubborn belief in the primacy of the human source. The best stories I ever wrote came from listening to someone who trusted me enough to tell the truth. The best communication my students will ever do will require the same: genuine understanding of another person’s need, context, or fear. AI can approximate that. It cannot replace it.
I am not optimistic about what AI will do to journalism in the short term. The economics favor the machines, and the accountability structures are nowhere near ready. But I remain cautiously hopeful about what it can do in the classroom — if we ask the hard questions, and insist that students understand not just how to use these tools, but why that is not the same as knowing how to think.
AI in Past and Present Tense
Allen Redmon
VOICES FROM CAMPUS & COMMUNITY
When I was a graduate student at Purdue University, I had the pleasure of working in the writing center. The center was in something of its adolescence in terms of developing the Purdue OWL (online writing lab). We were in the very early days of online tutoring. We still conducted most of our work with students around a physical desk in an actual room.
Even in those days, we did have an established way to connect to the masses beyond those walls: the “Grammar Hotline.” Our website listed a number concerned citizens around the world could call to have their pressing grammar questions answered. I was one of the lucky ones tasked during my first year with answering the hotline.
I was always surprised how often the phone rang. I was just as often surprised by the panic, angst, desperation, and condemnation on the other end of the line. People needed their grammar questions answered and quick. They needed to know who was right.
I must admit that I was not the best person for the job. I was eager to put my developing linguistic training to use. I wanted to explain the range of choices a speaker or writer has each time they look to express an idea. I answered the phone to talk about concepts like language variation and code-switching. The folks calling the “Grammar Hotline” just wanted the answer.
The conversations were typically short. Folks would ask their question. I would say, “Well, it depends.” They would say, “Yeah, but I’m right, aren’t I?” I would concede they might be technically right even if things like double negatives or why words like “got” or “fixin’” might have a place in our language.
We would have some discussion, but I suspect I had exactly zero converts. The folks on the other end of the line didn’t want to talk about grammars. They wanted to talk grammar, and they wanted to know their memories from grade school were correct.
Over the last thirty years I have come to see how educators across all levels were partly to blame for this need for rightness. Our multiple-choice tests asked students to find the most appropriate answer when we could have developed tests that explored the suitability of several possibilities.
Our feedback marked errors far more often than it marked moments of authentic expression. In so doing, we eliminated choices. We standardized language use. We reinforced a very narrow notion of correctness.
We shouldn’t be surprised, then, when people today treat assistive and generative AIs as generators of right answers. People have been trained to look for right answers. AIs give them, or at least something like them. Assistive AIs give us little squiggly lines that let us know when our phrasing misses some standard. Generative AIs answer prompts with all the insights of the World Wide Web behind them. Both technologies give us answers that respond to one kind of authority, the one given to the creation of successful products.
Ironically, neither education nor AI means to generate products. Both claim to invite learners or users into a process of discovery and creation.
Education wants to help students think and reason, to implement and apply. It wants to prepare students to make more informed, effective, and meaningful decisions. Education achieves this aim by helping students see nuance and complexity and emboldening them to make choices even if they are incomplete in some way.
AIs claim to be after something similar. They intend to simulate the kinds of human thinking and decisionmaking education inspires. When correctly prompted, they coalesce a vast range of information. They weigh competing viewpoints or reveal rival priorities. They help users see how to launch systematic responses to an issue or topic. They help users identify which skills are needed or which rules might be considered. They mean to help users make choices.
An over-emphasis on products has minimized this aspect of AI just as it has diminished this aspect of education. We focus on end-result rather than the process each can support. To accomplish the aim of AI, users must ultimately use the information they prompt to help them make choices rather than to retrieve products (ready-made answers). To achieve the ends of education, students must recover the opportunity to enter a process each class provides them.
To return to my opening story, we might all become the person answering the Grammar Hotline looking for ways to see grammars (the presence of multiple, equally valid ways of talking or writing) rather than grammar (the belief in one right answer). Despite the appearance of something else, we are all living in times where our questions and our ability to tolerate multiple answers is more important than ever. Education and AI can each help us through this moment.
The Human Side of AI
How Trideum Is Transforming Work Without Losing Its Values
Artificial intelligence (AI) is transforming nearly every aspect of the modern workplace. While it may still seem futuristic or abstract to some, particularly outside the tech sector, the reality within Trideum Corporation is very different. Here, AI is practical, grounded, and deeply human—not a trend or a replacement for people, but a set of tools that help teams work smarter, solve problems faster, and stay focused on missions that matter most.
AI on the Front Lines of Our Programs
Across Trideum’s portfolio, AI is accelerating how teams process information, identify patterns, and reduce time
spent on manual tasks. Work that once required extended data review can now be streamlined, allowing engineers, analysts, and operators to focus on decision-making, refinement, and innovation.
One of the clearest examples of this impact is in Trideum’s modeling and simulation work, particularly in long-standing support of the Operational Evaluation Command (OEC) at Fort Hood. Evaluating Army systems requires analyzing massive volumes of performance data, scenario outcomes, sensor inputs, and user feedback—traditionally a timeintensive process.
Ron McNamara
VOICES FROM CAMPUS
AI-assisted tools now surface insights quickly, shifting effort from sorting data to interpreting results and improving outcomes. These tools help assess simulation outputs, flag irregularities, and validate complex scenarios with greater speed and precision. Instead of spending days parsing raw data, analysts can move directly to refining test conditions and advising decision-makers. The result is testing that is more agile, more informed, and more mission ready.
What has not changed is the human judgement behind the mission. AI accelerates insight, but Trideum’s experts still guide analysis, interpret results, and shape recommendations. AI simply gives them more time to do what they do best.
AI also plays a growing role in Trideum’s human-centered engineering efforts, including work with unmanned aircraft system (UAS) interface controls. Designing interfaces for operators in high-stress environments requires a deep understanding of human performance, cognitive load, and usability.
AI adds analytical power without replacing human insight. By examining operator interaction patterns, it identifies usability issues earlier—highlighting hesitation, confusion, and potential design friction during prototype evaluation. These insights allow engineers to refine interfaces more quickly and effectively.
But again, AI does not dictate solutions. Trideum’s engineers remain the creative and technical drivers, interpreting observations and making decisions rooted in user needs and mission context. The result is betterdesigned systems, fewer redesign cycles, and equipment operators can trust.
Enhancing Internal Operations Without Losing the Human Touch
AI is also improving internal operations by reducing time spent on repetitive tasks and strengthening communication across teams. AI-assisted tools support document analysis, help locate information across large collections of policies and contracts, and generate initial drafts of proposals and summaries. Scheduling tools coordinate meetings, resources, and timelines more efficiently.
These tools do not replace the relationships or collaborative culture that define Trideum—they reinforce them. When administrative tasks are reduced, employees have more time to engage with customers, mentor colleagues, and focus on complex challenges. Technology enables the culture rather than competing with it.
Reinforcing Cybersecurity Through Intelligent Defense
As digital threats evolve, Trideum is increasingly using AI to strengthen cybersecurity. AI-driven monitoring tools detect unusual patterns in real time, analyzing large volumes of data and surfacing potential vulnerabilities or intrusions quickly.
AI also supports continuous compliance by automating audit processes and identifying system misconfigurations before they become risks. While cybersecurity teams remain central to all protective efforts, AI adds speed, depth, and predictive insight.
These tools must be used responsibly. Trideum maintains strong human oversight, protects sensitive information, and ensures that all AI-generated insights are reviewed by experienced professionals. Trust, accuracy, and accountability remain essential.
A Workforce-Centered Approach to AI
Trideum’s approach to AI is not about automation for its own sake. It is grounded in a simple principle: AI should enable people, not replace them.
To support that philosophy, the company emphasizes training, awareness, and responsible adoption. Employees are encouraged to explore AI tools, identify opportunities for improvement, and apply them within clear dataprotection guidelines.
As AI becomes more integrated into the workplace, technical expertise alone will not define success. Critical thinking, adaptability, communication, and ethical judgement remain essential. These human capabilities continue to drive mission outcomes.
The result is a workforce that sees AI as a teammate, not a threat. People remain the innovators and decision-makers. AI expands their capacity.
Looking Ahead
As AI continues to evolve, Trideum is committed to staying at the forefront—while remaining aligned with its values, mission, and the trust placed in it by its partners.
AI is strengthening capabilities, enhancing systems, and supporting people across program execution, internal operations, and cybersecurity. It enables faster, smarter, and more reliable outcomes—delivered with the same thoughtful, mission-focused approach that has guided Trideum from the beginning.
What’s on the Menu:
The Professor, The Nurse, and AI Bob
Dawn Riess
I have spent twenty-six years in healthcare and fourteen years teaching nursing. Over the course of my career, I’ve written peer-reviewed articles, earned professional certifications in artificial intelligence, and taken to the stage to speak to expert panels about the future of automation. I understand the algorithms, data structures, and massive societal shifts this technology represents.
But when I close my laptop at the end of a long day of teaching, my relationship with AI looks entirely different. I’m not using it to outline lectures or replace my knowledge or experience. Instead, I’m using it to solve a more immediate, high-stakes crisis: figuring out how to make dinner using the random, questionable assortment of ingredients remaining in my refrigerator.
There is a huge difference between understanding the technical mechanics of AI and understanding its practical influence on a Tuesday night. True mastery of this technology doesn’t belong exclusively to computer scientists; it belongs to anyone who treats it as a collaborative partner in the chaotic flow of daily life. For me, AI is the ultimate creative sidekick.
In professional settings, the presumption is that AI should be strictly used for high-level, technical automation. But real magic happens in informal, unscripted moments when using it as a sounding board for imagination.
Imagine sitting down to design an interactive group exercise or brainstorm a new project. The mental friction of starting from scratch can be downright paralyzing. That’s why I talk to Bob, my AI chatbot.
When I am completely stuck, I ask Bob to generate 10 or 20 unique options framing a concept. I don’t expect all of them to be brilliant; in fact, I usually discard half of them because they are delightfully unhinged. But Bob provides the raw clay so that I can sculpt it into something that actually works.
This collaborative process also shows up in the most wonderful non-work related ways, usually involving groceries. After an exhausting day of decision-making, the absolute last thing I want to do is plan a meal. By entering, let’s say, a few forgotten vegetables, a half-used block of cheese, and some chicken approaching its expiration date, into the prompt box, I offloaded that cognitive burden.
Bob doesn’t have a palate, but he is excellent at pattern recognition. He quickly provides a cohesive recipe blueprint, effectively turning the mundane into the miraculous. He isn’t dictating what I must eat; he’s just offering a spark to get me started so I don’t end up eating cereal for dinner again.
Beyond creative brainstorming, I’ve found immense value in using AI as a supportive logistics coordinator for community work. Humans are deeply communal creatures but building and maintaining that connection requires a daunting amount of behind-the-scenes coordination.
Consider the administrative scaffolding that goes into organizing a minute-by-minute timeline for a church hospitality meeting or structuring a group gathering. The true value of these events lies in the warmth, empathy, and welcoming spirit that we bring to the room. However, mapping out logistical checklists and flow charts from scratch can render the human planner quite exhausted.
When I use AI to do things like this, I am intentionally clearing off my plate, allowing technology to absorb the weight of the organizational minutiae and preserve my mental bandwidth for what truly matters: being present, engaged, and fostering real human connection.
When I use AI to proofread and refine text, I treat it as an objective, non-judgemental sounding board. Bob doesn’t approach a draft to critique my life choices or question my grammar; he simply polishes the mirror, so my original intent shines through clearly. He catches my repetitive phrasing, smooths out awkward transitions, and ensures the syntax holds strong.
The goal is never to strip away my unique voice or receive a lecture on style, but to ensure that expertise and personal touch are presented with the utmost clarity.
A lot of people are knowledgeable about prompt engineering, or have read technical documentation, and speak on panels about the future of machine learning. But the true utility of AI lives in the relationship between the user and the tool. Computers possess vast computational capacity, infinite patience, and instant access to linguistic patterns, but they lack lived experience. A machine has never felt the fulfillment of a successful community event, the bone-deep exhaustion of a long shift, or the joy of a shared meal.
AI provides: Efficiency, speed, and organization. Humans provide: The context, the ethical compass, the empathy, and the soul. And when we leverage AI to brainstorm exercises, invent recipes, plan events, or polish our writing, we aren’t outsourcing our lives to a machine. We are simply using a tool to clear away the busy work and spark our imagination. It takes both the algorithm and the architect to build a more efficient, creative daily life, one prompt (and one leftover casserole) at a time.
Texas in an AI Economy: Interpreting a Shifting Landscape
Ray Perryman
Everywhere these days, there’s a new headline related to Artificial Intelligence (AI) and its implications. Billions of dollars in data center construction are generating economic benefits in communities across the country, initial public offerings for major players are garnering headlines, and chipmaker Nvidia’s market valuation is topping $5 trillion. AI is having multifaceted and massive effects, and there’s no end in sight.
Texas is emerging as a primary center for the data centers that enable AI. Approximately one-fourth of all new activity is in the state, and it is rapidly displacing Virginia as the epicenter of this emerging phenomenon. Some 140 projects are at various stages of development, and a significant proportion of total national investment is occurring here.
Construction of these often multibillion-dollar campuses provides a substantial, though transitory increase in business activity. Once in operation, facilities provide well-paying jobs and opportunities for other local firms. Multiplier effects ripple through the economy.
In fact, one of the most important aspects of AI is as a source of economic development as the necessary infrastructure is put in place. Communities across the nation are working to secure quality corporate locations and expansions, with data centers to support AI and evolving technologies by far the most prevalent at present.
Location options for data centers are particularly widespread. Primary factors in location decisions typically include energy availability, flat available land, adequate water, and fiber connectivity.
Unlike many other types of corporate locations, data centers require a relatively small workforce once operational and, therefore, are not substantially constrained by population size or training availability. They also do not require proximity to large population centers or markets.
From the perspective of smaller communities, data centers represent a unique opportunity for substantial additions to the tax base without extensive infrastructure needs such as schools, roads, or housing.
Moreover, due to their relatively small employment needs compared to other types of manufacturing facilities, data centers are one of the most viable options for expanding business activity and the tax base in smaller communities and rural areas.
Business activity generates tax receipts. For example, retail sales and hotel occupancy increase as a result of data center projects. A portion of the retail sales would be taxable, benefiting the State and local taxing entities. Economic activity also affects property tax values.
Higher incomes increase housing demand, leading to higher taxable values as well as the need for additional houses. Increased retail sales and personal income also enhances the need for commercial space such as restaurants, retail outlets, and personal service facilities, further increasing the tax base.
These higher property values increase taxes to counties, cities, school districts, and other local taxing entities. These indirect taxes lead to significant incremental receipts to the State and local governmental entities. Even if competitive tax abatements are offered, data centers typically generate
substantially more tax revenue than open land, particularly land which qualifies for agriculture or timber exemptions. In some rural areas, the tax base becomes several times its prior levels, thus enhancing the capacity to provide much needed public services for local residents.
Clearly, the more profoundly impactful aspect of AI over time once the basic infrastructure is in place will be how it is implemented and the resulting level of increase in productivity. Without a doubt, AI will touch a large proportion of occupations, but it remains to be seen how changes in the job market will play out.
For some types of jobs, AI can enhance productivity but is unlikely to eliminate significant numbers of workers. However, in other cases, technology can more easily replace human workers.
A key question driving future patterns is how common AI usage is and becomes in the business world. While many people love its amazing capabilities on a personal level, huge investments in technology only make economic sense if they are used in commercial settings and create sustainable value. The more AI can enhance productivity and efficiency, the more it will grow the economy while generating profits to those enabling its usage.
According to survey data from the US Census Bureau, overall AI usage by businesses has been trending between 17% and 20% over the past six months, and a slightly higher percentage of companies expect to use it soon. Larger firms (those with at least 250 employees) are far more likely to use AI (37%), and deployment is growing somewhat faster than in smaller companies.
Some 32% of those with 100-249 workers indicated usage, with the frequency dropping to below 20% for smaller enterprises. Use rates also vary by industry, with the highest being about 40% in Information and 34% in Finance and Insurance. By contrast, businesses in the Retail Trade sector reported current and expected usage of only about 14%.
AI is changing the economic landscape, both as a tool to enhance productivity and as a source of economic development. There are certainly concerns to be dealt with, such as shifts in the workplace and challenges in generating the necessary electric power and, at times, providing the necessary water for the data center operations. However, the proverbial genie is clearly out of the bottle, and AI will continue to impact and transform the Texas economy.
You can tell a lot about a person by looking at their workspace. If it’s neat and tidy, they are probably the type-A, organized colleague who plans the potlucks and is sure to remind you about when your timecard is due.
My co-anchor has a light pink and green themed workspace with a fuzzy house rug that is inviting and cheerful. One of our producers has lots of shark items, an obsession that we regretfully inquired about one day. Another producer decorates for every holiday.
A few cubicles down, you’ll find a space that conveys a little more ADHD than type-A. There’s no welcome mat but more framed family photos than most people’s living room. That’s my desk.
Among the Diet Coke bottles, Post-it notes, and a large desk calendar scribbled with a million to-dos is a wooden sign in the shape of a word bubble. It reads “Just Nod & Smile.” I’m pretty sure it was an impulse buy from Cracker Barrel. I glance at it a few times each day as I get ready for the five-hour-long Texas Today newscast at KCEN-TV.
The movie “Anchorman” perfectly parodies the perception that, at our worst, TV anchors are just news readers suggesting that whatever is in the prompter, we will say – a tone-deaf robot that nods and smiles no matter what the story is. I have witnessed some anchor blunders and mispronunciations that could make a compelling case justifying this perception. And I’ve been guilty a time or two.
At our best though, a news anchor isn’t a talking head, but a journalist who thoughtfully writes and delivers stories about the community, connects with viewers as a trusted source and remains relatable – a person you can call or email your feedback and story ideas. Someone who will listen and actually cares. They are a last line of defense for justice that offers a voice and a platform for issues that impact real people. For 24 years, that’s the kind of journalist I strive to be.
The news industry has undergone multiple transformative periods in that time. Thankfully the beta tape and my early2000s hairdo are things of the past. But in this moment, journalists are faced with what could be its most rapidly changing and possibly damaging season due to the impact of AI.
From my view in the newsroom, it has the power to change the way we work, how news is consumed and who is doing the work. It does not have the power to change what journalism is.
The rise of social media and influencers has already changed traditional broadcast viewing habits.
My prediction is AI will contribute greatly to continued corporate cuts to staffing and increased efficiency across all departments. From automated news production to the craft’s evolution, there’s no doubt AI will be the throughline.
Still, as a lifelong working journalist, I embrace AI for practical reasons.
We already utilize software that allows reporters to input video footage which rapidly spits out a transcript with time codes. This upgraded process results in a gift of extra time for production and newsgathering.
As good as that is, we still need to ask what we might be losing by using that one AI tool. Is it the subtle nuance of a person’s facial expression when they deliver a powerful sound bite?
Obviously, an AI generated transcript can’t pick up on that, but a human can.
Recently, I reported on a multipart series on AI and sought out the top experts in the field at a discussion panel at A&M-Central Texas. Using AI tools in that series, I created an AI avatar of myself to deliver a line in the story.
The first attempt was robotic and phony. After several attempts, I created a pretty realistic sounding and looking avatar. It could one day, with my consent, be programmed to deliver the entire newscast.
Could it deliver a witty line as fast as the real me? No. At least not yet. But then again, I haven’t asked it to.
Could it fill an endless news cycle that includes social media reels and streaming newscasts? Quite possibly, yes. Is it capable of picking up the slack that the real person can’t keep up with as a living, breathing human that takes lunch breaks and likes to go on vacation too? This could be the future with ethical guardrails and, most importantly, consent.
The wooden trinket from Cracker Barrel isn’t just the desk clutter of a self-deprecating sense of humor. It’s a reminder to take what I do seriously but enjoy moments of levity, even if it’s thanks to a misspoken word. Those are sometimes the funniest on-air “live” moments that I can remember. By the way, “penitentiary” and “dispensary” are two words that I can’t say for the life of me on live television, but they get a hearty chuckle out of my coanchor and probably the viewers, whenever I try. I can’t help it I’m human.
For now, I put on my makeup, check my scripts and head out to the anchor desk to nod, smile, and deliver some humanity to a world where that’s becoming increasingly rare.
For the Record: Balancing Credibility and AI Technology in the Newsroom
Jacob Brooks
If I had written this back in my first year at Angelo State University in West Texas and admitted to having used AI, people wouldn’t have understood what I was talking about.
Artificial intelligence was around in those days, but it was nothing like the AI we know today. Thirty years later, here we are: using AI for a first, fourth, or final draft, and it’s become commonplace.
Admittedly, AI is very good at writing. Still, a lot of writers I know don’t agree with me. And the contrarians do have a point. And I hear them. “AI writing sucks.” “It makes mistakes.” “It lacks a soul.” “It steals from others.”
For the record, I did not use AI to write this. Not sure if we’ll keep having to say that in the future, but we’ll see.
Really, the writing that AI can do is informational and vast. I’m limited to the words I’ve learned over the years, and I still look up the definition when I see a word I don’t recognize. It has a seemingly unlimited vocabulary – as if it might know every word in every language.
In the Killeen Daily Herald Newsroom, we have found AI tools to be very useful, especially for saving time and increasing our productivity.
We use AI to write up the daily police blotter reports where dozens of thefts, burglaries and other crimes show up every day. Without AI, it takes a reporter about an hour to write up the blotter which involves downloading multiple documents and rewriting them into a uniform style. With AI, they can do it in 15 or 20 minutes.
We also use AI to rewrite boring, dry press releases into Associated Press-style news stories. It does a very good job at that, and it follows instructions when I tell it to focus on certain things or lead off a certain way.
Several reporters in the newsroom use Otter AI, which can transcribe interview recordings instantly. So, instead of spending hours transcribing, they can quickly read through the AI transcription, picking out the best quotes in minutes. We found this to be true in the video interviews we do, too. Dozens of local leaders, community organizers, athletes, and others have been interviewed in the KDH News Video Studio which we post to YouTube, Facebook, and kdhnews.com.
In minutes, we can take the audio files of those interviews and have them fully transcribed. Or we can just take that audio file and give it to AI with a simple prompt, “Take this audio file and write a 500-word news article based on the interview. Use AP style and give me a good headline.”
Usually, the result is very good. But we have to keep a close eye on the work, too. AI is getting better at preventing hallucinations, but they still pop up.
Like when we were first experimenting with AI in the newsroom a couple of years ago. We tried it with an article about the severe flooding that impacted Coryell County. We had already reported on the May 2024 floods that caused the Leon and Lampasas Rivers to swell, sweeping away cattle and damaging homes, bridges, and more.
We asked AI to summarize the government response to the flooding, and it gave a fair, accurate account of what happened, including the disaster declarations and hard work from county officials. Except for one thing: It said the National Guard responded.
As an editor who worked directly with the reporters who covered those devastating floods, I knew the National Guard was not deployed to Coryell County. So, we asked AI: “Why did you say the National Guard responded to Coryell County?”
It answered with something like, “Because the National Guard has responded to similar emergencies and it made sense.” I didn’t like that answer. Wisely, we ended up not publishing that piece, but the experience was valuable – and taught me that we have to be very cautious using AI in our line of work, where our credibility is everything.
That was nearly two years ago, and the KDH Newsroom has been tip-toeing our way into AI ever since. Meanwhile, the AI models have been getting a lot better: fewer hallucinations, improved sentence structure, more polished news writing, creative summaries and headlines.
One explanation is that AI has improved as more people have used it successfully. At the same time, trust in AI has gone up, especially in the last 12 months. So in February of this year, I researched and drafted an AI policy for the newsroom. It’s a three-page document carefully outlining how we use AI. Here’s the policy’s mission statement:
“The Killeen Daily Herald’s mission is to responsibly leverage AI to enhance our products and journalism, enriching the experience for our Central Texas audience. We ensure all published material upholds our 135-year legacy of accuracy and credibility through rigorous human verification and the highest journalistic standards.”
The use of the word “leverage” was my own and intentional. We use AI tools to better serve our readers, provide them with more news content and more useful information and maintain high journalism standards.
We are transparent when it comes to clearly marking any content created, in part, with AI tools. For these, we attach our “KDH Verified” graphic which identifies that content as substantially produced with AI, and we also use editor’s notes and other indicators to mark AI when needed.
I’d like to say that every print journalist I’ve worked with in the past 25 years at six different newspapers has been a great writer. But that’s just not the case. Some have been pretty bad. Some are great. Many are mediocre. And some are terrible. For some, the passion is the reporting over the writing.
In journalism school at Sam Houston State University in East Texas in 2001, we had a class discussion about what goes into “reporting” and what goes into the “writing” on any given story.
One student said it was the “reporting” that she really enjoyed, and not so much the “writing.” She liked asking questions, interviewing people, getting the scoop. But when it came to having to write it up – eh, the fun part was over.
Nowadays, a reporter can go out, interview people, take photos and videos, and load up everything into AI, which can “write” the story based solely on what the reporter gathered. Instead of spending a couple of hours writing, the story is done in minutes. The reporter and editor still have to review and edit it, but the big piece of the process – done with AI – just saved valuable time, allowing the reporter to tackle the next story. Will it be better than a human writing it?
