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By Dr. Robert Ambros, Chairman of Robotics & Artificial Intelligence

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AI technologists are in fast pursuit of artificial general intelligence (AGI), with some predicting it could arrive as soon as in the next few years. Just this month, Google outlined their latest step towards AGI with a new AI model that interacts with a convincing simulation of the real world.

It’s easy to see why there’s been so much hype around AGI. An AI tool that can think as well as humans, act on its own, and do everything a person can with the processing speed and knowledge of a tireless AI system would completely transform our economy and definition of humanity.

But going all-in on AGI is a misplaced goal, as doing so risks putting too much weight on automation-at-any-cost. We’ve become so enthralled by the idea of AGI that we’ve failed to realize the inevitable shortcomings that may accompany it: we’re thinking it’ll solve all our problems, when they’d be better solved with the collaborative technology that’s already right here in front of us.

AGI and full automation shouldn’t be the main goal in our AI journey, and robots’ lack of robust perception in complex environments plus a still-limited ability to adapt makes achieving this goal a ways off regardless. Instead, we should be focused on seamless human-AI systems in which we combine human judgement and intangibles with the productivity and speed of AI. With AGI as the singular goal for many technology developers, however, is it possible to create advanced AI while keeping humans at the helm?

A Better Vision: Human-AI Synergy in Robotics

Nothing makes the current predicament clearer than the world of robotics. While it would be incredible to have a fully automated robot that could run the factory floor by itself, this robot would not be of much use to anybody if its productivity remains a fraction of that of a human worker. I know this issue well, especially as it relates to intelligent robotics.

During my two decades as Chief of the Software, Robotics and Simulation Division at NASA’s Senior Executive Service, I saw up close the balancing act of full-blown automation and the need for a human touch. Often times, we get too caught up in creating the perfect robot; one that can do everything and anything, at any cost. But this often misses the point entirely. In both robotics and AI, technology is a tool, not a craftsman. Furthermore, automating the last 10% of a system often costs as much as the first 90%, so a good business decision results in a mix.

To this end, Human-in-the-Loop (HITL) systems, which combine human intelligence and machine-learning capabilities, are still the best way forward for AI and robotics. They also demonstrate a clear template for how we should engage with this emerging technology and how we can prepare for the onset of AGI.

Out in the Field

Take for instance the robot dog ‘Spot’ who helps monitor the buried Roman city of Pompeii. This robo-pup can gather and record data to help manage the area, keep it safe, and notify archaeologists of any parts of the site that have fallen into disrepair or pose potential safety risks. This machine helps archaeologists focus on the tasks only they can do, including carefully digging for ancient artifacts and continuing their tireless research. No matter how advanced AI gets, the final archaeological judgements must be made by a human expert, as only they can assess the inherently human value of the artifacts in question.

A close quadruped relative of Spot is the Swiss inspection ‘cobot’ (collaborative robot), which helps professional inspectors survey the equipment, safety, infrastructure, and air quality of industrial facilities. While a human expert must still analyze the data and make final determinations, this inspector-bot can help gather up-close, high-quality information that would otherwise be difficult or impossible to collect. Using visual and thermal cameras, an ultrasonic microphone, powerful spotlights, and even Lidar sensors, this machine can traverse nearly any terrain on Earth, even resorting to parkour if need be. The inspections are far too important to conduct with robots alone, so human judgement is added once all the data is collected. 

These robots are already in the field, simplifying dangerous or previously laborious physical processes to increase productivity many times over, and this type of human-AI collaboration is where we must focus.

Surgical Precision

We’re seeing these strides beyond fieldwork as well, in situations where human lives are on the line. In the operating room, the Da Vinci Surgical System is helping doctors conduct surgeries with extreme dexterity and consistency. Using this system, surgeons use a viewfinder, a patient cart with robotic arms, and a 3D visualization tool to carry out complex procedures with tiny incisions, meaning less pain and a faster recovery time for the patient. Consider the viral video of a grape undergoing a surgical procedure. That was done completely with the help of the Da Vinci system, combining the judgement of senior surgeons with the manual coordination of the best young hands.

While the technology performed a large degree of the work, it was all overseen by a highly trained medical professional, giving much more peace of mind for whoever’s going under the knife. However intelligent and capable the AI may be, few patients would likely feel comfortable with the final medical decisions being made by an entity than does not, and cannot, know what it means to be human.

Preparing for AGI by Focusing on Today

While the general applicability of an AGI might be the holy grail, take it from someone who’s been in robotics since the beginning: the advancements so many are waiting for – namely autonomous and sentient robots – are still light years away.

Regardless, we shouldn’t be discouraged. Combining AI systems that focus on narrow, but important tasks with more generalized human judgement will be even more important than AGI in the next decades. No matter how advanced and intelligent AI gets, we cannot coexist with technology that acts in a way we don’t understand or control. Collaborative HITL technology removes this “black box” problem before it starts, allowing us to focus on the end result rather than autonomy for its own sake. The human link isn’t a necessary evil to be endured as we await full autonomy – it’s the key for continued success.

Along the path towards AGI, we should not seek to automate just because we can, but because it makes sense from a business and safety perspective. We should be preparing for an economy that integrates AI and human labor, not waiting for one to fall in our lap.

Combining humans with AI in robotics is the more careful, fruitful, responsible approach. This combination will help us develop a more AGI-ready future; one in which AI’s success has less to do with the technology we can build and more with the world we can make with it at our sides.

Featured Leadership​

Dr. Robert Ambrose, Chairman of Robotics & Artificial Intelligence received his Ph.D. from the University of Texas at Austin in Mechanical Engineering and received his M.S. and B.S. degrees from Washington University in St. Louis. Ambrose joined the faculty of Texas A&M and accepted the J. Mike Walker Chair in Mechanical Engineering in August 2021. Also in August of 2021, Dr. Ambrose retired from NASA, where he served in the Senior Executive Service as the Chief of the Software, Robotics and Simulation Division at NASA’s Johnson Space Center in Houston, Texas. He continues to serve as the Director for Space and Robotics at the Bush Combat Development Complex and his research interests are in space systems for defense, security and commercial applications, as well as robotics and autonomous systems for helping humans on Earth.

JULY 25, 2025 | PUBLISHED IN​

by Dhaval Jadav alliant Chief Executive Officer​

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Before it was called “Silicon Valley,” Santa Clara Valley was best known for producing 30% of the world’s prunes. The technology epicenter we revere today didn’t form accidentally. Leaders saw the future and bet big.

Texas is at a similar technological precipice. With OpenAI and Apple choosing to build out major artificial intelligence data centers and server manufacturing plants in our state, there’s a rare and urgent window for us to lead the next wave of tech innovation.

The key to growing Texas into a tech powerhouse lies in three fundamentals: talent, energy and infrastructure.

Let’s start with talent. Beyond capital or infrastructure, Silicon Valley amassed a concentration of visionary people. Labs and server farms can be built anywhere, but the minds inside them hold irreplaceable value. Fortunately, a large share of that talent already calls Texas home.

In Houston, we have institutions that have pushed the boundaries of science like the Johnson Space Center. In Austin, a growing base of big tech talent is already reshaping the local economy, and Apple and OpenAI’s new facilities will only accelerate that trend. Talent growth often ebbs and flows with the market, so we must build on Texas’ long-term fundamentals to attract and retain tomorrow’s best minds.

For Texas to become an AI stronghold, state and private firms must reinvest in our tech talent pipeline at the academic level. At Texas A&M University, pioneers like NASA’s former robotics chief Dr. Robert Ambrose are fostering a new generation of “hard tech” talent bringing AI into the physical world through advanced robotics. We must aggressively expand academic programs that promote this kind of interdisciplinary innovation to build an edge that’s impossible to outsource.

Of course, AI doesn’t run on talent alone. It runs on power. As more powerful AI models come online, the infrastructure required to run and cool them becomes immense. Texas holds a natural advantage as the nation’s energy capital and, unlike Silicon Valley, we’ve got the land to support power-intensive technology.

Powering next-gen tech in Texas also means tackling grid reliability and water scarcity to ensure 24/7 operation. We can’t afford to be reactive: If we want to position ourselves as the default home for AI growth, we need to invest now in long-term, resilient infrastructure solutions.

Most importantly, Texas has a uniquely pro-business mindset, making it easy for innovators to scale quickly and take smart risks while other states tie them up in red tape.

How do we pay for the necessary investments? Funding for the science, technology, engineering and mathematics (STEM) talent pipeline, as well as infrastructure improvements, can come from a combination of partnerships with private companies and reappropriated taxpayer funds, since these programs’ economic improvements will benefit every Texan. To that end, Texas could revive and scale a Tech Reinvestment Program, inspired by the Texas Emerging Technology Fund, and redirect a portion of the new $1 billion school voucher budget to it, while filling the rest in with private funding.

A $750 million strategic investment in the first year would generate employment and innovation wins to attract further state and private investment. This initial funding would support faculty hiring and graduate fellowships, build and upgrade robotics and AI labs, strengthen power-grid resilience, and fund water system improvements, all while seeding K-12 STEM pipelines.

Put it all together – top-tier talent, abundant energy, infrastructure capacity, and a founder-first mentality – and Texas could become the heart of America’s “AI Belt.”

But here’s the catch: We haven’t fully recognized this potential. And if we wait too long to act, another state will.

Texas doesn’t need to follow someone else’s playbook. We’ve got the raw ingredients and the momentum to write our own. The next five years will determine whether we lead the future of AI or watch it pass us by. Let’s move.

Featured Leadership​

Dean Zerbe is alliant’s National Managing Director based in the firm’s Washington D.C. office. Prior to joining alliantgroup, Mr. Zerbe was Senior Counsel and Tax Counsel to the U.S. Senate Committee on Finance. He worked closely with then-Chairman and current Ranking Member of the Finance Committee, Senator Charles Grassley (R-IA), on tax legislation. During his tenure on the Finance Committee, Mr. Zerbe was intimately involved with nearly every major piece of tax legislation that was signed into law – including the 2001 and 2003 tax reconciliation bills, the JOBS bill in 2004 (corporate tax reform), and the Pension Protection Act. Mr. Zerbe is a frequent speaker and author on the outlook for short-term and long-term changes in tax policy, as well as ways accounting firms can help their clients lower their tax bill.