There\u2019s\u00a0an adage\u00a0when trying\u00a0to unravel a\u00a0corporate\u00a0mystery: follow the money. And when you start following the money in connection with the AI boom, you can get a sense\u00a0of the rumblings of an\u00a0erupting\u00a0volcano. Lenders and investors\u00a0are starting to get nervous,\u00a0which could\u00a0jeopardize planned\u00a0funding.<\/p>\n
We have written before about the risk that\u00a0current\u00a0power and data center\u00a0infrastructure can\u2019t support<\/a>\u00a0the continued exponential development of AI tools, the fact that the\u00a0cost of verifying AI outputs<\/a>\u00a0is\u00a0exceeding\u00a0the\u00a0savings, and the\u00a0resulting erosion of trust<\/a>\u00a0in historic processes and workflows.\u00a0<\/p>\n Financial Risk<\/strong><\/p>\n But there is another perhaps more fundamental risk that may\u00a0cause\u00a0the\u00a0volcano\u00a0eruption we have been\u00a0discussing. Thus far, the focus has been on\u00a0building\u00a0mega data centers needed for AI to work. These data centers are expensive to build and get permitted. They take\u00a0five to seven years to build before the power can even be turned on.\u00a0<\/p>\n And the power and energy capacity needed to make these\u00a0existing\u00a0and\u00a0contemplated\u00a0centers\u00a0doesn\u2019t\u00a0exist.\u00a0The power plants needed to supply that capacity have\u00a0to get\u00a0regulatory approval and be built. That too takes time.<\/p>\n Not only does\u00a0building\u00a0the capacity and data centers take time, it takes money. It requires lots of money. That money can come from\u00a0investors,\u00a0or\u00a0it can come from lenders. But because these projects are long-term investments and payoffs, the return won\u2019t come for years.\u00a0<\/p>\n So\u00a0anything\u00a0that happens which makes those long-term\u00a0returns riskier than originally thought is a problem. If the\u00a0infrastructure and power aren\u2019t there to support the\u00a0demand for AI, that\u00a0long-term\u00a0return\u00a0is\u00a0jeopardized,\u00a0and they get nervous. If something happens, say flood or hurricane, that delays the completion of the project and the return, they get nervous.\u00a0<\/p>\n And when investors and lenders get nervous, they begin looking for options like calling the loans or dumping their investments. When that happens, the stock value of the\u00a0entities\u00a0goes down. The investors in\u00a0the entities\u00a0developing the AI platforms and programs then\u00a0also\u00a0get nervous and begin to pull back.\u00a0<\/p>\n The\u00a0infrastructure challenges\u00a0create a cascading financial risk that\u00a0compounds the angst.\u00a0It\u2019s a vicious circle. At some point, the projects themselves get jeopardized.\u00a0That reduces\u00a0demand, reduces\u00a0infrastructure\u00a0building,\u00a0and the whole house of cards begins to fall.\u00a0It\u2019s\u00a0akin to\u00a0building roads (or as discussed below, railroads)\u00a0without knowing how much traffic will use\u00a0them. If the traffic\u00a0doesn\u2019t\u00a0materialize,\u00a0you\u2019re\u00a0left with\u00a0expensive\u00a0and\u00a0underutilized\u00a0capacity, capacity that doesn\u2019t provide the expected financial return.<\/p>\n And there are\u00a0growing reports<\/a>\u00a0suggesting that this is exactly what may be beginning.<\/p>\n Increased Risk<\/strong>s<\/strong><\/p>\n The problem is compounded by the FOMO of various\u00a0investors that\u2019s been going on as the AI hype\u00a0hit overdrive. Investors and lenders with\u00a0little\u00a0expertise and knowledge have waded in when perhaps they\u00a0shouldn\u2019t\u00a0have.\u00a0And if they get\u00a0nervous, they may be quick to exit.\u00a0<\/p>\n A\u00a0recent article<\/a>\u00a0makes this very point. In 2025, credit transactions for data centers in the U. S.\u00a0reached at least $178.5\u00a0billion. Major\u00a0tech players have pushed the total to over\u00a0$6.57 trillion. And a big piece of the\u00a0future data center capacity will be built by new players with little data center experience.<\/p>\n We talked to an\u00a0experienced\u00a0infrastructure investor,\u00a0Hector Fornelli<\/a>,\u00a0about this very\u00a0problem. Fornelli\u2019s company,\u00a0AgilaInvestments<\/a>, has invested in multiple data center projects, big and small. He says,\u00a0\u201cThere\u2019s\u00a0too much money going into this. 40% of investments going through Wall Street are going into the AI data center space. At some point\u00a0it\u2019s\u00a0going to break. And the reason why it\u2019s going to break is because people are not taking the proper steps to get there.\u201d\u00a0He\u00a0also\u00a0noted\u00a0that the\u00a0energy capacity\u00a0in the U.S. is\u00a0nowhere\u00a0near enough to supply the demand for power to run\u00a0all\u00a0the\u00a0planned\u00a0data centers. But\u00a0entities\u00a0are\u00a0continuing to\u00a0invest in the centers without considering where the power might come from or whether there are off-meter\u00a0sources.\u00a0<\/p>\n Moreover, the data centers generate massive\u00a0amounts\u00a0of heat that\u00a0must\u00a0be dealt with\u00a0which\u00a0is not being considered by the data center planners or their investors. And finally, there needs to be in place\u00a0agreements\u00a0ensuring\u00a0that\u00a0the\u00a0output from\u00a0centers\u00a0will provide a return. \u00a0As Fornelli puts it, \u201cIf it doesn\u2019t have a clear pathway to those three,\u00a0it\u2019s\u00a0not worth investing in\u00a0because at some point there\u2019s going to be a surplus of data center offers and demand is not going to be as large.\u201d Fornelli\u00a0believes\u00a0that\u2019s the\u00a0kind\u00a0of due diligence that should be done but is not, sowing the seeds for\u00a0disaster.<\/p>\n History<\/strong>\u00a0Lessons<\/strong><\/p>\n As George Santayana famously\u00a0said,\u00a0\u201cThose who cannot remember the past are\u00a0condemned\u00a0to repeat it.\u201d That may be the case here as some pundits have\u00a0already noted<\/a>.\u00a0<\/p>\n In the mid-1800s, there was a huge boom in railway\u00a0investment as investors became enchanted with the\u00a0railroads. But many of the projects in which they invested were poorly\u00a0planned\u00a0or never built. As\u00a0investors\u00a0began to see the profits had been vastly overestimated, the railroad stock prices\u00a0collapsed,\u00a0and the investments were\u00a0lost.<\/p>\n A more recent example:\u00a0in the 1990s, the internet and mobile phones were\u00a0all the investor rage.\u00a0They\u00a0believed demand for data and connectivity would skyrocket, so they spent huge amounts to build the networks that would carry that traffic.\u00a0But the demand didn\u2019t play out as forecast. That\u00a0led to the collapse of major players like WorldCom and Global Crossing\u00a0and\u00a0the\u00a0Telecoms Crash<\/a>\u00a0in 2001.<\/p>\n Easing\u00a0Investors\u2019 Angst<\/strong><\/p>\n But there are solutions that could ease investors\u2019 angst.\u00a0As we discussed in a\u00a0previous article<\/a>,\u00a0smaller\u00a0data center and energy\u00a0projects that are less\u00a0expensive\u00a0and don\u2019t take so long to\u00a0build could be employed.\u00a0<\/p>\n With smaller projects, the resulting risk to investors is less.\u00a0Smaller projects can better match demand since if demand falls, the amount at risk for investors is smaller. They can be added incrementally and still be economically\u00a0valid. If\u00a0the projects are\u00a0delayed,\u00a0the impact is less. The window for something to go wrong is\u00a0smaller. There\u00a0is a faster track to the return. They allow for greater\u00a0flexibility\u00a0should there be unanticipated risk. Smaller projects are less sensitive\u00a0to\u00a0interest\u00a0rate hikes.<\/p>\n These\u00a0smaller projects can take the form\u00a0of smaller data centers powered with generators that depend on existing and underutilized energy\u00a0sources\u00a0like combined heat and power (CHP) and behind-the-meter renewable energy\u00a0sources.<\/p>\n Fornelli agrees\u00a0that smaller projects may not only be less expensive but\u00a0useful: \u201cThere are other uses for data centers that people are not really paying attention to.\u00a0There\u2019s medical services. Hospitals, medical labs, pharmaceutical labs and banks that can use AI big time, but they don\u2019t need a 300 megawatt data center. They need a 10 megawatt data center. Or a five megawatt data center. They need to process a lot of information, but the source of the information is one, and the delivery of the information is to one single place.\u201d\u00a0<\/p>\n Or, for example law firms.<\/p>\n The Impact for Legal<\/strong><\/p>\n Which brings us to the impact of all this on the legal community. What\u2019s happening right now is a huge rush to adopt AI tools deep within\u00a0legal workflows and processes.\u00a0Often this employment is made without considering whether the tools\u00a0achieve\u00a0any savings or\u00a0assistance.<\/p>\n And\u00a0with that rush\u00a0and lack of studied approach, that FOMO, comes the risk of overreliance and lack of\u00a0contingency\u00a0planning if things go south on the infrastructure or supply side. If the volcano blows, then law firms may be left with\u00a0unusable and expensive technology. They\u00a0will\u00a0have to scramble to figure out how to get work done with\u00a0which\u00a0technology\u00a0was a\u00a0substantial contributor. In an industry that is deadline driven with little margin for error, that could be\u00a0catastrophic.<\/p>\n It\u2019s happened before.\u00a0Perhaps most famously was the\u00a0collapse of\u00a0Clearspire<\/a>\u00a0in 2010.\u00a0Clearspire\u00a0promised a tech- forward virtual law firm model\u00a0that would be more efficient.\u00a0But when it shut down due to operational and financial issues, those relying on it had to quickly find other options.\u00a0In\u00a02010, the practice\u00a0management company Aderant Expert Sierra was discontinued,\u00a0forcing customers\u00a0to migrate to other services. A similar thing happened when\u00a0Amicus Attorney\u00a0slowly unwound.<\/a><\/p>\n These kinds of migrations can be disruptive to say the least. Imagine the cost and disruptions should there be a significant AI\u00a0infrastructure\u00a0failure or if the AI services that depend on that\u00a0infrastructure\u00a0didn\u2019t function properly. The Cloudflare outage could be a harbinger of things to come.<\/p>\n What\u2019s a Law Firm\u00a0<\/strong>to<\/strong>\u00a0Do?<\/strong><\/p>\n Warnings\u00a0like these are often met with a \u201cit can\u2019t happen here\u201d shrug or a \u201cit\u2019s too big to fail\u201d roll of the eyes.\u00a0But lawyers and legal\u00a0professionals pride themselves on being skeptical and assessing risks for\u00a0clients. We need to do the same for ourselves.<\/p>\n That means contingency\u00a0planning\u00a0for\u00a0if\u00a0(when?)\u00a0the\u00a0\u201cwhat if\u201d actually happens.\u00a0It means hedging bets on AI to prevent overreliance. It means asking if you\u2019re purchasing AI tools out of FOMO or for valid reasons.\u00a0As the last one holding on to my BlackBerry long after the cost analysis made no sense, I know\u00a0what it means to not be tech diligent.<\/p>\n It Means Due Diligence<\/strong><\/p>\n Talk to any attorney today and they\u00a0don\u2019t have\u00a0a clue what their contracts with AI vendors actually say or how financially stable many vendors\u00a0really are. That\u2019s not the kind of due diligence we engage in for our clients.<\/p>\n Due diligence\u00a0means assessing\u00a0vendors\u2019\u00a0financial\u00a0integrity. Can they continue\u00a0supplying\u00a0products and services\u00a0if there is a downturn?\u00a0It means looking at the debt of and\u00a0investments\u00a0in the\u00a0vendor\u00a0to determine staying power and robustness. It means looking hard at vendor\u00a0agreements\u00a0and\u00a0indemnity\u00a0and liability\u00a0provisions.\u00a0<\/p>\n It means keeping up with\u00a0contractual\u00a0modifications that\u00a0vendors like to spew out with little notice. It means paying attention to what is going on in financial markets\u00a0relating\u00a0to AI and infrastructure.\u00a0<\/p>\n It means following the money.<\/p>\n Stephen Embry is a lawyer, speaker, blogger, and writer. He publishes\u00a0TechLaw Crossroads<\/a>, a blog devoted to the examination of the tension between technology, the law, and the practice of law<\/strong><\/em>.\u00a0<\/p>\n Melissa \u201cRogo\u201d Rogozinski is an operations-driven executive with more than three decades of experience scaling high-growth legal-tech startups and B2B organizations. A trusted partner to CEOs and founders, Rogo aligns systems, product, marketing, sales, and client success into a unified, performance-focused engine that accelerates organizational maturity. Connect with\u00a0Rogo on LinkedIn<\/a>.<\/em><\/strong><\/p>\n The post Like Lawyers\u00a0In\u00a0Pompeii: Is Legal Ignoring The Coming AI Financial Crisis? (Part IV)<\/a> appeared first on Above the Law<\/a>.<\/p>\n There\u2019s\u00a0an adage\u00a0when trying\u00a0to unravel a\u00a0corporate\u00a0mystery: follow the money. And when you start following the money in connection with the AI boom, you can get a sense\u00a0of the rumblings of an\u00a0erupting\u00a0volcano. Lenders and investors\u00a0are starting to get nervous,\u00a0which could\u00a0jeopardize planned\u00a0funding.<\/p>\n We have written before about the risk that\u00a0current\u00a0power and data center\u00a0infrastructure can\u2019t support<\/a>\u00a0the continued exponential development of AI tools, the fact that the\u00a0cost of verifying AI outputs<\/a>\u00a0is\u00a0exceeding\u00a0the\u00a0savings, and the\u00a0resulting erosion of trust<\/a>\u00a0in historic processes and workflows.\u00a0<\/p>\n Financial Risk<\/strong><\/p>\n But there is another perhaps more fundamental risk that may\u00a0cause\u00a0the\u00a0volcano\u00a0eruption we have been\u00a0discussing. Thus far, the focus has been on\u00a0building\u00a0mega data centers needed for AI to work. These data centers are expensive to build and get permitted. They take\u00a0five to seven years to build before the power can even be turned on.\u00a0<\/p>\n And the power and energy capacity needed to make these\u00a0existing\u00a0and\u00a0contemplated\u00a0centers\u00a0doesn\u2019t\u00a0exist.\u00a0The power plants needed to supply that capacity have\u00a0to get\u00a0regulatory approval and be built. That too takes time.<\/p>\n Not only does\u00a0building\u00a0the capacity and data centers take time, it takes money. It requires lots of money. That money can come from\u00a0investors,\u00a0or\u00a0it can come from lenders. But because these projects are long-term investments and payoffs, the return won\u2019t come for years.\u00a0<\/p>\n So\u00a0anything\u00a0that happens which makes those long-term\u00a0returns riskier than originally thought is a problem. If the\u00a0infrastructure and power aren\u2019t there to support the\u00a0demand for AI, that\u00a0long-term\u00a0return\u00a0is\u00a0jeopardized,\u00a0and they get nervous. If something happens, say flood or hurricane, that delays the completion of the project and the return, they get nervous.\u00a0<\/p>\n And when investors and lenders get nervous, they begin looking for options like calling the loans or dumping their investments. When that happens, the stock value of the\u00a0entities\u00a0goes down. The investors in\u00a0the entities\u00a0developing the AI platforms and programs then\u00a0also\u00a0get nervous and begin to pull back.\u00a0<\/p>\n The\u00a0infrastructure challenges\u00a0create a cascading financial risk that\u00a0compounds the angst.\u00a0It\u2019s a vicious circle. At some point, the projects themselves get jeopardized.\u00a0That reduces\u00a0demand, reduces\u00a0infrastructure\u00a0building,\u00a0and the whole house of cards begins to fall.\u00a0It\u2019s\u00a0akin to\u00a0building roads (or as discussed below, railroads)\u00a0without knowing how much traffic will use\u00a0them. If the traffic\u00a0doesn\u2019t\u00a0materialize,\u00a0you\u2019re\u00a0left with\u00a0expensive\u00a0and\u00a0underutilized\u00a0capacity, capacity that doesn\u2019t provide the expected financial return.<\/p>\n And there are\u00a0growing reports<\/a>\u00a0suggesting that this is exactly what may be beginning.<\/p>\n Increased Risk<\/strong>s<\/strong><\/p>\n The problem is compounded by the FOMO of various\u00a0investors that\u2019s been going on as the AI hype\u00a0hit overdrive. Investors and lenders with\u00a0little\u00a0expertise and knowledge have waded in when perhaps they\u00a0shouldn\u2019t\u00a0have.\u00a0And if they get\u00a0nervous, they may be quick to exit.\u00a0<\/p>\n A\u00a0recent article<\/a>\u00a0makes this very point. In 2025, credit transactions for data centers in the U. S.\u00a0reached at least $178.5\u00a0billion. Major\u00a0tech players have pushed the total to over\u00a0$6.57 trillion. And a big piece of the\u00a0future data center capacity will be built by new players with little data center experience.<\/p>\n We talked to an\u00a0experienced\u00a0infrastructure investor,\u00a0Hector Fornelli<\/a>,\u00a0about this very\u00a0problem. Fornelli\u2019s company,\u00a0AgilaInvestments<\/a>, has invested in multiple data center projects, big and small. He says,\u00a0\u201cThere\u2019s\u00a0too much money going into this. 40% of investments going through Wall Street are going into the AI data center space. At some point\u00a0it\u2019s\u00a0going to break. And the reason why it\u2019s going to break is because people are not taking the proper steps to get there.\u201d\u00a0He\u00a0also\u00a0noted\u00a0that the\u00a0energy capacity\u00a0in the U.S. is\u00a0nowhere\u00a0near enough to supply the demand for power to run\u00a0all\u00a0the\u00a0planned\u00a0data centers. But\u00a0entities\u00a0are\u00a0continuing to\u00a0invest in the centers without considering where the power might come from or whether there are off-meter\u00a0sources.\u00a0<\/p>\n Moreover, the data centers generate massive\u00a0amounts\u00a0of heat that\u00a0must\u00a0be dealt with\u00a0which\u00a0is not being considered by the data center planners or their investors. And finally, there needs to be in place\u00a0agreements\u00a0ensuring\u00a0that\u00a0the\u00a0output from\u00a0centers\u00a0will provide a return. \u00a0As Fornelli puts it, \u201cIf it doesn\u2019t have a clear pathway to those three,\u00a0it\u2019s\u00a0not worth investing in\u00a0because at some point there\u2019s going to be a surplus of data center offers and demand is not going to be as large.\u201d Fornelli\u00a0believes\u00a0that\u2019s the\u00a0kind\u00a0of due diligence that should be done but is not, sowing the seeds for\u00a0disaster.<\/p>\n History<\/strong>\u00a0Lessons<\/strong><\/p>\n As George Santayana famously\u00a0said,\u00a0\u201cThose who cannot remember the past are\u00a0condemned\u00a0to repeat it.\u201d That may be the case here as some pundits have\u00a0already noted<\/a>.\u00a0<\/p>\n In the mid-1800s, there was a huge boom in railway\u00a0investment as investors became enchanted with the\u00a0railroads. But many of the projects in which they invested were poorly\u00a0planned\u00a0or never built. As\u00a0investors\u00a0began to see the profits had been vastly overestimated, the railroad stock prices\u00a0collapsed,\u00a0and the investments were\u00a0lost.<\/p>\n A more recent example:\u00a0in the 1990s, the internet and mobile phones were\u00a0all the investor rage.\u00a0They\u00a0believed demand for data and connectivity would skyrocket, so they spent huge amounts to build the networks that would carry that traffic.\u00a0But the demand didn\u2019t play out as forecast. That\u00a0led to the collapse of major players like WorldCom and Global Crossing\u00a0and\u00a0the\u00a0Telecoms Crash<\/a>\u00a0in 2001.<\/p>\n Easing\u00a0Investors\u2019 Angst<\/strong><\/p>\n But there are solutions that could ease investors\u2019 angst.\u00a0As we discussed in a\u00a0previous article<\/a>,\u00a0smaller\u00a0data center and energy\u00a0projects that are less\u00a0expensive\u00a0and don\u2019t take so long to\u00a0build could be employed.\u00a0<\/p>\n With smaller projects, the resulting risk to investors is less.\u00a0Smaller projects can better match demand since if demand falls, the amount at risk for investors is smaller. They can be added incrementally and still be economically\u00a0valid. If\u00a0the projects are\u00a0delayed,\u00a0the impact is less. The window for something to go wrong is\u00a0smaller. There\u00a0is a faster track to the return. They allow for greater\u00a0flexibility\u00a0should there be unanticipated risk. Smaller projects are less sensitive\u00a0to\u00a0interest\u00a0rate hikes.<\/p>\n These\u00a0smaller projects can take the form\u00a0of smaller data centers powered with generators that depend on existing and underutilized energy\u00a0sources\u00a0like combined heat and power (CHP) and behind-the-meter renewable energy\u00a0sources.<\/p>\n Fornelli agrees\u00a0that smaller projects may not only be less expensive but\u00a0useful: \u201cThere are other uses for data centers that people are not really paying attention to.\u00a0There\u2019s medical services. Hospitals, medical labs, pharmaceutical labs and banks that can use AI big time, but they don\u2019t need a 300 megawatt data center. They need a 10 megawatt data center. Or a five megawatt data center. They need to process a lot of information, but the source of the information is one, and the delivery of the information is to one single place.\u201d\u00a0<\/p>\n Or, for example law firms.<\/p>\n The Impact for Legal<\/strong><\/p>\n Which brings us to the impact of all this on the legal community. What\u2019s happening right now is a huge rush to adopt AI tools deep within\u00a0legal workflows and processes.\u00a0Often this employment is made without considering whether the tools\u00a0achieve\u00a0any savings or\u00a0assistance.<\/p>\n And\u00a0with that rush\u00a0and lack of studied approach, that FOMO, comes the risk of overreliance and lack of\u00a0contingency\u00a0planning if things go south on the infrastructure or supply side. If the volcano blows, then law firms may be left with\u00a0unusable and expensive technology. They\u00a0will\u00a0have to scramble to figure out how to get work done with\u00a0which\u00a0technology\u00a0was a\u00a0substantial contributor. In an industry that is deadline driven with little margin for error, that could be\u00a0catastrophic.<\/p>\n It\u2019s happened before.\u00a0Perhaps most famously was the\u00a0collapse of\u00a0Clearspire<\/a>\u00a0in 2010.\u00a0Clearspire\u00a0promised a tech- forward virtual law firm model\u00a0that would be more efficient.\u00a0But when it shut down due to operational and financial issues, those relying on it had to quickly find other options.\u00a0In\u00a02010, the practice\u00a0management company Aderant Expert Sierra was discontinued,\u00a0forcing customers\u00a0to migrate to other services. A similar thing happened when\u00a0Amicus Attorney\u00a0slowly unwound.<\/a><\/p>\n These kinds of migrations can be disruptive to say the least. Imagine the cost and disruptions should there be a significant AI\u00a0infrastructure\u00a0failure or if the AI services that depend on that\u00a0infrastructure\u00a0didn\u2019t function properly. The Cloudflare outage could be a harbinger of things to come.<\/p>\n What\u2019s a Law Firm\u00a0<\/strong>to<\/strong>\u00a0Do?<\/strong><\/p>\n Warnings\u00a0like these are often met with a \u201cit can\u2019t happen here\u201d shrug or a \u201cit\u2019s too big to fail\u201d roll of the eyes.\u00a0But lawyers and legal\u00a0professionals pride themselves on being skeptical and assessing risks for\u00a0clients. We need to do the same for ourselves.<\/p>\n That means contingency\u00a0planning\u00a0for\u00a0if\u00a0(when?)\u00a0the\u00a0\u201cwhat if\u201d actually happens.\u00a0It means hedging bets on AI to prevent overreliance. It means asking if you\u2019re purchasing AI tools out of FOMO or for valid reasons.\u00a0As the last one holding on to my BlackBerry long after the cost analysis made no sense, I know\u00a0what it means to not be tech diligent.<\/p>\n It Means Due Diligence<\/strong><\/p>\n Talk to any attorney today and they\u00a0don\u2019t have\u00a0a clue what their contracts with AI vendors actually say or how financially stable many vendors\u00a0really are. That\u2019s not the kind of due diligence we engage in for our clients.<\/p>\n Due diligence\u00a0means assessing\u00a0vendors\u2019\u00a0financial\u00a0integrity. Can they continue\u00a0supplying\u00a0products and services\u00a0if there is a downturn?\u00a0It means looking at the debt of and\u00a0investments\u00a0in the\u00a0vendor\u00a0to determine staying power and robustness. It means looking hard at vendor\u00a0agreements\u00a0and\u00a0indemnity\u00a0and liability\u00a0provisions.\u00a0<\/p>\n It means keeping up with\u00a0contractual\u00a0modifications that\u00a0vendors like to spew out with little notice. It means paying attention to what is going on in financial markets\u00a0relating\u00a0to AI and infrastructure.\u00a0<\/p>\n It means following the money.<\/p>\n Stephen Embry is a lawyer, speaker, blogger, and writer. He publishes\u00a0TechLaw Crossroads<\/a>, a blog devoted to the examination of the tension between technology, the law, and the practice of law<\/strong><\/em>.\u00a0<\/p>\n Melissa \u201cRogo\u201d Rogozinski is an operations-driven executive with more than three decades of experience scaling high-growth legal-tech startups and B2B organizations. A trusted partner to CEOs and founders, Rogo aligns systems, product, marketing, sales, and client success into a unified, performance-focused engine that accelerates organizational maturity. Connect with\u00a0Rogo on LinkedIn<\/a>.<\/em><\/strong><\/p>\n The post Like Lawyers\u00a0In\u00a0Pompeii: Is Legal Ignoring The Coming AI Financial Crisis? (Part IV)<\/a> appeared first on Above the Law<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":" There\u2019s\u00a0an adage\u00a0when trying\u00a0to unravel a\u00a0corporate\u00a0mystery: follow the money. And when you start following the money in connection with the AI boom, you can get a sense\u00a0of the rumblings of an\u00a0erupting\u00a0volcano. Lenders and investors\u00a0are starting to get nervous,\u00a0which could\u00a0jeopardize planned\u00a0funding. We have written before about the risk that\u00a0current\u00a0power and data center\u00a0infrastructure can\u2019t support\u00a0the continued exponential development […]<\/p>\n","protected":false},"author":3,"featured_media":141671,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"","_et_pb_old_content":"","_et_gb_content_width":"","_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[16],"tags":[],"class_list":["post-141746","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-above_the_law"],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/xira.com\/p\/wp-content\/uploads\/2026\/01\/money-technology-intellectual-property-IP-litigation-bonus-600x392-u7xkLL.jpg?fit=600%2C392&ssl=1","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts\/141746","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/comments?post=141746"}],"version-history":[{"count":0,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/posts\/141746\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/media\/141671"}],"wp:attachment":[{"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/media?parent=141746"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/categories?post=141746"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/xira.com\/p\/wp-json\/wp\/v2\/tags?post=141746"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}
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