| | | As the second Trump administration prepares to move on Washington, some investment analysts are predicting a more permissive M&A market, deregulation as a catalyst for growth and fiscal policies that stimulate economic activity. And they see AI as catalyst in the shift. The effect could be dramatic, since the entire, U.S.-based tech startup ecosystem faces numerous headwinds at present. Not least is “an already crowded $1 trillion backlog of non-AI unicorns that are primed for exits, due to investors and traditional acquirers narrowing focus on AI.” The analysts behind the observations work for HSBC, the global banking giant headquartered in London. In a report released last week, the company offers some intriguing observations for market watchers interested in venture capital (VC) trends and forecasts. Here are 10. 1. U.S. venture investment in AI companies is nearing the scale of capital allocated to the rest of the VC market. ‘This trend has accelerated in recent years, with a step change in 2023, catalyzed by early foundational model breakthroughs, fundamentally shifting investment theses.’
2. Despite the nascency of the technology, a substantial portion of AI funding is concentrated in a small number of leading firms. ‘As of 2024, just 20 AI companies have each raised $2B or more, underscoring the high-stakes race to invest heavily at the front end of this next innovation wave.’
3. Sectors with ample unstructured data and limited downside to experimentation have seen relatively rapid climbs for AI startups. ‘Verticals with highly structured data (fintech, ecommerce) or those with high consequences for inaccuracy (healthcare, life sciences) have seen slower uptake in AI deals.’
4. Industries with significant data and high impact use cases (cybersecurity, cloud tech) have seen early AI adoption. ‘They’ve also seen a higher proportion of the first wave of AI startups maturing into later stage venture investment opportunities.’
5. An AI ‘supercycle’ holds the promise of reigniting labor efficiency gains from 2010’s lows (1.5%) to historical norms (~2.7%). ‘This stands to unleash $10T of additional GDP growth over the next decade.’
6. The transition to AI companies in 2023–24 highlights the shift in investment priorities.‘AI is now poised to lead the next wave of innovation and value creation in the venture capital ecosystem.’
7. The emphasis on AI as a growth driver underscores a growing misalignment between the broader unicorn backlog and evolving market demand. ‘The majority of the backlog is composed of non-AI companies. This cohort—which is worth nearly $1T—faces mounting risks of valuation markdowns as investor attention shifts toward AI companies.’
8. The leading technology companies have shifted strategies guiding their approach to external innovation.‘This comes amid increased regulatory scrutiny, the changing venture investment conditions following the 2021 boom and the rise of AI as a strategic core.’
9. The cash-rich ‘magnificent 7’—Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia and Tesla—are expanding investment portfolios with a concentrated focus on AI. ‘This accounts for more than half of their venture investments since 2022.’
10. Leveraging tremendous growth in free cash flows from legacy businesses, the Mag7 are focused on building out core capabilities through R&D spend—now totaling more than all dollars invested in U.S. startups. ‘Beyond spending today for internal innovation, the Mag7 are investing substantial capital expenditure on infrastructure for the next decade in AI.’
The authors add that, while VC investing has plateaued over the past three years or so, the largest technology companies continue to increase their collective R&D efforts as they “race to define the next era of technological breakthroughs in AI.” Download the full report from here. |
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| | | Buzzworthy developments of the past few days. - Who is Sriram Krishnan, and why is he headed to the White House? He’s a combination engineer, entrepreneur and investor who lately has been working as a general partner at the venture capital firm Andreessen Horowitz. And he’s going to Washington because President-elect Trump just named him senior policy advisor for AI. Announcing the appointment on social media, Trump says Krishnan will work in various capacities to help ensure continued American leadership in AI. Meanwhile Krishnan will likely promote open-source mechanisms for websites and social-media platforms to “exchange value” with AI assistants. That prediction is based on an op-ed he published in the New York Times in 2023. “Some industry experts believe the answers [to data hoarding] are in legal action and older sites forming content alliances,” he noted at the time. “As a technologist, my hope is that the answers lie in code rather than lawyers and that we see creative technology solutions to help keep the internet open.” The Hill has more on the tech team Trump is assembling under AI & crypto czar David Sacks. CIO has more on Krishnan.
- Hospitals really ought to step up their game on advanced analytics and AI investment in 2025. That’s the considered opinion of analysts at Kaufman Hall under its new parent company, Vizient. As provider organizations are famously data-rich and information-poor, AI and digital analytics toolkits “can reveal important interconnections,” explains Kaufman Hall senior VP Erik Swanson. “They are a sorting mechanism to determine what is most important to focus on, which you can then use to create objectives and action plans around key performance indicators.” Vizient/Kaufman Hall expounds on this and other points in a 2025 trends report released in December.
- Calls are increasing to monitor AI medical devices throughout their life cycles. But that kind of attention doesn’t come cheap. It requires continuously retraining not only the algorithms but also the humans who are responsible for them. “You need people, and more machines, to make sure the new tools don’t mess up,” KFF points out in an article picked up by CBS News. “Everybody thinks AI will help us with our access and capacity and improve care and so on,” says Nigam Shah, chief data scientist at Stanford Health Care. “All of that is nice and good, but if it increases the cost of care by 20%, is that viable?”
- Relatedly, the older a large language models gets, the more likely it is to develop—no kidding—dementia. It looks enough like actual senility, anyway, for academic researchers in Israel to be tagging it as such. Evaluating several models with the Montreal Cognitive Assessment (MoCA) test, the team found that, with the exception of ChatGPT 4o, almost all LLMs “showed signs of mild cognitive impairment.” They go even further. “As in humans, age is a key determinant of cognitive decline,” the researchers report in The BMJ. “Older chatbots, like older patients, tend to perform worse on the MoCA test.”
- In fact, let’s go ahead and say generative AI is not ready for primetime in medtech. Or we can just hold our tongue while nodding in agreement with medtech founder and CEO Erez Kaminski of Ketryx. He comes right out and pronounces it. “While generative AI might eventually play a role in administrative functions or patient education, we’re not ready to deploy it in clinical or life-or-death scenarios in 2025,” Kaminski writes in Medical Product Outsourcing. “For now, the risks far outweigh the potential rewards. Simply put, we don’t know how to safely control generative AI in life-and-death situations—and won’t for some time.” Hear him out.
- That’s not to say GenAI is DOA all across healthcare. After all, successful use cases are really not hard to find. A key thread running through all of them is the use of AI as an assistant for humans who oversee it—not as a know-it-all who might be able to do it all. “As long as organizations can keep that idea in mind as they implement AI, they will be in position to succeed during this era in which healthcare is being transformed by AI,” writes Tim Wetherill, MD, chief clinical officer at Machinify. His short list of scenarios in which AI should not be used, published by Unite.AI, includes cases that involve denying claims and care, relying on past decisions, building on legacy systems and leaning on old data.
- Nurses aren’t going to like this. What would be Robert F. Kennedy Jr.’s view of healthcare AI should Congress approve his nomination as HHS secretary? Fierce Healthcare put the question to Paul Mango, who served as HHS deputy chief of staff during the first Trump administration. Suggesting Kennedy would probably consult with DOGE leaders Musk and Ramaswamy, Mango wonders aloud: “What if we could use technology to help monitor patients differently than the way nurses did it 20 years ago, and we only needed half the number of nurses?” Read the whole thing.
- Recent research in the news:
- Funding news of note:
- From AIin.Healthcare’s news partners:
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