I think we'll see under Trump a lot more mid-market M&A. If I were to, you know, let's call it under $100 billion, $100 billion acquisition would be fine with me. Under 100.View on YouTube
Donald Trump did win the 2024 U.S. presidential election and began serving a second (non‑consecutive) term on January 20, 2025, so the conditional part of the prediction about his returning to office has been met.
However, the substance of the prediction concerns whether his second administration “will permit substantially more mid‑market M&A” in tech (roughly under $100 billion) than under Biden. As of late 2025, the evidence is mixed and still very early:
- The Trump DOJ and FTC have kept the 2023 Biden‑era merger guidelines rather than explicitly rolling them back, signaling continuity in formal merger review standards. (cnbc.com)
- Enforcement against significant tech and tech‑adjacent deals has continued: DOJ sued to block Hewlett Packard Enterprise’s $14 billion acquisition of Juniper Networks and the FTC sued to block GTCR’s $627 million acquisition of Surmodics, and DOJ reaffirmed a Biden‑era push to break up Google; major antitrust litigation against Meta is also ongoing. (mondaq.com)
- At the same time, some commentary and data suggest overall M&A activity (across sectors) has picked up and that enforcement is easing somewhat compared with Biden’s term, with fewer merger challenges so far and more willingness to settle or allow deals with remedies. (wsj.com)
But Trump’s second term is less than a year old, and available analyses focus on broad M&A or individual high‑profile cases, not on a robust, quantitative comparison of mid‑market tech deals allowed versus those during the full four years of the Biden administration. Given the short time window and the mixed, still‑evolving enforcement picture, there is not enough evidence yet to say that U.S. antitrust policy under Trump has clearly permitted “substantially more” sub‑$100B tech M&A than under Biden.
Because the relevant policy outcomes over the full 2025–2029 term are still unfolding and the comparative data are incomplete, the prediction is best classified as inconclusive (too early to tell) rather than clearly right or wrong.