Despite geopolitical risk and economic uncertainty, M&A is surging because companies are executing on long-term (20-30 year) strategic repositioning plans conceived post-COVID. When capital markets open, even briefly, companies are quick to act on these dormant, high-conviction plans, ignoring near-term volatility.

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Because boards lack deep expertise in AI's seismic impact, they are pursuing scale-driven M&A. The goal is to accumulate diverse assets ('cards in a deck') to maintain flexibility and strategic options in an unpredictable, AI-driven future, rather than making specific bets on the technology itself.

While competitors retrench during recessions, Amphenol leverages its strong balance sheet to accelerate M&A. This counter-cyclical strategy allows it to acquire strategic assets at attractive valuations, ensuring it emerges from downturns with increased market share and strength.

Current M&A activity related to AI isn't targeting AI model creators. Instead, capital is flowing into consolidating the 'picks and shovels' of the AI ecosystem. This includes derivative plays like data centers, semiconductors, software, and even power suppliers, which are seen as more tangible long-term assets.

Recent antitrust lawsuits against Meta and Google resulted in minimal consequences ("nothing burgers"), signaling a more permissive regulatory environment. Combined with anticipated economic stimulus, this creates ideal conditions for a wave of large-scale M&A ($25B-$250B) among major tech companies in the coming year.

The term 'private equity' is now insufficient. The M&A market's capital base has expanded to include sovereign wealth funds and large, tech-generated family offices that invest directly or co-invest like traditional PE firms. This diversification creates a larger, more resilient pool of capital for deals.

Twenty years ago, globalization and open markets (geopolitical tailwinds) created new opportunities for businesses. Today, rising nationalism, trade barriers, and security concerns act as headwinds, creating obstacles and increasing the complexity of international operations.

Major tech companies view the AI race as a life-or-death struggle. This 'existential crisis' mindset explains their willingness to spend astronomical sums on infrastructure, prioritizing survival over short-term profitability. Their spending is a defensive moat-building exercise, not just a rational pursuit of new revenue.

The most lucrative exit for a startup is often not an IPO, but an M&A deal within an oligopolistic industry. When 3-4 major players exist, they can be forced into an irrational bidding war driven by the fear of a competitor acquiring the asset, leading to outcomes that are even better than going public.

For legacy companies in declining industries, a massive, 'bet the ranch' acquisition is not an offensive growth strategy but a defensive, existential one. The primary motivation is to gain scale and avoid becoming the smallest, most vulnerable player in a consolidating market, even if it requires stretching financially.

Assets like launch capabilities, energy access, or media influence may not generate strong cash flows but provide immense strategic leverage. In an era of competing power blocs, controlling these strategic assets is becoming more valuable than traditional financial metrics suggest, a shift that markets struggle to price.