The return of Donald Trump to the White House has reignited global market volatility. From aggressive import tariffs to unpredictable policy shifts, his second-term leadership has caused unease across multiple industries. However, in the midst of this global disruption, one sector has not only survived, but thrived: AI data infrastructure.

As governments and businesses adapt to new uncertainties, the demand for robust data infrastructure capable of supporting AI-powered transformation is accelerating. Large tech players are acquiring data integration and analytics firms at record prices, pushing the sector into a spotlight of strategic importance.

Meta and Salesforce Lead Strategic Acquisitions

One of the biggest moves in the data infrastructure space came in June 2025, when Meta announced its acquisition of a 49% stake in Scale AI for a staggering $14.8 billion. Scale AI specializes in data labeling services, which are essential for training generative AI models. The move signals Meta’s increasing commitment to owning not just the algorithms but also the datasets that power them.

Meanwhile, Salesforce followed suit by revealing plans to acquire Informatica, a global leader in data integration and cloud data management, for $8 billion. Informatica will help Salesforce unify both internal and external data sources, feeding their proprietary Einstein AI engine with deeper, cleaner insights.

These deals indicate a growing recognition: "AI without data is like life without oxygen," said Brian Marshall, global head of software investment banking at Citi, as reported by Reuters. The synergy between AI and data infrastructure is no longer optional, it’s existential.

Data Infrastructure Firms Are the New Hot Targets

According to a Dealogic report, merger and acquisition (M&A) activity in 2025 has reached $421 billion during the first five months alone, surprisingly strong considering the overall slowdown in global economic confidence. What’s even more notable is that three-quarters of these deals are centered on AI software companies, with a significant portion focused on data infrastructure players.

Industry experts believe firms like Confluent, Collibra, Sigma Computing, Matillion, Dataiku, Fivetran, Boomi, and Qlik are the next potential targets for acquisition. These companies specialize in different aspects of the data stack—from cloud data pipeline management to enterprise integration and analytics.

Florian Douetteau, CEO of Dataiku, explains it succinctly:

"Data silos have long hindered enterprise transformation efforts. With AI deployment now critical, improving our data architecture isn’t just important, it’s existential."

His comments reflect a broader industry sentiment that clean, well-integrated data is the fuel that will determine the future success of any AI initiative.

Why AI Data Infrastructure Remains Resilient in a Trump-Led World

Trump’s second-term policy agenda includes increased tariffs on Chinese imports, corporate tax reforms, and renewed pressure on American companies to repatriate manufacturing and jobs. While these strategies have created hurdles for traditional industries like automotive, manufacturing, and retail, the tech sector—particularly in AI and data—has remained largely insulated.

This is for a few key reasons:

• AI is mission-critical: In sectors like finance, healthcare, and logistics, AI tools are being deeply embedded into operations. These tools require real-time access to accurate and high-volume data. Companies simply can’t afford disruptions in their AI pipelines.
• Cloud-native by design: Most data infrastructure providers operate in the cloud, making them agile, global, and resilient to physical or geographic limitations.
• Cross-sector demand: Whether it's e-commerce personalization, predictive maintenance in factories, or fraud detection in banking, data infrastructure has become a non-negotiable asset.

Moreover, the shift to sovereign AI,

localized AI systems that comply with national regulations—has only added more complexity, making data infrastructure even more vital. Organizations must manage data across jurisdictions while adhering to compliance, privacy, and latency requirements.

Strategic Implications for Investors and Policymakers

The implications of this trend are far-reaching. For investors, AI data infrastructure is becoming the new frontier of “safe haven” assets in the tech space. Unlike consumer apps or hardware, these platforms offer B2B value, recurring revenue models, and high switching costs—traits that are especially attractive during market volatility.

Governments and regulators, on the other hand, face a pressing need to update their frameworks. With acquisitions happening fast, there’s a risk of data monopolies forming. Entities like Meta and Salesforce will not only control AI platforms but also the lifeblood data streams that feed them. Policymakers must strike a delicate balance between encouraging innovation and preventing over-consolidation.

The Road Ahead: From Data Chaos to Clarity

The path forward for enterprises is clear—invest in data infrastructure or risk falling behind. That’s why data companies are no longer seen as auxiliary tech providers but as core strategic assets. Whether through acquisition or in-house development, companies are racing to build end-to-end data pipelines that support scalable, responsible, and explainable AI.

Even in a volatile global political climate, the AI data infrastructure sector remains an island of stability, innovation, and growth. It’s the silent enabler behind AI’s promise, powering the next wave of digital transformation—even when the rest of the world is in flux.