LLMs Are No Longer AI’s Hottest Commodity. Here’s What Acquisitions Are Telling Investors About Which Companies Are In Highest Demand

When Meta (META) announced a $14.3 billion investment for a 49% stake in Scale AI in mid-2025, it represented one of the most expensive private deals on record, but it also drew immediate skepticism. Critics deemed it a costly misstep, pointing to falling valuations and reports of low internal morale at the company. 

However, Meta wasn’t buying an AI model or LLM. It was betting on a crucial provider of high-quality training data, a resource that’s becoming scarcer than the models themselves. A year on, Zuckerberg’s play for Scale AI looks more deliberate: as access to LLMs becomes commoditized, value is migrating towards the platforms and data sitting underneath them. 

Acquisitions of AI companies today are less about finding profitable deals that will generate a solid return on investment, and more about highly strategic long bets centered around the future of the industry. For Meta, that meant data and for the broader market, it has meant infrastructure, chips and enterprise platforms. 

Take Google's (GOOGL) $32 billion purchase of Wiz, IBM's (IBM) $27.8 billion data-stack acquisition, or Salesforce's (CRM) $3.6 billion purchase of Fin, to name a few; 2025, in fact, broke historic records for consolidation activity in the AI and data space, amounting to at least $157 billion in disclosed value through 33 major acquisitions. 

However, this year’s dealmaking is expected to move beyond pure tech and into industry verticals more broadly. Here’s what investors should expect. 

AI takeovers accelerate company roadmaps 

While the AI and data dealmaking broke records during 2025, the pattern continues into 2026. SpaceX's (SPCX) announcement this month that it will acquire AI coding startup Cursor for $60 billion in an all-stock deal is the latest signal that the largest players are still buying aggressively. 

In 2026, we expect to see even further consolidation of AI companies, with organizations leveraging these firms to accelerate roadmaps and more rapidly bring their products to broader customer bases. 

New York-based proptech GetCovered, for one, acquired Revyse in June 2026, an AI-powered vendor management platform, in a major development for the multifamily markets in the U.S. Although GetCovered already offers a comprehensive risk platform, the deal immediately expanded the company’s capabilities for compliance solutions to compound the value that AI is delivering for this vertical. 

“Through a new focus on M&A, we can quickly and strategically acquire complementary technologies that expand compliance, data, and insurance distribution capabilities and quickly launch new insurance products in response to market demand,” said Ryan Solomon, Chief Strategy Officer at GetCovered. 

“The next phase of product acceleration will also see us invest more heavily in data-driven risk analytics and scale integrations with insurers, MGAs and property management platforms.” 

Meanwhile in biotech, AI-led acquisition strategies are also gaining momentum. In January, AstraZeneca acquired Modella AI, a Boston oncology AI firm the biotech giant had been working with for less than a year, converting what began as a July 2025 partnership into a full acquisition in six months and folding both the team and the technology into its oncology R&D organization. 

While it represents another prime example of how industry-leading companies position their strategies through pointed acquisitions, it’s also a wider bet on intelligence. “They are paying for the layer beneath the trial, the workflow intelligence that decides how a program is run, and they are treating that layer as durable, defensible IP,” Sidhant Khadanga, Partner at Sonata Software. 

Investors looking for exposure to this trend may want to watch industry leaders here, including SoundHound AI (SOUN) and C3.ai (AI). In both publicly and privately traded markets, we shouldn’t expect this activity to slow down – quite the opposite. 

Access to talent, specialization and workflows 

Elsewhere, McKinsey expects AI-related M&A activity to have a significant influence on global competitiveness. In addition to the convergence of AI companies, the consulting firm predicts that 2026 is likely to see “more capability-driven acquisitions in enterprise software and services". 

In particular, IT and professional-service firms are acquiring specialized AI companies to accelerate their integration of genAI into workflows, customer service and knowledge management. Such is the case of AI operationalization firm Straive, and its acquisition of AI engineering firm NextGen Invent.

Said Namit Sureka, President at Straive, at the time of acquisition, “By bringing NextGen Invent’s forward-deployed engineers into the Straive fold, we will be accelerating our ability to land and seamlessly scale up to build, run, and transform our clients’ business priorities.” 

The transaction brings together complementary capabilities focused on enterprise transformation. But beyond a singular case, the move reflects a broader industry effort to help enterprises expand from isolated AI experiments toward scalable, production-grade deployments. 

Meanwhile, chipmaker Qualcomm (QCOM) is pursuing a similar talent-and-tech play, reportedly in exclusive talks to acquire Modular, a young company building software for AI infrastructure – a move aimed at strengthening its position in the fast-growing AI systems market.  

Regardless, while organizations become adept at testing AI use cases, many continue to face challenges when attempting to operationalize those solutions across large and complex business environments.

According to company executives, the shared objective is to help organizations move from  strategy discussions to real-world implementation. Yet, while many enterprises have established roadmaps, far fewer have successfully integrated AI into mission-critical workflows in ways that generate measurable business impact.

AI solutions providers linked to next phase of value creation 

AI firms building LLMs were once branded the hottest commodity in the technology industry. Today, the focus has shifted as industry heavyweights race to develop the Agentic AI systems expected to bring autonomous decision-making into the real world. 

This is where AI solutions and digital transformation providers are expected to play a critical role: as demand grows for organizations to deploy the technology at scale and generate tangible business value, companies with expertise to implement and operationalize AI solutions are likely to become increasingly important across industries.

Both established technology firms and leading AI model developers are increasingly targeting this segment as they seek greater control over how their technologies are deployed within enterprises. Like many of the industry's landmark acquisitions, these potential deals reflect a strategic effort to address one of AI's biggest challenges: turning technological breakthroughs into widespread enterprise adoption.

Although details remain limited, the value of AI services providers increasingly lies in their ability to combine deep expertise in emerging technologies such as Agentic AI with a proven track record of delivering successful digital transformation initiatives. According to Ness Digital Engineering Chief Growth Officer Mahesh Raja, “The real unlock will come from combining technology with execution capability. That includes access to the right engineering talent, clear operating models, and a practical roadmap to scale AI across the enterprise."

The investment case for AI execution 

For investors, this emerging layer of the AI ecosystem may offer some of the most compelling opportunities through the end of the decade. As enterprises move beyond experimentation, interest is likely to shift toward solutions that can bridge the gap between AI innovation and execution.

Several leaders are already positioning themselves at the center of this trend. Ibrahim Hasanov, for one, is helping shape the growing AI-powered sales automation market through MyUser, a platform designed to automate traditionally labor-intensive outbound sales functions such as prospect research, personalized outreach and scheduling. 

Meanwhile, ADvendio CEO Bernd Bube is advancing AI adoption across media operations, advertising sales workflows and campaign management, while investors such as ElevenX Capital's Anjli Jain have been increasingly identifying opportunities in industry verticals – including education – and backing companies like IvySchool.ai, which helps individuals build the skills needed for an AI-driven economy.

As the AI market matures, the next wave of value creation may not come from building larger models alone, but from the companies and leaders that make those models indispensable to everyday business operations. 

The ventures that successfully connect AI innovation with real-world execution could thus become some of the most sought-after investment opportunities in the years ahead.