Like all new technologies, artificial intelligence is following a predictable pattern. We’ve seen a dizzying parade of new tools emerge, massive investment in startups, soaring valuations and countless warnings that the industry is entering bubble territory. There are valid concerns that the AI bubble might be about to burst, as we continue to see niche startups emerge on a daily basis and the biggest players committing to investing trillions of dollars in infrastructure. Yet, AI is also maturing at lightning speed, and the prevailing trend now is one of accelerating consolidation. The most established players aren’t waiting around for the dust to settle, but instead putting a stake in the ground as they strive to offer real business value to increasingly skeptical buyers. Acquisitions are a natural part of that evolution. Recent activity supports this idea, with Meta Platforms (META) snapping up a sizable stake in ScaleAI, the French model maker Mistral AI buying cloud infrastructure firm Koyeb, Apple (AAPL) snapping up Q.ai and ServiceNow’s (NOW) recent gambit, buying the enterprise data analytics startup Pyramid Analytics. And then there’s the mammoth in the room – SpaceX merging with xAI as part of Elon Musk’s grand plan to put AI data centers into orbit. Startups are being gobbled up left, right and center at a time when the initial enthusiasm for AI is beginning to mature. Customers, especially businesses, aren’t buying into the hype anymore. They want to see real, measurable value from their AI investments, but that has so far proven elusive for many. Will these new M&A moves be the key to unlocking that value?Will Businesses Become More Productive?Plenty of data points suggest that AI’s promised impact on productivity has not yet materialized. A new survey of 6,000 business executives by the National Bureau of Economic Research found that the vast majority have seen little value from AI so far. Around two-thirds of respondents said they’re already using AI in their business operations, but so far, that usage amounts to less than two hours per week. Even more telling, 90% of executives said AI has not had any impact on productivity in the last three years. That’s troublesome, because most of those executives are spending bucketfulls of cash on AI. In another survey from Dataiku, 71% of Chief Information Officers admitted that they’re facing real pressure now to start showing a concrete return on those AI investments. And they’re running out of time. The pressure is on, not only for buyers, but also the AI companies themselves. After all, they’re spending billions of dollars on the data center infrastructure required to run their AI products, and if they can’t provide value, they won’t see the revenue to pay for it. In response, many AI firms are turning to acquisitions to try and refine their offerings and start showing benefits. AI is now driving the majority of mergers and acquisitions in the tech world. SOMO’s Big Tech M&A tracker shows that 15 of the 25 acquisitions announced by “major tech companies” in the last year involved AI firms, including chipmakers, data center infrastructure providers, software development shops and big data firms. It’s a clear signal the biggest players are scrambling to deliver on AI’s potential. Big Tech’s AI Acqui-accelerationThe wave of AI acquisitions is all about the bigger players searching for ways to accelerate AI automation. A case in point is ServiceNow’s recent announcement that the company is acquiring BI software company Pyramid Analytics. Gaurav Rewari, ServiceNow’s senior vice president and general manager of data and analytics products, said the startup’s technology will enable it to embed intelligence directly into business workflows and "turn insights into action.” Pyramid’s generative BI tech can help ServiceNow’s customers to decide which data inputs matter, how they’re interpreted and what recommendations should follow. The AI will then be able to choose the right system to execute that recommended action, and define how the outcomes dictate what follows. In this scenario, Pyramid provides the intelligence and insights, while ServiceNow will integrate these into workflows and use its AI agents to automate the actions. Avi Perez, co-founder and CTO of Pyramid, believes it’s a killer use case for AI-driven business intelligence. ServiceNow’s users will no longer need to interpret data-based signals themselves, and can instead move directly to prescriptive action. “What is the ultimate use case for AI and generative AI?” Perez asked. “It’s the idea that I don’t even need to see a bar chart. I don’t need to see the data. You just tell me what I need to do tomorrow."Meta’s deal to acquire a stake in ScaleAI was originally seen as an acqui-hire of sorts, with the social media giant recruiting its founder Alexandr Wang to head up its new Superintelligence unit. But Meta didn’t pay $14.8 billion for talent alone. ScaleAI will accelerate Meta’s AI ambitions by providing it with the massive volumes of valuable training data needed to develop its next-generation models, said Sky Sharma, a consultant at Innovation Vista. He emphasized the importance of data quality in AI training. "Scale AI’s strength lies in its ability to provide "clean" and accurately labeled data, which is the lifeblood of training robust LLMs,” he wrote. Armed with a consistent supply of high-quality data that’s annotated by real, human experts, Meta has secured the foundation it needs to develop more robust and reliable models that will power the AI features in Facebook, Instagram, WhatsApp and in VR and metaverse environments for years to come. AI model makers are at it too. Europe’s leading LLM company Mistral AI recently acquired the serverless cloud infrastructure startup Koyeb, saying it intends to accelerate the build out of its dedicated cloud platform, Mistral Compute. With the deal, Mistral is transforming into a full-stack AI platform, and will gain precise control over how its models are deployed and scaled. This should provide significant benefits to Mistral’s customers. Koyeb has developed high-performance cloud infrastructure with sub-200 millisecond startup times, which will have a direct impact on Mistral’s latency. Moreover, it can now offer businesses serverless environments, where GPUs will scale up and down automatically, lowering the cost of “bursty” AI applications. Prabhu Ram of Cybermedia Research said Koyeb will enhance Mistral’s appeal to businesses. “It gets a step-up in its progress towards full-stack capabilities,” he told InfoWorld. “The Koyeb acquisition bolsters Mistral Compute, enabling better on-premises deployments, GPU optimization and AI inference scaling.” History Repeats Because It Has ToThis wave of consolidation should not come as a surprise. Gartner said it would happen last year, pointing out that the supply of AI models and platforms has far outstripped demand. In such situations, consolidation is inevitable. In fact, it is a natural and predictable step in the evolution of almost every new technology, and we’ve witnessed it repeatedly in areas such as cloud computing, big data and networking. When a hot new tech first emerges, dozens of smaller players pop up, creating a fragmented market. Once things start maturing and people begin to understand what they need from the technology, the most successful players buy up the smaller fish to reinforce their competitive advantage. It’s a lifecycle that’s driven by a combination of economic pressure, the need for scale and ultimately, the demand for greater value. It ends with the dominance of a handful of players. History is merely repeating itself, asserted Gartner analyst Will Sommer. "While we see early signs of market correction and consolidation, product leaders should recognize this as a regular part of the product product life cycle, not a sign of inevitable economic crisis," he said. Consolidation in AI was bound to happen. The initial hype and buzz around what AI can do is rapidly giving way to the realization that it doesn’t always provide the desired benefits. AI companies are under pressure to deliver tangible business value, and the M&As will pick up pace as the bigger players race to meet that demand. This article was written by FM Contributors at www.financemagnates.com.