Our 2025 Tech Trends report provides a concrete roadmap for corporate leaders to navigate some of the most important technology shifts in the year ahead.

We include specific recommendations for action so that business leaders can get ahead of the next wave of value creation.

Here is a selection of key findings from the report:

• AI agents are given money to spend: AI agents’ utility is limited until they can make transactions seamlessly. A small group of tech players is building new infrastructure to make that happen.
• The future data center arrives: With data center power usage expected to more than double by 2026, big tech companies are morphing into energy innovators to support AI workloads. There’s a huge opportunity in improving data centers’ energy efficiency.
• Investment floodgates open for RNA therapeutics: RNA therapeutics developers are pioneering new ways to treat traditionally “undruggable” diseases, with a growing focus on neurodegenerative disorders like Alzheimer’s and Huntington’s diseases.
• AI M&A fuels the next wave of corporate strategy: AI’s share of corporate tech M&A has doubled since 2020. Tech incumbents like Nvidia, Salesforce, and Snowflake, as well as consultancies like Accenture, are rapidly acquiring AI startups to tap into enterprise demand. 
• Disease management enters a new phase with AI: AI is improving care delivery across 3 key areas of disease management: precise symptom evaluation; testing/screening for earlier disease detection (including before symptoms even appear); and finding at-risk individuals in datasets of entire patient populations. 
• Retail’s personalization imperative: Generative AI is unlocking 1:1 experiences across commerce touchpoints, with leaders like Target seeing a corresponding 3x boost in conversation rates. Personalization will become omnipresent in retailers’ offerings.
• And much more

Methodology

Our analysis relies on a wide range of CB Insights datasets, including financing and acquisition data, valuations, founding team and key people data, earnings transcripts, and more. We also leverage CB Insights’ proprietary scoring algorithms to measure business health (Mosaic) and maturity (Commercial Maturity), as well as the likelihood of acquisition (M&A Probability score). Throughout the report, we provide CB Insights customers with jumping-off points to dig deeper into the data behind the report.

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This spending is creating opportunities for growth across the AI data center value chain.

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The space is already seeing a steady stream of M&A activity, as established players seek to quickly acquire novel capabilities and fill in gaps in their AI talent.

But amid the frenzy, which specific genAI markets are most primed for exits — and what should corporate strategy and M&A teams be doing about it?

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Nvidia has used its experience developing graphics processing units (GPUs) — which were originally developed for applications like gaming but turned out to be rather good at AI tasks — to become a dominant force in AI infrastructure and applications. 

But a host of established companies and startups are investing heavily to capture a share of the growing AI computing market. This includes building new types of chips specifically for training and running AI models, evolving traditional processors like CPUs and GPUs to better support AI workloads, and exploring novel information processing technologies such as quantum and neuromorphic computing. 

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To stay on top, OpenAI has raised billions of dollars in funding and ramped up its hiring into the thousands of employees.

It has also acquired 3 startups in the last year to add new enterprise tech capabilities and talent, as noted in the Acquisition Insights on OpenAI’s CB Insights profile. 

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Prefer to listen in? Check out our discussion of the report here: 

An empowered digital workforce would reshape industries as we know them. The implications would be enormous, changing how companies hire and scale, as well as what they can achieve with a small headcount. 

That future isn’t too far off. 

The idea of autonomous AI agents — LLM-powered bots that can independently reason and execute tasks — caught on like wildfire in 2023, marking an important evolution beyond chatbots and copilots. 

OpenAI CEO Sam Altman has described agents as “AI’s killer function” as recently as May 2024.  

While much of the tech remains limited in its ability to execute tasks reliably, use cases are gaining traction in horizontal enterprise applications like customer support, sales, and engineering.

We mined CB Insights startup, financing, business model, and buyer interview data to map the evolving landscape and analyze its future. 

In the 28-page report, we cover: 

• The state of AI agents: Investment is surging to companies in the space, but limitations — most notably, agent reliability — remain. 
• Leading horizontal applications and impacts: The landscape of VC-backed agent startups is dominated by a focus on horizontal applications — across sales, customer support, and other enterprise and general productivity workflows.
• Emerging industry applications and opportunities: While few agentic companies focus on single industries, companies are emerging to target workflows across financial services, industrials, and more. 

Download the full report to get all of the data and analysis.

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In the last 2 years, it has backed more than 20 AI startups — mostly via its OpenAI Startup Fund (which has LPs including Microsoft and other OpenAI investors) — many of which are building on OpenAI’s own infrastructure. The company itself also doles out occasional grants and has acquired 3 startups in the last year.

OpenAI’s recent investments point to potential growth opportunities for the firm, especially as it faces pressure to earn its eye-watering $80B valuation and stay ahead of competitors in the fast-moving generative AI market. 

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While Nvidia initially developed its graphics processing units (GPUs) for gaming, these chips turned out to be ideal for powering AI tasks. Now, the company is focusing its efforts on providing the computing hardware — notably its A100 and H100 GPUs — and the software infrastructure required for developing generative AI applications.

Amid the generative AI rush, Nvidia has grown rapidly. In fact, it recently surpassed Microsoft and Apple to become the world’s most valuable company. To bolster its leadership position and keep ahead of AI computing competitors like AMD and Intel, Nvidia has forged relationships with companies across the AI landscape.

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Microsoft’s market cap is hovering at all-time highs as investors have gotten behind its embrace of the technology. Meanwhile, Nvidia joined the club after cruising past the $1T and $2T market cap benchmarks in less than a year on the back of demand for its high-end AI chips. 

Where big tech is putting its money — including investments and acquisitions — provides a window into each player’s strategy. The number of AI deals backed by the group increased 57% in 2023 compared to 2022. Notably, Meta and Apple didn’t invest in any AI startups in 2023, though Meta has been active in developing its own open-source AI models and Apple acquired an AI video compression startup last year.

Below, we map out every AI company backed by big tech and their strategic venture arms in 2023 with key takeaways below.

CB Insights customers can use this search to stay updated on every big tech AI investment, including 2024 deals. 

Key takeaways

1) Big tech continues to pile in on AI infrastructure, nabbing stakes in the next generation of AI startups.

As companies rush to harness AI’s potential, big tech wants to put itself right at the heart of AI value chains.

Some of the largest AI rounds backed by the group in 2023 went to leading foundation models and other development platforms: OpenAI ($10B corporate minority from Microsoft), Anthropic ($2.6B in funding over multiple rounds backed by Google and Amazon), and Databricks ($500M Series I backed by Nvidia’s NVentures with follow-on participation from AWS and Microsoft). 

2) Rivalries in cloud computing drive activity, while some startups bring in multiple big tech backers to remain neutral.

Due to the capital-intensive nature of AI development, startups are linking up with big tech companies like Google, Microsoft, Amazon, and Nvidia to access their cloud infrastructure, chips, and dollars.

In turn, big tech companies are fueling their rival cloud computing and chip businesses.

3) Healthcare and industrials lead big tech’s vertical AI investments.

Nvidia backed 8 AI startups in healthcare & life sciences in 2023, with 7 of these focusing on AI drug discovery, as the chipmaker doubles down on the sector.

Applications in materials development, manufacturing, and warehousing are also drawing the attention of big tech as the sector races to automate operations.

For example, the Amazon Industrial Innovation Fund invested in AI-powered robotics safety startup Veo Robotics in April 2023. Meanwhile, just last month, Microsoft’s M12 and NVentures backed humanoid robotics startup Figure’s $675M Series B. 

4) An emerging focus area is AI companions and agents.

Companies in this category like Inflection are working to make interacting with computers as conversational as it is to talk to people.

A number of companies backed by big tech in 2023, like Adept and Imbue, are building “autonomous agents” — LLM-powered bots that can independently reason and execute tasks.

In this vein, in January 2024, the Amazon Alexa Fund backed a round to AI agent startup MultiOn.

5) Nvidia bursts onto the scene.

Overall, Nvidia has ramped up its activity more significantly — from backing 5 AI startups in 2022 to 32 in 2023 — than any other tech giant as it embeds itself deeper in the generative AI ecosystem.

Apple and Meta, which historically have made fewer investments compared with other giants and do not have venture arms, did not publicly disclose any AI startup investments in 2023. 

Looking ahead

Large acquisitions have been key for big tech to bring in new revenue sources as well as launch new product lines.

But with regulatory pressure hobbling big tech’s acquisition activity, expect these players to lean more heavily on AI partnerships and investments, as well as product launches, in the coming months. 

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In the past 2 years, it has established key partnerships with tech giants like Microsoft, Nvidia, and Google to give its clients access to custom generative AI capabilities, AI toolkits, and more.

Accenture also recently announced it will invest $3B in AI by 2026, including doubling its AI talent to 80,000 employees. As part of this investment, the consulting giant announced the launch of a network of generative AI studios to help its clients deploy the tech.

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The divide is playing out among big tech companies vying to gain an edge in the great AI race.

Meta launched its open-source large language model (LLM), Llama 2, earlier this year, while Google and OpenAI have taken closed approaches so far.

The private LLM developer market is also split.

Proponents of open-source AI — where source code is available for public use — highlight advantages such as:

• Increased model flexibility & customizability
• Accelerated innovation that comes with a large developer community
• Transparency into AI models, data, and code vulnerabilities

But opponents of open-source AI fear it will be misused to fuel cyberattacks, AI-generated hate speech, and more — and highlight closed-source LLMs’ performance edge, additional development resources from deep-pocketed backers, and greater support from the companies that developed them.

While developers debate the philosophy of open vs. closed, early LLM adopters appear to be more interested in the day-to-day practicalities of what companies are offering.

For this buyer we spoke with, OpenAI’s ease of use stands out. But open-source models are attractive for their potential cost-savings.

OpenAI

OpenAI’s developer API and the developer experience is definitely the best. It’s really managed, super clean APIs, well documented, and has the most integrations. There was a big push toward using open-source models and then fine tuning them with your own data. That’s still a big thing. We’re actually evaluating that for some of the public data set stuff because it’s a lot cheaper, especially if you add in more huge amounts of data versus a giant OpenAI model. — Partner, Early-stage VC firm

Read the full transcript here.

This OpenAI customer, who is also considering Hugging Face and Meta’s Llama 2, indicates that open-source may have better ROI, even if performance is weaker.

OpenAI

Meta’s invention… it may be cheaper than the OpenAI [model] because it’s open source. Then we believe the performance of the Hugging Face and also the Llama 2 is also comparable to the OpenAI [model]. Maybe just a little bit weaker than that, but maybe the overall…ROI is quite a good deal. — Cloud, Data & AI Lead at Fortune 500 company

Read the full transcript here.

The open-source AI development market map

Beyond open-source foundation models, a number of vendors have emerged over the years to offer open-source tools for different parts of the AI development process.

For example, in LLM application development, Rasa provides an open-source conversational AI framework. 

Rasa Technologies

We considered several other vendors in this space before choosing Rasa Technologies, such as IBM and Watson, LivePerson, Eva from Amplify, and Sprinklr’s conversational bot solution…We leveraged Rasa Technologies as the natural language understanding (NLU) on the back end…The pros for us of using Rasa Technologies were the price model and our ability to grow with the product, the quality we got for it, and the support. We were able to own our own data and our own environment and set things up how we wanted it. — Senior Manager, Fortune Global 500 company

Read the full transcript here.

Dig in with the full map. 

Our AI research director recently dove into the landscape in our Future of Large Language Models briefing  — download the recording for free here. 

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But OpenAI is only one of the players building the foundational layers for generative AI applications and garnering heavy investor interest. For example, in May 2023, Cohere raised a $270M Series C round while Anthropic secured a $450M Series C round with backing from Google and Salesforce Ventures, among others.

Using CB Insights data, we explore key trends in the LLM developer landscape, including:

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The startup reached a $1B valuation after raising $150M of Series D funding in March 2022. However, the company is reportedly now looking to sell itself for significantly less. Toughening market conditions have put pressure on high-valued unicorns, forcing valuations to contract and driving investors away from late-stage rounds. 

Rapid’s troubles could be a sign of things to come for other highly-valued companies in the API management space.

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Copilots are designed to work alongside humans, automating tedious tasks or providing suggestions to allow users to finish things up more quickly.

There are generative AI-powered copilots emerging for a host of applications, but one of the most prominent is software development. Since 2021, Microsoft-owned GitHub has offered a copilot for coders that taps into OpenAI‘s models, while Amazon recently launched a competing service called CodeWhisperer. But the tech giants face a growing slate of rivals vying for the attention of software developers.

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Microsoft is betting that generative AI could tip the competitive scales in its favor for decades to come.

The tech giant has poured billions into ChatGPT maker OpenAI to become one of its largest stakeholders, while also providing computing infrastructure to power the startup’s resource-hungry operations.

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Get up to speed with our explainer video — and read on for the full report.

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