Venture Capital and Enterprise Tech Trends for 2025: AI Adoption, Data Infrastructure, and Market Dynamics

What will this year bring in VC? We asked a few investors | TechCrunch

A new year brings with it hope for a better tomorrow -- kind of, at least. In the world of venture capital, nothing is quite predictable. The number of firms in the U.S. has taken a sharp dip as risk-averse institutional investors splash money on only the biggest names in Silicon Valley, as reported by the Financial Times. AI is the only category that seems to matter, and that doesn't look to be changing anytime soon. But the new year has just started, and perhaps so has the impetus for change. We spoke to some VCs to gather their predictions on the new year -- the good, the bad, and what might end up being the unexpected. Their responses have been edited and shortened for clarity. The good: As wealthy individuals lower their return expectations for fixed income and cash equivalents, they will look more aggressively to private markets for outsized returns. This channel is expected to invest over $7 trillion in private markets by 2033. In response to this expected influx of capital, we have seen large wealth and asset managers use venture capital as a differentiating strategy among their private market offerings. These institutions have positioned venture to be a strategy where they can offer access to the best deals while capturing a portion of the $7 trillion expected to be invested in private markets through net new flows. Fund managers will simultaneously partner with these institutions to gain access to a new set of LPs that create a new, consistent, and long-term capital stream for their funds. More good: We expect the AI field to start seeing consolidation, primarily through acquisition, in areas where AI can become a commodity, like large language models. The AI companies that will make it to be leaders in their field are opening new market segments and owning proprietary data. The good: The IPO market will fully reopen, and we'll see some big-name IPOs bring much-needed liquidity. That's a win for everyone. On the early-stage side, investment pacing will pick up, maybe not to 2021 levels, but certainly more than 2022-2024. It feels like 2025 will be a banner year for venture and hopefully the official start of the next bull run. The bad: 2025 will be a make-or-break year for AI startups selling to enterprises. A lot of AI startups have grown quickly but are still stuck in the "experimental" phase, living on innovation budgets instead of being part of core software spend. Many won't make the leap, leaving a number of startups on the chopping block as churn and slow growth take over. The good: The emergence of solo GPs and angel funds will drive increased investment into earlier-stage companies -- a much-needed evolution for the venture capital ecosystem. We'll see more specialized and well-defined investment approaches, with industry-specific, knowledgeable investors providing meaningful value to founders. This shift is not only beneficial for startups but is also likely to deliver better returns for investors. Capital allocation to diverse founding teams will continue to grow, particularly in sectors like sustainability and healthcare, where diverse perspectives can drive innovation and impact. The bad: Meaningful M&A or IPO activity is unlikely until late 2025 as market conditions remain challenging. Limited partners will remain hesitant to deploy capital, waiting for improved distribution to paid-in capital metrics before committing to new funds. The good: Long-awaited increased liquidity for LPs with an opening of the IPO and M&A markets. More funds and companies taking secondaries as well. A reset of expectations of the zombie companies that are profitable not going to have the outcomes the VCs on the cap table underwrote, selling at a more grounded price to private equity. Consolidation and roll-ups in oversaturated spaces (e.g., GLP-1s). The bad: Continued falling unicorns that have significant reset in valuations due to market resizing and growth expectations resetting. The good: IPO markets will reopen following the success of Service Titan, as will M&A activity for private companies. Finally realizing these gains will increase liquidity for the LPs behind many venture capital firms. This will lead to LPs committing to more new funds -- more venture funds than in years past. The bad: [LPs] may be more reluctant to commit to new fund managers after seeing a lot of undisciplined behavior in the last cycle. The unfortunate side effect is that some of the most innovative strategies will have a lot of trouble getting funded. What will stay: Dealmaking will remain favorable to investors with dry powder. Investors will continue to move away from looking at products using [the] "number of users" as a key consideration and move toward booked revenues, client pipeline, and costs as key considerations prior to investing. The pace of investing will also maintain this investor-friendly environment. We do not expect venture firms to return to the frenzied pace of investing experienced for the past couple of years but instead continue with a balanced approach. What will go: The outlook for IPO activity is moderately positive. Founder-renewed confidence in the public markets and comps coupled with dwindling cash runways and those high-valued companies that have survived the recent fundraising constraints, have right-sized their valuations to align more closely with the market. We believe that the consumer is also prime for investing in small-cap stocks, given the mega-cap technology stocks that have moved U.S. indexes into all-time highs and returned tremendous shareholder value. While there are still a number of companies whose valuations are not yet tracking to the market there are some, primarily in the tech space, that are ready for the public market. What will stay: Small teams scaling revenue. We're seeing teams of just one to three people hitting $2 million+ ARR using AI tools -- doing more with less and doing it better than ever. This kind of growth was unheard of before 2024 and highlights how much startups are automating internally with new software tools. The big question now is how these teams will scale and build strong organizations, but it's impressive to see such growth with such a lean setup. We'll also see a resurgence in investment around reskilling -- platforms addressing talent shortages in skilled trades, manufacturing, hospitality, healthcare, and other areas that software can't automate away. What will stay: AI is here to stay. The widespread deployment of AI in 2024 marked a significant shift, and I believe this momentum will only grow. While it offers immense opportunities -- such as enhancing decision-making, improving deal sourcing, and streamlining operations -- it also presents challenges. For instance, human intuition and experience remain vital, particularly when evaluating founding teams and their dynamics. This evolution will require LPs to think more critically about how they select managers and construct their portfolios. What will go: The spray-and-pray investment approach. I expect we'll see fewer deals but with greater diligence and meaningful value-add from investors. This trend, already evident in 2024, signals the end of the growth-at-all-costs mentality. Instead, investors will prioritize paths to profitability and sustainable business models, which will continue to be the hallmark of attractive opportunities. What will stay: [The] perceived short list of winners in the AI space will continue to command significant investor attention at premium valuations. [There will be a] continued trend of VC-backed companies shuttering as capital markets [become] more selective in terms of funding [and the] continued trend [of] VCs, especially seed stage, [being] unable to raise new funds due to rough performing 2020 or 2021 vintages. What will go: The last cycle was a deep shift to more investors backing enterprise SaaS companies and fewer backing consumer applications. I think this will start to reverse as AI creates more applications for consumers that just weren't possible a few years ago. Consumer tech will make a welcome comeback in 2025. We could see mergers or even closures of some big-name unicorns, many of which have been industry darlings for years. These companies have just enough cash to make it to 2025, but not enough growth to go any further. We're already seeing some consolidation, and this will likely accelerate into 2025. A significant climate-related disaster, geopolitical conflict, or economic shock has the potential to fundamentally reshape the startup and VC landscape. A surge in venture dollars looking at hard technology, as software becomes commoditized due to generative AI. Hard tech as defined by bio, tech, hardware, other forms of deep tech taking center stage. [There will also be] a significant increase in companies raising only a seed round and having a sub-$100 million exit in sub-three years of existence -- revealing a new math that could potentially work for founders and the VCs due to companies with distribution quickly acquiring top products that will complement their existing offering. Something unexpected is that OpenAI could convert to a for-profit entity just for Microsoft to be able to acquire it in the largest acquisition ever.

From AI agents to enterprise budgets, 20 VCs share their predictions on enterprise tech in 2025

While AI is lauded by some as the biggest technological breakthrough since the industrial revolution, enterprises -- arguably the tech's biggest potential customer base -- have been slow to adopt AI. While some investors predicted that 2024 would be the year we'd start to see more AI adoption by enterprises, that didn't play out as budgets remained constrained and AI tech often remained in the "experimental" category. Will that all start to change in 2025? Depends on who you ask. TechCrunch talked to 20 venture capitalists who back startups looking to sell to enterprises about their predictions for 2025. They told us what they anticipate regarding enterprise budgets, trends worth following, and what it will take to raise a Series A in 2025, among other things. Here's what they said. What enterprise-related trends will you be paying attention to the most in 2025? SC Moatti, managing partner, Mighty Capital: I'm really looking into this theme -- AI adoption hinges on better data. As enterprises transition from AI experiments to large-scale deployment, the demand for high-quality data intensifies. Aaron Jacobson, partner, NEA: Code agents for app development modernization are underhyped. Expect to see AI being used to re-platform mainframe apps to the cloud and upgrade older codebases. Molly Alter, partner, Northzone: A key focus of mine is on spaces that were historically untouchable by venture funds because their business models demanded high COGS or OpEx. We're seeing AI automate so much behind-the-scenes work that sectors like accounting services, or revenue cycle management, or white-glove legal services can now command software-like margins. Marell Evans, founder and general partner, Exceptional Capital: Understanding trends in enterprise sales cycles -- what is the duration certain organizations are trialing tools for before making decisions about internal adoption? In addition, understanding the different pricing models of AI [in relation to] traditional SaaS, consumption-based and/or outcome-based. Mike Hayes, managing director, Insight Partners: An unappreciated metric and something that I think will gain traction in 2025 is TTFV, or time-to-first-value. I see this as a proxy for ease-of-implementation, so faster TTFV solutions should have a bigger advantage going into [the] new year. What areas are you looking to invest in? Liran Grinberg, co-founder and managing partner, Team8: Enterprise resilience, whether in front of operational faults or malicious insider or outsider threats. The CrowdStrike software update incident demonstrated how fragile our digital world is, not only due to cyberattackers but also just mistakes. Jonathan Lehr, co-founder and general partner, Work-Bench: Data sovereignty as a service. Organizations are increasingly investing in data sovereignty solutions driven by regulatory requirements and geopolitical concerns. We are exploring startup opportunities that enable companies to maintain complete control over their data's location, storage, processing, and governance while ensuring compliance with local regulatory frameworks. Mark Rostick, vice president and senior managing director, Intel Capital: One area we're looking at is companies that focus on task-specific models. While the foundational models are well established, I find models that excel at specific functions particularly intriguing, especially when combined with agents built on top of them. In addition, we are closely monitoring the development of alternatives to transformers and any possible solutions to reduce the need for the huge amount of computing capacity now required to train LLMs and use them in production. Mike Hayes, managing director, Insight Partners: Enterprises have historically thought of technology as either driving revenue or reducing cost, but that is quickly changing in favor of technology that drives enterprise value while simultaneously reducing business friction. I look for solutions that solve unique, orthogonal challenges for enterprises -- areas where traditional solutions have fallen short; this includes vertical and persona-specific workflows reimagined with GenAI or agentic automation and security innovations that not only identify and alert, but also remediate. Jason Mendel, venture investor, Battery Ventures: A few interesting areas where I think AI can add significant value, and which I'm excited about, include observability / incident response, IT service management, demand generation and sales engagement, offensive security, software development, and the SOC workflow. Ed Sim, founder and general partner, Boldstart Ventures: We think in second order effects. So if we assume that in the future, meaning the next two to three years, we could live in a world where each of us has dozens or hundreds of agents doing work for us, we need to think about all of the infrastructure that needs to be built to support these new digital employees. Who's going to provide the security infra to provide access control? Who's going to manage these? Is there a platform to manage disparate agents and secure them? What about a runtime system for Claude's MCP, which feels like a dockerized, secure sandbox for agents to do work. What technologies, sectors, companies, etc., are you finding interesting that aren't AI? Liran Grinberg, co-founder and managing partner, Team8: Quantum computing is still promising. Cybersecurity isn't going anywhere as well, with attackers leveraging AI and an increased complexity in protecting our digital infrastructure. Nina Achadjian, partner, Index Ventures: We've seen a resurgence in fintech, SaaS, and e-commerce, which were hot sectors that saw a slowdown in the last couple of years. Beyond that, we expect cyber and gaming to continue to be interesting this year, with cyber accelerating further as the IPO market opens up and regulations and disclosure rules around security increase. Aaron Jacobson, partner, NEA: There is a ton of hype around securing AI, but the bigger opportunity is helping enterprises apply "Cybersecurity 101" at scale in a way that doesn't impede user productivity. Key areas of particular interest are enforcing least privilege access, maintaining a secure data posture, and preventing ransomware. I'm also excited to invest in technology that facilitates multi-cloud deployments for enterprises. Molly Alter, partner, Northzone: I'm really excited about companies addressing the public sector. The fiscal environment for government contracting is flush; total federal agency contracts reached $774 billion in 2023. Technology adoption and modernization are key to driving the efficiencies that the new administration is committing to, and there is a growing ecosystem of companies that are tackling this head-on. Andrew Ferguson, vice president, Databricks Ventures: We're spending a significant amount of time with our system integrator partner ecosystem. These companies are doing the hard work of helping enterprises take their data and AI strategies and turn them into real-world implementations. Janelle Teng, vice president, Bessemer Venture Partners: We are moving beyond the modern data stack. The data infrastructure landscape is undergoing a massive transformation, fueled by various factors, including the rise of lakehouse architecture and convergence toward specific open table format standards. Raviraj Jain, partner, Lightspeed Venture Partners: Energy is a huge sector to invest in given increasing demand for energy for data centers and the challenges with grid failures across the country. We'll see continued interest in nuclear -- both fusion and fission. When it comes to AI, how are you determining that a company has a moat? Cathy Gao, partner, Sapphire Ventures: I think about it in a "5D framework": design, data, domain expertise, distribution, and dynamism. Since early this year, we at Sapphire have used this framework to evaluate companies building applications with AI. SC Moatti, managing partner, Mighty Capital: An AI moat is built on proprietary data, cutting-edge algorithms, and scalable infrastructure, enabling unique and superior solutions. Scott Beechuk, partner, Norwest Venture Partners: The deepest moats will be created by large proprietary datasets. The companies with the greatest long-term potential are those building their own unique datasets to excel in their particular, verticalized channels -- often by either training or fine-tuning their own models. Jonathan Lehr, co-founder and general partner, Work-Bench: As a pureplay seed fund, we're focusing most of our energy in vertical AI opportunities tackling business-specific workflows that require deep domain expertise and where AI is mainly an enabler of acquiring previously inaccessible (or highly expensive to acquire) data and cleaning it in a way that would've taken hundreds or thousands of man-hours. Raviraj Jain, partner, Lightspeed Venture Partners: Question to ask is, As models become better, does this company get threatened or strengthened? What does it take to raise a Series A as an enterprise startup in 2025? Liran Grinberg, co-founder and managing partner, Team8: With a strong founder-market fit, and an ambitious vision to build a big company, one can raise a solid $15 [million to] $25 million Series A round with only a few $100Ks in ARR. Molly Alter, partner, Northzone: Successful Series A enterprise startups will show strong topline traction (>100% YoY) with low burn multiples; gone are the days of 2021 when it was all about growth at all costs. More importantly, these businesses will show a clear long-term differentiation strategy that will set them apart from the host of other offerings attempting to raise money and sell into the same enterprise customer base. Kirby Winfield, founding general partner, Ascend: Go from zero to $1 million in two quarters with an A-plus team in a massive market with a differentiated solution having created overwhelming demand. Andrew Ferguson, vice president, Databricks Ventures: If you're building an AI-first product, an all-star technical team and early product market traction ($2 [million to] $5 million ARR) may be the Series A expectation. The time from product launch to $5 million ARR is materially faster in the AI era than it was in the traditional SaaS era. I expect that the Series B bar will be much higher -- and it remains to be seen if this early ARR is high-quality and durable. Jonathan Lehr, co-founder and general partner, Work-Bench: We're hearing from downstream peers that the bar is around $1.5 million with the ability to grow 3x from there sequentially to raise a stellar Series A. Jason Mendel, venture investor, Battery Ventures: Repeatability. Startups that are solving a real pain point in a large market where there is clear urgency from a buyer/user perspective should be well-positioned to raise a Series A in 2025. Do you predict enterprises will increase their tech budgets for 2025? Will they decrease them? Aaron Jacobson, partner, NEA: Within AI, we'll see budget allocated away from "chatbots" to agents. Enterprises will move beyond the low-hanging fruit of "GPT wrappers" to deploy digital workers that can reason and take action to make a real business impact. Scott Beechuk, partner, Norwest Venture Partners: Tech budgets across many industries will increase in 2025, driven by leaders' desire to achieve two goals -- which will sometimes be at odds with each other. The first goal is consolidation. The second is increasing top-line growth and improving operational efficiency, both of which are achievable with AI-based software applications. Buyers will purchase startup solutions in this category despite their desire to consolidate. Kathleen Estreich, partner, Pear VC: In 2024, we expected to see more enterprise adoption of AI. But that hasn't panned out, primarily because we haven't yet figured out use cases that are tightly scoped enough and the tools to reduce hallucinations and validate outputs have not gotten robust enough. In 2025 I expect to see more enterprise adoption as the model providers extend their stack upward. Every enterprise will need an AI tech strategy. If you don't adopt, you won't keep up. This will also create a lot of false signals on the revenue side for AI startups as experimental budgets will be high, but true product-market fit will be harder to see at first glance. Kirby Winfield, founding general partner, Ascend: Enterprises will increase AI budgets in 2025. The question isn't whether they'll invest but how they'll tackle pricing, testing, and data security. Companies like Salesforce and Smartsheet have already committed to AI adoption and will push harder to leverage their data assets to stay competitive. Susan Liu, partner, Uncork Capital: Probably the same for the first half, and then as the economy improves and revenue/profits improve, we'll see an increase in tech budgets in the second half. Mike Hayes, managing director, Insight Partners: Based on what I'm hearing from our enterprise partners, they're likely to marginally increase their tech budgets in 2025, with a focus on areas that deliver measurable ROI and clear KPIs. I expect pressure from boards and CXOs to put AI use cases into production to increase and receive discretionary budget. I also expect continued enterprise investment in cybersecurity and cloud optimization. Said differently, the right emerging technologies should not have trouble landing due to tech budgets. Jason Mendel, venture investor, Battery Ventures: I'm optimistic about 2025 and expect to see companies increase their IT budgets with a strong focus on emerging technologies. Heading into the 2025 budgeting season, we at Battery Ventures polled 100 CXOs, collectively representing over $35 billion in annual technology spend, and 74% of them expected to increase their technology spend in 2025. Will there be more AI adoption? Paul Drews, managing partner, Salesforce Ventures: Yes, essentially all enterprise workflows can be optimized with AI -- especially agentic AI. We're seeing real demand for AI and ML tools that can make underlying models 50% more efficient while delivering improved results. AI is experiencing froth, but from a larger market perspective (not just Silicon Valley), AI is still new and everyone is trying to figure out how to use it, price it, and purchase it. Mark Rostick, vice president and senior managing director, Intel Capital: For the moment, it is clearly easier to adopt AI through application vendors than trying to build your own platform given that the market for enterprise platform tools is still very, very fragmented. I do think there is pent-up demand for some sort of platform solution, so I believe we'll see many founders trying to address that problem this coming year. Raviraj Jain, partner, Lightspeed Venture Partners: It's a consensus view but AI adoption will continue to accelerate in 2025 as (1) model capabilities improve, (2) enabling infrastructure is built out, and (3) stronger AI-first products come to market. What kinds of companies in your portfolio are seeing the strongest growth? Do you predict that will change in 2025? Marell Evans, founder and general partner, Exceptional Capital: Urgent pain points for AI-ready customers are producing shorter enterprise sales and procurement cycles and therefore faster traction and scale. As we see AI adoption more broadly, we may see enterprises will have greater appetite to try not just solving for the urgent problems but also planning ahead to maintain competitive edge with "nice to have" or more future-forward and strategic solutions. Kathleen Estreich, partner, Pear VC: We are seeing great traction in vertical agents with a clear understanding of the unique needs of their customers. I think vertical SaaS is a huge opportunity in 2025 to own the end-to-end workflows with custom-built agents for the tasks to be done. Janelle Teng, vice president, Bessemer Venture Partners: Many of Bessemer's AI defense tech companies experienced tremendous growth this year. One of our observations earlier in the year is that the defense community is not sitting idly by as the AI revolution sweeps the consumer and commercial industries by storm. The [Department of Defense] mapped and released its formal AI adoption strategy last year, and we predicted that advancements and applications of ML will be embraced as essential for the national agenda and the defense community's day-to-day work. This prediction proved prescient as the year continued. Mark Rostick, vice president and senior managing director, Intel Capital: Another strong segment of the portfolio focuses on the infrastructure layer of software and services companies. Anyscale is a fantastic example. With their software, developers can build, run, and scale AI applications instantly. There's also RunPod, a virtual cloud service provider (CSP) for inference. It can bridge the gap between hardware and software stacks, which allows for seamless operation across various server providers, addressing a current challenge in the AI space. Ed Sim, founder and general partner, Boldstart Ventures: No. This is one of the greatest platform shifts I've seen in 29 years of being a venture capitalist and IMO this will only accelerate. What are your predictions for the exit environment next year? Cathy Gao, partner, Sapphire Ventures: I predict M&A activity will increase as large companies seek to acquire AI expertise. Strategic acquirers will focus on startups with domain-specific AI capabilities or high data moats. The IPO market will remain cautious, but high-growth companies with profitability metrics might test the waters. Nina Achadjian, partner, Index Ventures: I anticipate more liquidity in 2025, both for M&As and the public markets. Aaron Jacobson, partner, NEA: With the change of administration, I expect the return of mega M&A deals. We are going to see a multi-billion and even decacorn M&A outcome for a leading AI company. Marell Evans, founder and general partner, Exceptional Capital: We expect exits to pick up slightly next year, possibly more acquisitions and IPOs. Although, given the latest fed meeting, exit volume might be slower than we expected. Kirby Winfield, founding general partner, Ascend: I predict new FTC leadership under the incoming administration will make hyperscalers more acquisition-friendly for tech and talent. But the IPO market will likely remain sluggish, given the frothy valuations some companies can command from the private market. Andrew Ferguson, vice president, Databricks Ventures: 2025 may finally be the year that we see an uptick in tech M&A activity, as more favorable macro and (potentially) less onerous regulatory oversight make larger companies less skittish about M&A. Most strategic M&A will be focused around amazing technical founders and technology, rather than on scaled business, especially ones that matured during the ZIRP era where the growth/profitability metrics may still not pencil out for strategic acquirers. It's possible that private equity or growth equity investors make a play to consolidate that class of assets into broader platforms. Paul Drews, managing partner, Salesforce Ventures: The likely emphasis on government efficiency and lower regulation will spur growth, investments, and exits. The public markets are soaring, but there continues to be hesitation around the IPO process from a private company perspective. We've seen glimmers of hope in the IPO markets, which pre-IPO businesses should take as a good sign, but there is still some disconnect between the last private valuation and where the public market will price businesses. Mike Hayes, managing director, Insight Partners: I think enterprises will look to strengthen their inorganic growth through acquisition more in 2025 than in 2024. As far as the IPO market, I do think that enterprises focusing on mission-critical solutions with predictable revenue will have opportunities in 2025. I'm optimistic and energized for 2025.

Why 2025 will redefine data infrastructure: 11 expert insights on sovereign clouds, exploding data, PaaS and more

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More If 2023 was all about generative AI-powered chatbots and search, 2024 introduced agentic AI -- tools capable of planning and executing multi-step actions across digital environments. From Devin's engineering breakthroughs to Microsoft's early trials with Copilot Vision, the innovations were diverse, but one constant remained: the need to keep data infrastructure organized and reliable. As enterprises leaned into advanced AI initiatives, several trends reshaped how data is managed, secured and used. Businesses increasingly adopted multicloud, open data, and open governance strategies to avoid vendor lock-in and gain more flexibility. They also focused on unstructured data, transforming data marketplaces into hubs providing pre-trained AI models with proprietary datasets and apps. Simultaneously, progress in vector and graph databases added new possibilities, setting the foundation for what's next. Now, as the AI story continues to unfold, industry leaders share their predictions for how the data infrastructure underpinning it will evolve in 2025. 1. Real-time multimodal data will fuel intelligent data flywheel "In 2025, enterprises will fully embrace multimodal data and AI, transforming how they operate and deliver[ing] value. At the core of this shift is the 'Intelligent Data Flywheel' -- a dynamic cycle where real-time data powers AI-driven insights, fueling continuous innovation and improvement. Today's dark data -- images, videos, audio, and sensor outputs -- will become central to unlocking sharper predictions, smarter automations and real-time adaptability, ultimately leading to a richer and more nuanced understanding of the business reality. "With the real-time data flywheel in place, AI will autonomously diagnose problems, optimize processes and generate innovative solutions. Enterprises will rely on AI agents to ensure data quality, uncover insights and shape strategies, enabling human talent to focus on higher-level tasks. This will redefine efficiency, accelerate innovation and transform businesses into more dynamic and intelligent organizations." - Yasmeen Ahmad, MD of strategy and outbound product management for data, analytics and AI at Google Cloud 2. Chill factor: Liquid-cooled data centers "As AI workloads continue to drive growth, pioneering organizations will transition to liquid cooling to maximize performance and energy efficiency. Hyperscale cloud providers and large enterprises will lead the way, using liquid cooling in new AI data centers that house hundreds of thousands of AI accelerators, networking and software. "Enterprises will increasingly choose to deploy AI infrastructure in colocation facilities rather than build their own -- in part to ease the financial burden of designing, deploying and operating intelligence manufacturing at scale. Or, they will rent capacity as needed. These deployments will help enterprises harness the latest infrastructure without needing to install and operate it themselves. This shift will accelerate broader industry adoption of liquid cooling as a mainstream solution for AI data centers." - Charlie Boyle, VP of DGX platforms at Nvidia 3. Global data explosion to create storage shortage "The world is creating data at unprecedented volumes. In 2028, as many as 400 zettabytes will be generated, with a compound annual growth rate (CAGR) of 24%. However, the storage install base is forecasted to have a 17% CAGR -- therefore [growing] at a significantly slower pace than the growth in data generated. And it takes a whole year to build a hard drive. This disparity in growth rates will disrupt the global storage supply-and-demand equilibrium. As organizations become less experimental and more strategic in the use of AI, they will need to build greater physical data center space and capacity plans to ensure storage supply, and fully monetize investments in AI and data infrastructure -- while balancing financial, regulatory and environmental concerns." - B.S. Teh, EVP and chief commercial officer at Seagate Technology 4. AI factories will evolve to PaaS "In 2025, AI factories will evolve beyond their initial phase of providing infrastructure-as-a-service, offering compute, networking, and storage services, to delivering platform-as-a-service capabilities. While the foundational services have been essential to jumpstart AI adoption, the next wave of AI factories will prioritize platforms that drive data affinity and provide lasting value. This shift will be key to making AI factories sustainable and competitive in the long term." - Rajan Goyal, cofounder and CEO at DataPelago 5. Companies will use their massive datasets but demand reliability "For the most part, early applications of AI have just used foundation models trained on massive amounts of public data. With sophisticated RAG applications becoming mainstream and the rapid maturity of products to produce structured data, applications that leverage the massive troves of private enterprise data will begin to create true value. But the bar for these applications will be high: Enterprises will demand reliability from AI applications, not just the whiz-bang demo. "Further, AI companies providing these models will have to play nice with publishers and content providers to safeguard the future of AI development. They will need to enter licensing agreements with content providers to ensure they're being compensated for the extremely valuable data they offer. This must happen soon, before it's all a tangle of lawsuits and blocking AI crawlers." - Sridhar Ramaswamy, CEO at Snowflake 6. Enterprise agents will devour communications data "In 2025, enterprises will mine terabytes of communication data, such as emails, Slack messages, and Zoom transcripts, using agents that deliver analytics insights, dashboards, and actionable decision support tools. "This will drive significant productivity improvements across industries." - Nikolaos Vasiloglou, VP of research and ML at RelationalAI 7. Data governance and quality will be biggest barriers to successful and ethical AI adoption "In 2025, data governance, accuracy and privacy will emerge as the most significant barriers to effective AI adoption. As organizations look to scale AI, the realization will occur that successful AI outcomes are entirely dependent on trustworthy data. Managing and preparing massive amounts of data, ensuring compliance and maintaining accuracy will provide complex challenges. Enterprises will need to overcome these hurdles by investing in foundational data platforms that enable unified management across diverse data sources. "As a result, we'll see a stronger emphasis on data stewardship roles and governance frameworks that align with AI initiatives, as businesses recognize that unreliable data directly impacts AI effectiveness." - Jeremy Kelway, VP of engineering for analytics, data and AI at EDB 8. Unified data observability platforms will emerge as essential tools "In 2025, unified data observability platforms will emerge as essential tools for large enterprises, enabling comprehensive visibility into data infrastructure performance, quality, pipeline health, cost management and user behavior to address complex governance and integration challenges. By automating anomaly detection and enabling real-time insights, these platforms will support data reliability and streamline compliance efforts across industries." "In 2025, we're going to see a real push towards sovereign and private clouds. We're already seeing the largest hyperscalers pouring billions of dollars into constructing data centers around the world to offer these capabilities. This...capacity will take a while to come online; in the meantime, demand will skyrocket fueled by a wave of legislation coming predominantly from the EU. Those with flexible, scalable and elastic cloud infrastructure will be able to adopt sovereign or private approaches quickly. Those with monolithic, rigid infrastructure will be putting themselves behind the curve." "I'm keeping an eye on the potential expansion of edge computing, driven by the proliferation of 5G, which brings data processing closer to the source and reduces latency. This could help democratize AI. The question is, can we build efficient AI apps that run on mobile devices, possibly without relying on cloud resources? "If 5G is available to field technicians, they could leverage AI to assist in their work -- whether it's medical professionals providing diagnosis and treatment in disaster areas where 5G is available but Wi-Fi isn't, or engineers and scientists making on-site decisions with AI-assisted research and real-time calculations." - Jerod Johnson, Sr. technology evangelist at CData 11. Protection of unstructured data will become more urgent "Traditionally, data protection has focused on mission-critical data because this is the data that needs faster restores. Yet the landscape has changed, with unstructured data growing to encompass 90% of all data generated in the last 10 years. The large surface area of petabytes of unstructured data coupled with its widespread use and rapid growth make it highly vulnerable to ransomware attacks. Cyber-criminals can use the unstructured data as a Trojan horse to infect the enterprise. Cost-effectively protecting unstructured data from ransomware will become a critical defense tactic, starting with moving the cold, inactive data to immutable object storage where it cannot be modified. "To this end, IT and storage directors will look for unstructured data management solutions that offer automated capabilities to protect, segment and audit sensitive and internal data use in AI -- a use case that is bound to expand as AI matures. Further, they will need to create systematic ways for users to search across corporate data stores, curate the right data, check for sensitive data and move data to AI with audit reporting." - Krishna Subramanian, cofounder of Komprise To sum up, 2025 promises significant advancements in enterprise data infrastructure, ranging from multimodal data flywheels to sovereign clouds. However, challenges such as data governance and storage shortages will persist. Success in this dynamic space will depend on balancing innovation with trust and sustainability, turning data into a lasting competitive advantage.