As global competition intensifies and supply chains fracture, the ability to deploy capital into technologies that make the US more self-reliant, adaptive, and secure has become a national priority. 

JPMorgan Chase’s initiative is designed to meet that moment, representing both a financing bonanza for US-based companies across the 27 strategic sub-areas identified by the banking giant and a capital deployment challenge. 

To help, we’ve used CB Insights’ predictive signals, including our outlook score for company success, Mosaic, to shortlist 79 companies for JPMorgan Chase to consider investing in. 

We map them all below, categorized across all but 4 of the strategic areas identified by JPMorgan Chase due to a lack of promising startups matching our criteria — full methodology available at the end of this report. Key recommendations follow.

Find our success and exit predictions for the full list of featured companies here

Key recommendations

Invest in AI as the backbone of manufacturing sovereignty 

A new class of industrial AI startups is aiming to rebuild the nation’s productive capacity across manufacturing, materials, and mobility. 

Companies like Skild AI (robot foundation models), Charge Robotics (factory automation), and Cartken (autonomous mobile robots) are reducing the cost gap for onshore production by automating physical work and logistics. 

Meanwhile, Earth AI and Periodic Labs are applying AI to accelerate materials discovery and secure domestic access to critical minerals and battery inputs. Material development platforms have recently captured investor attention as AI and quantum computing unlock new capabilities, becoming one of the hottest emerging markets (i.e., with a Commercial Maturity median of 3 or below) in the manufacturing sector. 

Source: CB Insights Markets Index (as of 9/9/2025)

Even legacy-heavy domains like shipbuilding are seeing AI-enabled autonomy from firms such as Seasats and Blue Water Autonomy, which aim to reduce costs in a historically high-cost, labor-intensive industry. 

Together, these companies are forming the digital-industrial layer for intelligent reshoring, using AI to make domestic manufacturing faster, adaptive, and globally competitive again.

Bet on autonomous defense systems to redefine deterrence

Modern conflict is evolving faster than traditional defense procurement can adapt, primarily driven by the proliferation of drone warfare with the invasion of Ukraine. A new generation of startups is filling the gap with software-defined, low-cost autonomy. 

Companies like Fortem Technologies (drone detection and interception) and Allen Control Systems (Counter-unmanned systems) are deploying scalable unmanned systems across air and land. Paired with Picogrid’s defense connectivity networks and Rune Technologies’ predictive logistics AI, these platforms create adaptive, sensor-rich meshes that can respond to threats in real time. 

The result is a rapidly emerging autonomous defense ecosystem that strengthens deterrence through speed, intelligence, and distributed resilience.

See the hottest defense tech markets ranked by equity raised over the past year here

Smarter and cleaner energy production and distribution will help maintain AI lead

The AI boom has made energy an ever greater strategic resource, making diversified, digitally managed generation essential to both national security and computational progress. 

Investing in startups focused on nuclear innovation, solar automation, and AI-driven grid resilience will help build a smarter, sovereign energy base. 

Companies like Pacific Fusion and Realta Fusion are redefining what clean baseload power can look like, while Aalo Atomics and Natura Resources advance modular fission systems that can be rapidly deployed near data and industrial centers. 

Paired with Antora and Rondo Energy’s storage systems and David Energy’s automated grid orchestration, these technologies form an adaptive, distributed energy network capable of self-balancing demand spikes from AI compute and industrial electrification. 

See the most promising startups helping manage demand spikes from AI here

Investing in this ecosystem builds not only clean power capacity but also strategic autonomy, ensuring the intelligence revolution runs on domestically controlled, resilient, and low-cost energy.

Support edge intelligence to make AI truly ubiquitous

The frontier of artificial intelligence is shifting from centralized data centers to the physical world, where latency, cost, and privacy demand on-device autonomy. 

Startups like EnCharge AI (compute-in-memory chips) and MemryX (edge inference for automotive and robotics) are re-architecting silicon for real-time decision-making, while Modal and Fireworks AI deliver serverless deployment layers that make model execution as elastic as cloud functions. 

On the software side, Together AI (an AI 100 2025 winner) and Liquid AI are advancing compact, efficient small language models that can run locally, enabling intelligence in drones, sensors, and industrial systems. 

Combined, these technologies are creating a distributed AI fabric that embeds cognition into every node of the economy, from factory floors to vehicles and handhelds. The result: lower latency, greater resilience, and unprecedented reach, as intelligence moves from “in the cloud” to everywhere work gets done.

Track emerging genAI startups, shifting markets, and breakout opportunities in real-time here

Finance the intelligent age security: AI, data, and infrastructure

As AI becomes the backbone of critical systems, the attack surface expands exponentially. 

A new cohort of startups is fortifying this frontier by integrating AI-native security, quantum-safe encryption, and infrastructure hardening into the fabric of the intelligent economy. 

Companies like TXOne Networks and Xage Security are protecting industrial and energy assets with zero-trust architectures built for operational technology, while TrustLogix and Concentric AI safeguard sensitive enterprise data through granular policy enforcement and autonomous monitoring. 

TrustLogix is among the AI security startups most likely to be acquired next, according to CB Insights Predictive Intelligence, as large cyber players have been on a M&A spree to seize this opportunity and integrate AI security features into existing offerings.

See the top AI security startups ranked by their M&A probability

Quantum Xchange ensures secure data transmission with quantum-resistant encryption, and HiddenLayer defends AI models themselves against poisoning, inversion, and adversarial attacks.

Together, these technologies create a secure AI infrastructure stack that spans digital, data, and physical domains, ensuring that as intelligence scales, trust scales with it. Investing in this layer isn’t just about cybersecurity; it’s about protecting the nervous system of the modern economy.

Methodology

We used CB Insights’ predictive intelligence to analyze thousands of startups and select the most promising ones that align with JPMorgan Chase Security and Resiliency Initiative’s 4 key areas and 27 sub-areas.

We looked across our 1,500+ Markets to identify the hottest areas based on equity funding raised over the past year and selected companies with the highest Mosaic scores (min 550) operating in these markets. We focused on private, early to mid-stage (Series B max), US-based startups. Data is as of 10/23/2025.

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GenAI and agentic AI are expanding attack surfaces and fueling a booming AI security market. While companies are actively hiring for AI and security talent, as revealed by CB Insights’ Hiring Insights Agent, they have also opted for M&A as a faster way to seize the opportunity and integrate AI security features into existing offerings.

Most of these acquisitions are early-stage end-to-end platforms that combine offensive capabilities (red teaming, vulnerability management) with defensive features (incident response, alerts). Over half of the targets were Series A or earlier, 75% raised under $60M, and only one was generating revenue.

This points to a future where AI security becomes a table-stakes feature embedded in broader cyber offerings, rather than a standalone platform — driving large players to continue their acquisition spree.

Using CB Insights’ predictive signals, including Mosaic company health scores and M&A probability, we’ve identified the AI security startups that are ripe for acquisition next. 

See the top AI security startups ranked by M&A probability here

Key takeaways

• Securing the data pipeline will be a new frontier in AI security. Companies with the highest M&A probability in this group focus on securing AI data pipelines, including TrustLogix (with a 56% chance of being acquired in the next 2 years) and Protecto (with a 64% chance). Both are early-stage and have not received funding past Seed. Their combination of strong Mosaic (more than 1.5X the overall average of 370) and low funding positions these companies as low-cost acquisition targets that could add value in industries with highly sensitive data.
• Partnerships with large tech firms signal product validation, with 5 out of the 8 interest zone companies having partnered with large tech or cyber firms. 2 companies partnered with Snowflake for data privacy, 2 partner with Amazon, 1 integrates with OpenAI ChatGPT, and 1 has an ex-Google CISO on board. This market is nascent, with all companies either validating or deploying solutions and having raised at most Series A funding. In a market that’s so early-stage, partnerships are a proxy for market validation to potential acquirers.
• C-suite tech expertise is a talent acquisition opportunity: 50% of founding teams  come from large tech companies. The CEO of HydroX AI spent time at Meta, HP, and LinkedIn, the C-suite of Protecto comes from Microsoft, Apple, and Oracle, and the founding team at Lasso Security comes from SAP and Check Point. This expertise at the highest levels makes these companies potential targets for acquirers looking to bring AI talent in-house. As Check Point CEO Nadav Zafrir noted in a recent earnings call, “in this AI world, it’s all about talent and the critical mass of talent that you can bring into the organization.” 

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They already dwarf the private tech sector — surpassing the combined value of all 1,200+ unicorns by a factor of 3 — and after a period of layoffs, they’re back to hiring, with 2024 headcount growing an average of 7% YoY.

Now, they’re betting big on AI to power their next phase of growth. 

Spending on AI infrastructure (including data centers) has sent their capital expenditures to unprecedented levels. The venture arms of Nvidia, Google, and Amazon all backed a record number of AI deals last year. And after a years-long slump in big tech M&A, AI acquisitions will likely drive a rebound in 2025.

Below, we dive into how AI is reshaping dynamics among big tech players — including deep dives into fast-emerging markets like humanoids and AI agents — across 7 charts.

Note: We include US-based big tech companies based on market cap ($1T+) as of 04/11/2025.

Big tech heads toward $300B+ in 2025 capex

Increased spend on AI infrastructure like high-powered data centers has driven Amazon, Microsoft, Alphabet, and Meta’s combined capex past $50B in recent quarters. 

Meta CEO Mark Zuckerberg framed Meta’s capex spend as a “strategic advantage” on its Q4’24 earnings call as the company scales AI usage across its products. Meta plans to spend $60-65B in capex in 2025.

As AI model costs drop, cloud providers in particular expect they will benefit from the expanding market. 

Microsoft CEO Satya Nadella emphasized this potential on the company’s recent earnings call: “We ourselves have been seeing significant efficiency gains in both training and inference…as AI becomes more efficient and accessible, we will see exponentially more demand.”

To capture the demand, the big 3 are planning major infrastructure investments: 

• Amazon projects $100B in capex in 2025, up from $83B in 2024
• Microsoft has committed $80B in 2025 to build out AI data centers
• Google expects $75B in capex in 2025

Cloud competition hinges on AI demand

AI demand is turning into cloud revenue for Amazon, Google, and Microsoft. 

AI sales have helped boost revenue growth for Microsoft’s Azure and cloud services arm, which averaged 31% quarterly growth in 2024, up from 28% in 2023.

Google Cloud’s more muted growth in Q4’24 (down 5 percentage points quarter-over-quarter) sent Alphabet’s shares down in February. Both Microsoft and Alphabet cited compute capacity constraints as reasons for the more limited growth in their latest quarters. 

Expect close investor attention in 2025 to cloud revenue growth, especially as these players accelerate their infrastructure spend. AWS’ $28.8B in Q4’24 revenue was nearly on par with Amazon’s capex spend overall ($27.8B). 

Meanwhile, as cloud competition intensifies, providers are strengthening their security offerings to capture enterprise clients with stringent compliance requirements. 

Google Cloud has made notable investments in cloud security through strategic acquisitions including Wiz, Siemplify, and Mandiant. In contrast, AWS primarily leverages its partner network for security solutions, collaborating with companies like Bitdefender for endpoint security and CrowdStrike for incident response. 

Their divergent approaches represent another dimension where cloud giants are competing for enterprise wallet share, beyond just AI compute capacity.

2025 likely to bring a rebound in M&A

Tech giants have pulled back dramatically on M&A in the last few years amid the antitrust climate. But with a new US administration in office, tech giants are betting on a friendlier dealmaking environment.

Notably, Google parent Alphabet announced a $33B acquisition of cloud security firm Wiz in March — the biggest VC-backed M&A exit ever. It’s also the first billion-dollar big tech acquisition since 2023, when Microsoft’s Activision deal closed. 

In 2024, Nvidia led acquisition activity, with a focus on companies optimizing AI workloads (Run:AI, Deci, Octo AI). It’s already made 2 more acquisitions in 2025 so far: synthetic data generation startup Gretel in March; and server-renting service Lepton AI in April.

While tech giants test the M&A waters, we also expect to see more “quasi-acquisitions” — for instance, hiring away the teams and licensing the tech of promising startups to avoid antitrust scrutiny. For example, Amazon hired robotic startup Covariant’s founders and a quarter of its staff, while licensing the company’s models, in August 2024. 

Nvidia accelerates AI startup investments

Nvidia has leapfrogged other big tech companies like Microsoft and Amazon in AI dealmaking. 

The chip leader’s AI startup investments nearly 5x’d between 2022 and 2023. Of course, many of its investments — like Perplexity and xAI — are in turn using its chips.  

The upswing indicates the strategic importance it’s placing on being a player in the AI startup landscape. 

Nvidia also takes the lead when it comes to the strength of its AI startup portfolio. According to CB Insights’ Mosaic scores — which measure private-company health and growth potential, on a scale of 0-1,000 — Nvidia’s AI investments since 2024 come out on top with an average score of 840. 

Nvidia is followed by Microsoft, with an average Mosaic score of 750 among its AI investments since 2024.

See every big tech-backed, private AI company ranked by Mosaic

Physical AI in focus

Big tech is aggressively pursuing the humanoid robotics space. 

In February 2025, for example, Google joined Apptronik’s $403M Series A funding round while Meta formed a new unit under its Reality Labs hardware division to develop humanoids.

Humanoids are complicated to build and deploy, requiring substantial sensor processing, advanced control, and more.

Tech giants see this as an opportunity to flex their software muscle and deep pockets. AI breakthroughs are unlocking new robotic capabilities, allowing humanoids to complete more complex tasks in a shorter training window, with applications from industrials to healthcare. 

CBI customers: Map the industrial humanoid robotics market

Race to own AI agents

Increasingly capable AI agents will reshape industries as we know them. 

Big tech is getting in on the ground floor — each company is developing agents or building the tooling for them. 

We expect big tech players (alongside LLM developers) to dominate general-purpose agent use cases, such as in commerce, given their distribution and infrastructure edge. Read more in our report on AI agent trends to watch.

RELATED RESEARCH FROM CB INSIGHTS

• The AI agent market map
• The future of the customer journey: AI agents take control of the buying process
• Big Tech in Energy: How Amazon, Google, Microsoft, & Nvidia are advancing the global energy transition
• The foundation model divide: Mapping the future of open vs. closed AI development

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The AI boom has set the stage for a wave of tech M&A this year.

After 2 consecutive years of decline, tech M&A deals were up in 2024, with some of the largest deals centering on AI. AI companies have also bucked the general downward trend in exit valuations, instead seeing nearly double the median acquisition price from 2023 to 2024.

Using CB Insights’ predictive signals, such as Mosaic and M&A Probability, we’ve identified 7 AI-related areas where we expect to see M&A activity this year, as well as high-potential acquisition targets for each.

See highlights below, and download the full report for the rationale behind each prediction, as well as M&A target shortlists.

Tech M&A prediction highlights

• Big tech players set their sights on humanoid robotic: As physical AI takes off thanks to the rise of LLMs, humanoid robotics is becoming big tech’s next battlefield. Among high-potential acquisition targets, 1x stands out for its dual focus on industrial and consumer humanoids (just in January, it acquired Kind Humanoid to accelerate household robot development). This makes it a prime target for Meta, which recently announced plans to enter the consumer humanoid market.
• Enterprise tech heavyweights compete for AI infrastructure dominance: We’re already seeing strong signals from cash-rich companies such as Cisco and IBM, which are future-proofing their business models with AI investments. Hardware-aware AI optimization players CentML and Nota AI — which help accelerate AI model deployment while reducing compute costs — appear in our AI infrastructure acquisition target list. These companies have already shown quantifiable efficiency improvements as well as validation from Nvidia as a partner or investor.

Source: CB Insights advanced search. Data is dynamic (as of 2/27/2025).

• Data center energy demands fuel interest in cooling tech: Companies offering immersion and liquid cooling solutions enjoyed a funding rebound last year, attracting a combined $120M in fresh funding. Hypertec and Submer are high-potential acquisition targets in this space.
• Professional services firms seek AI capabilities: GenAI is coming for knowledge jobs — and leading professional services firms are buying AI capabilities to get ahead of it. One area where we see high M&A potential for professional services firms is to cater to clients’ responsible AI needs, with potential acquisition targets such as Lasso Security and HydroX AI.
• Pharma companies target AI drug discovery startups: AI drug discovery M&A is surging, with 12 deals in the sector since 2023. That M&A deal volume reflects both a maturing technology and growing urgency among pharma players to bring AI tech in-house.
• SaaS giants fortify their offerings with AI agent acquisitions: While some believe AI agents signal the death of SaaS companies, we anticipate SaaS leaders will acquire AI agent companies to avoid disruption. We’re already starting to see this happen with ServiceNow acquiring Moveworks for close to $3B in March 2025.

Source: CB Insights — ServiceNow Acquisition Insights

• Coding AI agents drive next wave of AI agent consolidation: Explosive growth, soaring valuations, a fractured AI agent landscape, and rising doubts about revenue defensibility make the coding AI agents market ripe for consolidation. While some players like Cursor look too expensive for an acquisition, we’ve identified Warp, Vidoc, and Bito as likely targets with high Mosaic scores and higher-than-average M&A Probabilities.

What is Mosaic?

Mosaic is CB Insights’ proprietary metric that measures the overall health and growth potential of private companies using non-traditional signals. Mosaic is widely used as a target company and market screener to identify high-potential emerging tech companies, typically defined as those with a score of 510 or higher.

What is M&A Probability?

M&A Probability is CB Insights’ proprietary signal that measures a private company’s chance of an M&A exit within the next 2 years. It is used to quickly screen and triangulate companies based on exit likelihood.

Combining both Mosaic Score and M&A Probability makes it easy to shortlist acquisition targets.

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The 2024 Change Healthcare cyberattack demonstrates the far-reaching consequences of cybercrime in healthcare. This attack compromised the protected health information of at least 100M people and cost parent company UnitedHealth around $3B.

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These attacks can inflict damages costing billions of dollars. Since 2017, every critical infrastructure cyberattack causing an estimated $1B+ in damages has affected the healthcare sector in some capacity, highlighting its particular vulnerability to digital threats.

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By 2029, SDVs could account for as much as 90% of auto production, up from just 3% in 2021, per Morgan Stanley. However, the transition comes with steep challenges, such as the technical complexity involved and the need for strong cybersecurity measures to protect connected vehicles.

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

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What you need to know:

Startups in the space have raised just over $350M across 21 deals YTD (as of 10/7/2024). This marks a big funding increase compared to prior years and has been driven almost entirely by early-stage activity. 

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As new, hard-to-predict threats emerge from the nascent genAI space, so too do startups working on a broad range of novel cybersecurity solutions — some of which protect against genAI risks, while others use genAI to build new defenses. 

But among these young companies, which are building the tech solutions that could eventually grow into their own cybersecurity markets? 

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For the networking leader, AI forms the crux of a multi-pronged strategy to steer away from pure hardware toward services and software, which offer expanded revenue streams. Cisco is investing in pure-play AI infrastructure startups, forming AI partnerships, and embedding AI in its products.

Yet Cisco is going one step further by embracing an approach to AI computing centered on Ethernet and networking fabrics. These technologies could help handle the scale the speed demanded by data- and compute-intensive AI workloads. To this end, Cisco has partnered with chip leaders like Nvidia to help businesses manage AI clusters and deployments more easily. 

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Wiz also considered a $23B acquisition by Google, before walking away from the offer in July with plans to pursue an IPO. The news comes alongside rising cyber consolidation as cyber leaders look to keep up with an evolving attack surface, with M&A activity up 14% quarter-over-quarter (QoQ).

We break down the cybersecurity landscape in H1’24 across funding trends, mega-rounds, exits, and more using CB Insights data

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Humans will still play a crucial role — but instead of assembling parts or operating machinery, they will maintain robots and keep them running.

In these future factories, robots coordinate in unison, completing work automatically — without breaks, every hour of the day — to get products out the door. 

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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. 

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Beyond relevance to government agencies, IQT’s investment activity has historically pointed to next-gen technologies that have the potential to be developed for use beyond the public sector.

IQT has participated in over 50 disclosed deals since the beginning of 2022, with many of its investments falling into areas categorized as “deep tech” — cutting-edge technologies rooted in scientific or engineering advances, such as biotech and quantum computing.

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These threats include data poisoning (corrupting or modifying training data to compromise the model), jailbreaking (tricking the LLM into producing malicious outputs that bypass safety protocols), and prompt injection (manipulating the input prompt to override the LLM’s original instructions).

Companies offering generative AI-powered solutions face high stakes, as security incidents could lead to compromised AI models, sensitive data loss, or reputational damage. A notable example occurred when Samsung banned use of generative AI tools after employees disclosed meeting notes and proprietary code to OpenAI’s ChatGPT last year.

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Driving the upswing: Humanoid robot funding has reached a record annual level just 4 months into the year, while investment in the operational technology (OT) security tools that can help protect them has already outpaced the previous 2 years combined.

Despite the gains, sector-wide deal count fell to its lowest quarterly level since 2016. This mirrors the broader pullback in venture dealmaking globally. 

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The company has faced multiple high-profile incidents over the past 6 years — including crashes involving its planes and a fuselage blowout. This series of events has resulted in a decline in consumer trust, aggravated airlines, and lost sales to rival Airbus.

Amid these challenges, Boeing has shaken up its corporate leadership and moved to improve its manufacturing quality. For instance, the company is exploring a reintegration with Spirit AeroSystems to help address production flaws.

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Threats to grid stability are escalating due to more extreme weather events and sophisticated cyber attacks. Increasing electricity demand due to data centers and electric vehicles exacerbates these challenges, while the global push toward sustainable — yet intermittent — power sources like solar and wind adds further complexities.

There is an urgent need for more power generation diversity and delivery system reliability, as exemplified by incidents like the 2021 Texas freeze and the 2022 California heatwave.

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Funding to the space set a new record in 2023 — bucking the broader decrease in venture funding for the second year in a row.  

While still a nascent technology, startups are pursuing a broad range of potential use cases for quantum computing (which process information in a fundamentally different way to typical computers) across numerous industries — from training AI models more efficiently to simulating otherwise hard-to-model chemical reactions to quickly solving complex logistics problems, among many others.

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Threats to company hardware — e.g., servers, chips, and hard drives — abound.

For example, some attackers are creating counterfeit hardware that companies are incorporating into their IT infrastructures. These devices often contain backdoors that can be exploited to access company systems. Attackers are also finding ways to modify existing devices to gain unauthorized access. Meanwhile, elements like outdated password practices and firmware-level exploits are introducing additional vulnerabilities.

These hardware attacks can be incredibly damaging.

Compromised hardware can undermine all other cybersecurity defenses in place, granting cybercriminals direct access to sensitive information. Hardware attacks can also allow attackers to gain direct control of a device and even those connected to it in some cases, putting entire systems at risk of infiltration and disruption.

Meanwhile, the risks facing company hardware are intensifying with the development of new technologies. For example, quantum computers could eventually become capable of cracking some types of encryption in a fraction of the time it would take a conventional computer — complicating everyday challenges like user verification, access control, handling data, and more.

As a result, companies are turning to hardware security solutions to protect their physical devices and prevent unauthorized access to enterprise systems.

In the market map below, we identify 144 hardware security vendors operating across 15 categories.

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Note: This map includes public companies, private startups, and exited companies that continue to operate independently. It is not intended to be exhaustive of the space and categories are not mutually exclusive.

Key takeaways

1. Hardware security markets are in varying stages of development. For example, post-quantum cryptography saw an influx of early-stage investment activity last year, while the hardware security modules market is dominated by more legacy firms.
2. More industries — from manufacturing to automotive — are embracing connected products, bringing internet of things (IoT) security front and center. Among highlighted markets, IoT security has seen the most equity deals over the past year (15 deals).
3. Access control is becoming more central to hardware security. Companies are increasingly moving IP assets and computing operations to the cloud, which is creating a new set of security challenges. Consequently, several different markets are now focused on managing user credentials and permissions for cloud applications to uphold hardware security — e.g., enterprise key management, passwordless authentication tools, and biometric identity.

Market descriptions

Enterprise key management

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As AI increases the frequency and sophistication of cyber threats, investors are looking to emerging cybersecurity solutions to help enterprises prevent costly breaches. Advancements in generative AI are also carving out new cybersecurity needs, requiring companies to protect their data, models, and how employees use third-party tools.

Regulation from oversight bodies — like the SEC’s new rules governing cyber risk management and incident disclosure — is also a key driver for investors backing cybersecurity startups.

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Despite the increase, cybersecurity startups secured just $5.7B in the first 3 quarters of 2023, down 58% from the same period in 2022.

While cybersecurity M&A exits declined in Q3’23, the sector saw one of its largest M&A deals to date: Cisco acquired Splunk for $28B to beef up its AI capabilities.

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To prevent and defend themselves against these security vulnerabilities, enterprises are increasingly adopting identity & access management (IAM) solutions, which ensure that the right individuals have access to the right resources at the right time.

IAM solutions are foundational to a zero-trust cybersecurity framework, where each entity is authenticated before being granted permission to corporate resources. More organizations are moving toward this standard as a proactive security measure. Last year, for instance, the US federal government advised all agencies to adopt a zero-trust model by fiscal year 2024. 

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