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Data Center Cooling Tower Market to Reach USD 2.44 Billion by 2035 as Water Rules Push Hybrid and Adiabatic Coolers – DC Market Insights

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Market grows at an 8.06% CAGR from USD 1.12 billion in 2025; hybrid and adiabatic coolers grow fastest at 12.39% a year as AI campuses trade water against power, and replacement plus service work rises to 43.4% of spending by 2035

LONDON, Oct. 19, 2026 /PRNewswire/ — The “Data Center Cooling Tower Market – Growth, Share, Opportunities & Competitive Analysis, 2026-2035” report has been added to the DC Market Insights offering. The global Data Center Cooling Tower Market was valued at USD 1.12 billion in 2025, is estimated at USD 1.30 billion in 2026, and is projected to reach USD 2.44 billion by 2035, growing at a CAGR of 8.06% from 2025 to 2035. DC Market Insights finds that money in this market follows water, not heat: evaporative cooling towers reject data center heat with the least electricity of any method, but water-use disclosure laws in the European Union, California and Utah, and 45 °C liquid-cooled AI racks that can run on dry coolers, are reshaping which designs new campuses buy.

Data Center Cooling Tower Market at a Glance

Metric

Value (DC Market Insights estimate)

Market size, 2020

USD 564.65 million

Market size, 2025 (base year)

USD 1.12 billion

Market size, 2026

USD 1.30 billion (+15.65% year on year)

Market size, 2030

USD 1.93 billion

Market size, 2035

USD 2.44 billion

CAGR 2025-2035

8.06% (low case 6.11%, high case 9.87%)

CAGR 2020-2025 (historical)

14.77 %

Largest product type

Open-circuit cooling towers, 45.0% of 2025 value

Fastest-growing product type

Hybrid and adiabatic coolers, 12.39% CAGR

Leading region

North America, 44.0% (USD 494.66 million)

Fastest-growing region

Latin America, 11.99% CAGR

Largest country

United States, USD 438.45 million (39.0%)

Fastest-growing large country

India, 14.82% CAGR

Market leaders

SPX Technologies (Marley), Baltimore Aircoil Company, EVAPCO: about 50% combined

Key Takeaways

The market more than doubles from USD 1.12 billion in 2025 to USD 2.44 billion in 2035, because new data center capacity served by evaporative heat rejection still grows 55%, from 5,448 MW to 8,467 MW a year, even as its share of new builds falls from 45.4% to 31.4%.Hybrid and adiabatic coolers rise from 25.0% to 37.0% of market value, because they use water only on the hottest days and fit water-disclosure rules better than open towers.Open-circuit towers keep the largest share in 2035 at 33.0%, because they remain the cheapest way to reject heat per kilowatt at water-rich and reclaimed-water sites.Replacement and rebuild work grows 9.77% a year and service and maintenance grows 10.36% a year, both faster than new equipment, as towers built in the 2015-2025 boom reach mid-life.The evaporative-served installed base grows from 55,680 MW of IT load in 2025 to 124,400 MW in 2035, creating a large recurring revenue pool for rebuilds, Legionella risk management and water metering.Dry coolers are the main substitute: an October 2026 order for more than 1,000 dry coolers providing 5 GW of AI heat rejection shows how much new AI capacity can move outside this market.

Scope & Segmentation – Data Center Cooling Tower Market

The report analyzes the market across the following segments:

Product Type: Open-Circuit Cooling Towers; Closed-Circuit Fluid Coolers; Hybrid and Adiabatic Coolers.Construction: Factory-Assembled Units; Field-Erected Towers.Data Center Type: Hyperscale and AI Data Centers; Colocation Data Centers; Enterprise and Edge Data Centers.Offering: New-Build Equipment; Installation and Commissioning; Replacement and Rebuilds; Service and Maintenance.Geography: North America, Europe, Asia Pacific, Latin America, Middle East and Africa, with 12 country forecasts.

Report Updated: Oct. 18, 2026

Get Free Sample Report – Data Center Cooling Tower Market

“The data center cooling tower decision is now a water decision as much as a thermal one. AI campuses that are capped by their grid connection still value the low fan and compressor power of evaporative heat rejection, but disclosure laws and 45 °C liquid cooling are pushing many new halls toward hybrid, adiabatic or fully dry designs. That is why we see hybrid coolers, rebuilds and service contracts growing faster than open towers, and why suppliers that can retrofit an existing tower to cut water by 75% to 90% are best placed for the next decade.”

— Amit Jain, Senior Consultant, ICT & Emerging Technologies, DC Market Insights, report author

Why This Report Matters

Cooling towers sit where three pressures meet: rising AI heat loads, constrained grid power and new public scrutiny of data center water use. The report helps cooling tower and fluid cooler manufacturers, data center operators, hyperscalers, mechanical contractors, water-treatment and service providers, and investors size evaporative and hybrid heat rejection spending, compare it with dry cooling, and track where rules and climate keep water-based designs competitive.

Key Attributes

Report attribute

Details

Historical Period

2020-2024

Base Year

2025

Forecast Period

2026-2035

Market Size 2025

USD 1.12 billion

Market Size 2026

USD 1.30 billion

Market Size 2035

USD 2.44 billion

CAGR 2025-2035

8.06 %

Leading Region

North America (44.0%)

Report Format

PDF + Excel, 21 chapters, 11 data tables

How Big Is the Data Center Cooling Tower Market in 2026?

DC Market Insights values the Data Center Cooling Tower Market at USD 1.30 billion in 2026, 15.65% above 2025, as AI campuses ordered in 2025 receive their heat rejection equipment. The market grew 14.77% a year from 2020 to 2025 because new data center IT capacity doubled from 6,000 MW to 12,000 MW a year. The chart below shows the market path to 2035.

Year

Market size (USD million)

Market size trend

2020

564.65

██████░░░░░░░░░░░░░░░░░░

2025

1,124.23

███████████░░░░░░░░░░░░░

2026

1,300.00

█████████████░░░░░░░░░░░

2030

1,930.00

███████████████████░░░░░

2035F

2,441.75

████████████████████████

Source: DC Market Insights, Data Center Cooling Tower Market report, Oct. 2026.

Why Does Growth Slow From 14.77% to 8.06% a Year?

Growth slows for one reason particular to this product: water. NVIDIA puts the water use of conventional evaporative designs at about 2.6 million gallons per MW a year, and racks that accept 45 °C coolant can run on dry coolers with zero water. DC Market Insights therefore models the evaporative share of new AI capacity falling from 48% in 2025 to 30% in 2035, and the evaporative share of all new data center capacity falling from 45.4% to 31.4%. Because total new capacity rises from 12,000 MW to 27,000 MW a year, evaporative-served capacity still grows in absolute terms.

Indicator

2025

2035

New data center IT capacity per year

12,000 MW

27,000 MW

Share of new capacity using evaporative or hybrid heat rejection

45.4 %

31.4 %

Evaporative-served new capacity per year

5,448 MW

8,467 MW

Evaporative share of new AI capacity

48 %

30 %

Evaporative-served installed base

55,680 MW

124,400 MW

Replacement, rebuild and service share of market

36.2 %

43.4 %

Which Cooling Tower Type Leads Data Center Spending?

Open-circuit cooling towers lead with 45.0% of 2025 value (USD 505.90 million) but grow only 4.76% a year, because open water contact makes them the main target of water rules. Hybrid and adiabatic coolers are the fastest-growing product at 12.39% a year and approach open towers in value by 2035.

Product type

2025 (USD million)

Share 2025

2035 (USD million)

CAGR

2035 value

Open-Circuit Cooling Towers

505.90

45.0 %

805.78

4.76 %

███████████░

Closed-Circuit Fluid Coolers

337.27

30.0 %

732.52

8.06 %

██████████░░

Hybrid and Adiabatic Coolers

281.06

25.0 %

903.45

12.39 %

████████████

Which Data Center Type Spends the Most on Cooling Towers?

Hyperscale and AI data centers spend USD 539.63 million in 2025 (48.0%) and grow 10.50% a year, the fastest data center type, because they add most new capacity even with lower evaporative shares. Enterprise and edge sites grow only 0.83% a year as server rooms move to colocation and cloud.

Data center type

2025 (USD million)

Share 2025

2035 (USD million)

CAGR

2035 value

Hyperscale and AI Data Centers

539.63

48.0 %

1,465.05

10.50 %

████████████

Colocation Data Centers

382.24

34.0 %

756.94

7.07 %

██████░░░░░░

Enterprise and Edge Data Centers

202.36

18.0 %

219.76

0.83 %

██░░░░░░░░░░

Construction and Offering: Where Does the Money Go?

Factory-assembled units hold 72.0% of 2025 value (USD 809.45 million) and grow 9.07% a year as heat rejection modules reach 5 MW per unit; field-erected towers grow 5.00% a year. By offering, new-build equipment leads with 54.1% of 2025 value, while service and maintenance grows fastest at 10.36% a year.

Segment

2025 (USD million)

Share 2025

2035 (USD million)

CAGR 2025-2035

Factory-Assembled Units

809.45

72.0 %

1,928.98

9.07 %

Field-Erected Towers

314.78

28.0 %

512.77

5.00 %

New-Build Equipment

608.28

54.1 %

1,171.07

6.77 %

Installation and Commissioning

109.49

9.7 %

210.79

6.77 %

Replacement and Rebuilds

211.58

18.8 %

537.41

9.77 %

Service and Maintenance

194.88

17.3 %

522.48

10.36 %

DC Exclusive: How Much Water and Capital Does Each Heat Rejection Design Need?

DC Market Insights modelled the equipment cost and yearly water use of five ways to reject heat from one MW of IT load in 2025. A hybrid or adiabatic cooler cuts water by 75% to 90% compared with an open tower for about USD 75,000 to USD 85,000 more equipment per MW, while a dry cooler removes water entirely but costs about 2.6 times the open tower and needs the most fan power on hot days.

Heat rejection design

In this market?

Equipment per MW of IT (USD)

Water per MW of IT a year (m³)

Water use

Fan and pump energy

Open-circuit tower with water-cooled chiller

Yes

80,000

9,800

██████████

Lowest

Closed-circuit fluid cooler

Yes

130,000

8,000

████████░░

Low

Hybrid cooler, wet only above 25 °C

Yes

155,000

2,500

███░░░░░░░

Medium

Adiabatic cooler with pads, wet on peak days

Yes

165,000

1,000

█░░░░░░░░░

Medium

Dry cooler, 45 °C liquid loop

No

208,000

0

░░░░░░░░░░

Highest

How Much Does Data Center Heat Rejection Cost per MW?

DC Market Insights estimates evaporative heat rejection equipment at about USD 95,000 per MW of IT load in a conventional hall and USD 140,000 per MW in an AI hall in 2025, or about USD 73 to USD 108 per kW of heat rejected, before installation at 18% of equipment value.

Year

Conventional hall (USD per MW of IT)

AI hall (USD per MW of IT)

Conventional (USD per kW of heat rejected)

Service (USD per evaporative-served MW a year)

2020

85,000

125,000

65

3,000

2025

95,000

140,000

73

3,500

2030

102,000

150,000

78

3,900

2035

108,000

156,000

83

4,200

What Is Driving Data Center Cooling Tower Demand?

Supplier capacity build for AI campuses: SPX Technologies raised its estimated annual data center revenue capacity to about USD 1.1 billion in July 2026, Baltimore Aircoil Company opened its first Latin American plant near Monterrey, Mexico, in May 2026, and EVAPCO announced an Indian subsidiary in August 2026.Lower electricity on grid-limited campuses: evaporative towers are far less energy intensive than dry alternatives, which matters where grid power, not water, is the binding constraint, especially in the United States, India and Southeast Asia.An installed base that more than doubles: each evaporative-served MW carries a rebuild cycle on fill, fans and gearboxes, and a maintenance contract worth USD 3,500 a year in 2025 rising to USD 4,200 in 2035.

What Could Shrink Cooling Tower Spending?

45 °C liquid cooling and dry coolers: if AI halls move faster to chiller-less dry cooling, the evaporative share of new AI capacity reaches 20% instead of 30% in 2035 and the market reaches USD 2.03 billion instead of USD 2.44 billion.Water disclosure laws: California AB 2469 and AB 2619 (signed 21 September 2026), Utah HB 76 (effective 6 May 2026), and EU Delegated Regulation 2024/1364 with the European Commission’s new data centre rating scheme with WUE classes all raise the political cost of open towers.

Where Are the Openings for Cooling Tower Suppliers?

The two largest openings are hybrid retrofits of existing towers and service contracts, together worth about USD 1.06 billion in 2035. Replacement and rebuild work reaches USD 537.41 million (22.0% of the market), and service and maintenance reaches USD 522.48 million as operators buy contracts that cover Legionella risk management under ASHRAE Standard 188 and water-use metering for the new disclosure laws.

Which Region Spends the Most on Data Center Cooling Towers?

North America leads with 44.0% of 2025 value (USD 494.66 million). Latin America is the fastest-growing region at 11.99% a year, and Europe is the slowest at 5.00% as cool climates and water reporting favour dry cooling.

Region

2025 (USD million)

Share 2025

2035 (USD million)

CAGR

2025 share

North America

494.66

44.0 %

976.70

7.04 %

████████████

Asia Pacific

314.78

28.0 %

817.99

10.02 %

████████░░░░

Europe

202.36

18.0 %

329.64

5.00 %

█████░░░░░░░

Middle East and Africa

73.07

6.5 %

195.34

10.33 %

██░░░░░░░░░░

Latin America

39.35

3.5 %

122.09

11.99 %

█░░░░░░░░░░░

Which Countries Buy the Most Data Center Cooling Towers?

The United States leads with USD 438.45 million in 2025, 39.0% of global value. India is the fastest-growing of the 12 largest countries at 14.82% a year, rising from USD 33.73 million to USD 134.30 million, because its new capacity sits in hot coastal hubs where evaporative heat rejection saves scarce grid power. Malaysia grows 13.73% a year on Johor’s campus pipeline.

Rank

Country

2025 (USD million)

Share 2025

2035 (USD million)

CAGR 2025-2035

1

United States

438.45

39.0 %

866.82

7.05 %

2

China

134.91

12.0 %

329.64

9.35 %

3

Japan

44.97

4.0 %

97.67

8.06 %

4

Germany

39.35

3.5 %

63.49

4.90 %

5

India

33.73

3.0 %

134.30

14.82 %

6

United Kingdom

33.73

3.0 %

53.72

4.76 %

7

Australia

28.11

2.5 %

65.93

8.90 %

8

Canada

28.11

2.5 %

61.04

8.06 %

9

Saudi Arabia

22.48

2.0 %

68.37

11.76 %

10

France

22.48

2.0 %

39.07

5.68 %

11

Brazil

20.24

1.8 %

61.04

11.67 %

12

Malaysia

16.86

1.5 %

61.04

13.73 %

How Could the 2035 Forecast Change?

Scenario

Evaporative share of new AI capacity, 2035

Price vs base

2035 value (USD million)

CAGR 2025-2035

Low

20 %

-5 %

2,034.15

6.11 %

Base

30 %

0 %

2,441.75

8.06 %

High

40 %

+5 %

2,882.14

9.87 %

Which Rules and Standards Apply to Data Center Cooling Towers?

CTI STD-201 thermal performance certification for cooling towers and fluid coolers.ANSI/ASHRAE/IES Standard 90.1 with Standard 90.4 as the data center compliance path.ASHRAE Standard 188 for Legionellosis risk management in building water systems.Delegated Regulation (EU) 2024/1364: water input and WUE reporting for data centres of 500 kW and above.EU data centre rating scheme with PUE and WUE classes, adopted 21 September 2026.California AB 2469 and AB 2619 (2026) and Utah HB 76 (2026) on data center water reporting.

Competitive Landscape and Recent Developments

SPX Technologies (Marley, Recold), Baltimore Aircoil Company and EVAPCO together hold about 50% of 2025 market value, according to DC Market Insights. Companies profiled include SPX Technologies, Baltimore Aircoil Company (Amsted Industries), EVAPCO, Kelvion, Güntner, Johnson Controls, Hamon, Enexio, Delta Cooling Towers, Brentwood Industries, Paharpur Cooling Towers, King Sun Industry, Liang Chi Industry and Kuken Kogyo.

In October 2026, Kelvion won a USD 800 million order for more than 1,000 dry coolers providing 5 GW of heat rejection for a United States AI campus.In September 2026, California’s governor signed AB 2469 and AB 2619 on data center water use, and the European Commission adopted a data centre rating scheme with WUE classes.In August 2026, SLB agreed to acquire Kelvion, whose largest end market is data centers.In July 2026, SPX Technologies raised its estimated annual data center revenue capacity to about USD 1.1 billion.In May 2026, Baltimore Aircoil Company opened its first Latin American plant near Monterrey, Mexico.

Frequently Asked Questions

What is the size of the Data Center Cooling Tower Market?

USD 1.12 billion in 2025 and USD 1.30 billion in 2026, projected to reach USD 2.44 billion by 2035 at an 8.06% CAGR, according to DC Market Insights.

What is a data center cooling tower?

Equipment that rejects data center heat by evaporating part of the condenser or process water into the air: open-circuit towers, closed-circuit fluid coolers and hybrid or adiabatic coolers, with their installation, rebuilds and service. Pure dry coolers and chillers are excluded.

How much water does a data center cooling tower use?

About 9,800 cubic metres per MW of IT load a year for an open tower, consistent with the 2.6 million gallons per MW that NVIDIA cites for evaporative designs. Hybrid and adiabatic coolers cut that by 75% to 90%.

Do AI data centers still use cooling towers?

Yes. 48% of new AI capacity used evaporative or hybrid heat rejection in 2025, falling to 30% by 2035 in the base case, as 45 °C liquid cooling lets many AI halls use dry coolers while grid-limited hot sites keep evaporative designs.

Which region leads the market?

North America, with 44.0% of 2025 value. Latin America grows fastest at 11.99% a year, and India is the fastest-growing large country at 14.82% a year.

Who are the leading data center cooling tower companies?

SPX Technologies (Marley), Baltimore Aircoil Company and EVAPCO, about 50% of 2025 value together. Kelvion, Güntner, Johnson Controls, Hamon, Enexio and Delta Cooling Towers also compete.

Methodology

DC Market Insights built the market bottom-up from evaporative-served MW of new and installed IT capacity, equipment value per MW for conventional and AI halls, installation at 18% of equipment value, rebuilds at 4% a year of the evaporative-served installed base, and service at USD 3,000 to USD 4,200 per MW a year. Results were checked against supplier-revenue ceilings and floors, including SPX Technologies’ disclosed HVAC revenue and data center capacity.

Download Sample Report – Data Center Cooling Tower Market

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CollectivIQ Introduces GigaBrain, Giving Enterprises a Shared Brain That Gets Smarter as Employees Work

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New Enterprise Intelligence Layer Turns the Collective Learnings of AI Agents Into Secure, Usable Organizational Knowledge

BOSTON, Oct. 21, 2026 /PRNewswire/ — CollectivIQ, the collective intelligence platform built to give employees more honest AI insights and digital teammates that put its intelligence to work, today announced the availability of GigaBrain, a new shared intelligence layer that enables organizations to capture, connect, and use the knowledge accumulated by employees and their Digital Direct Reports (DDRs), which are specialized AI teammates that work for people much like human direct reports do. Every company has valuable knowledge that lives outside its formal systems, across various tools, residing in employees’ heads, embedded in conversations, and lodged in disparate company applications. GigaBrain is designed to make that collective intelligence available to the organization and its employees.

As employees work with their Digital Direct Reports, those AI teammates develop context about their work, including projects, processes, responsibilities, relationships, and preferences. With GigaBrain, those individual learnings can contribute to a shared enterprise memory, allowing knowledge developed in one part of an organization to make AI more useful across the business. The result is an enterprise AI environment that gets smarter through use. Rather than requiring employees to repeatedly find, upload or explain the same information, GigaBrain gives employees and their Digital Direct Reports access to relevant organizational context when they need it.

When a sales representative’s DDR learns the intricacies of a customer’s procurement process, including approval requirements, key decision-makers, and purchasing timelines, that knowledge can automatically become available to other team members, subject to appropriate access permissions. When the customer reaches out for help, the team will already have the context needed to navigate the relationship effectively, without asking the customer to repeat information or relying on a manual handoff.

“Companies are collectively spending billions to bring intelligence to their employees, but very little of that investment makes the company itself smarter,” said John Davie, CEO of CollectivIQ. “The breakthrough isn’t just giving every employee an AI teammate, it’s making sure what those employees and AI teammates learn becomes an advantage for the entire organization. GigaBrain turns everyday work into intelligence that compounds across the enterprise.”

While enterprise AI platforms such as Microsoft Copilot and Glean help employees access organizational information, GigaBrain is designed to capture knowledge that emerges through employees’ day-to-day interactions with their DDRs, including insights that may never be formally documented. GigaBrain creates an organizational knowledge layer that can connect what employees and their Digital Direct Reports learn through everyday work, giving AI access to relevant internal context alongside the broader knowledge available from large language models.

GigaBrain was built to provide a source of enterprise knowledge that Digital Direct Reports can draw upon as they work, including the ability to trace information back to its source, giving employees greater visibility into where organizational knowledge came from, and helping AI work from relevant company context. Employees do not need to manually document every useful insight for the system to become more valuable. As they collaborate with their Digital Direct Reports, relevant knowledge can become part of the enterprise intelligence available to other authorized AI teammates.

GigaBrain is also designed for the realities of enterprise information governance, as employees can use an incognito mode when working with information that should not contribute to shared organizational memory, giving users a way to keep sensitive or confidential interactions out of GigaBrain.

GigaBrain expands CollectivIQ’s vision for Digital Direct Reports beyond individual AI productivity, allowing the knowledge developed through that work to become part of a broader organizational intelligence layer. Together, they give companies a foundation for AI that does more than answer questions. CollectivIQ’s ecosystem can learn how an organization works, retain what it learns and make that knowledge useful across the enterprise.

GigaBrain is available through the CollectivIQ platform. For more information, visit www.collectiviq.ai.

About CollectivIQ

CollectivIQ is the collective intelligence platform built to give employees more accurate AI insights and teammates that put its intelligence to work. Founded by the leadership team behind Buyers Edge Platform, CollectivIQ was built to bring accountability, action, and economic alignment to enterprise AI adoption. Learn more at www.collectiviq.ai.

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Pactum Launches Intake Agent, Cutting Purchase Request Cycle Time by 90%

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New AI agent replaces complicated purchase forms and repeated follow-ups by completing and checking every request before it is submitted, inside Microsoft Teams, Coupa, and SAP Ariba.

MOUNTAIN VIEW, Calif., Oct. 21, 2026 /PRNewswire/ — Pactum, the most advanced agentic AI platform for enterprise autonomous procurement execution, today announced the launch of its Intake Agent, which lets employees describe what they need to buy in plain language. The agent turns each request into a complete, correctly coded requisition and checks it against company buying policies before it is submitted.  Available now in Microsoft Teams, Coupa, and SAP Ariba, the Intake Agent connects with Pactum’s other agents to enable end-to-end autonomous indirect procurement. A purchase can draw on an existing contract or move to autonomous sourcing and negotiation, with a human buyer handling requests that require judgment.

The launch extends Pactum’s growing portfolio of AI agents to the start of indirect procurement, covering purchases such as software, office equipment, and professional services. It brings Pactum’s co-founders’ vision of procurement run with AI agents from the first request through sourcing and negotiation into operation. Procurement teams set the buying rules once, and the agent applies them to every request, whatever its value.

“Procurement teams can now run indirect procurement with full autonomy while remaining in control and managing the exceptions,” said Kaspar Korjus, Co-Founder and CEO of Pactum. “Our Intake Agent helps resolve questions earlier so requests can move forward with less back-and-forth and teams can focus on the decisions that need their expertise.”

For employees, finding an approved supplier or selecting the right accounting code can require expertise across procurement, finance, operations, and IT teams. Missing or incorrect information can lead to rejected requisitions and repeated follow-ups, leaving buyers to focus on correcting forms instead of focusing on supplier relationships and commercial decisions. Review queues can stretch from days to weeks.

With Pactum Intake, employees describe what the business needs, whether goods or services of any complexity, and can provide supporting documents such as a supplier quote. The agent uses the request and relevant documents to identify the best procurement category and complete the accounting and supplier details. It asks only the follow-up questions needed to complete the requisition. Once the request is checked, it is handed off to another Pactum digital worker to autonomously source and negotiate for better pricing and terms where required.

“Building software that assists procurement professionals is relatively easy. Building software that runs the whole process on its own, from the first request to the final purchase, is much harder,” said Kristjan Korjus, Co-Founder and Chief Scientist at Pactum. “It is the difference between driver assistance and a car with no one behind the wheel. Most procurement AI still needs a buyer at the wheel for every request. Our AI agents take the request all the way to the purchase on their own, and it is remarkable to watch them pass the work from one agent to the next.”

The launch follows Pactum’s Requisition Alignment Agent surpassing one million requisition checks, which validates purchase requests against company buying policies, existing contracts, and approved suppliers. Intake builds on this foundation in policy enforcement by connecting employee requests with agents that carry out sourcing and negotiation.

For more information about Pactum Intake, visit https://pactum.com/procurement-agents/intake.     

About Pactum:

Since 2019, Pactum has been leading the shift to autonomous procurement. Its AI agents check every purchase request against a company’s policies, contracts and approved suppliers, source and negotiate with suppliers in more than 40 languages, and work inside Coupa and SAP Ariba. Pactum agents are relied on by more than 60 of the world’s largest enterprises. To learn more, visit www.pactum.com.

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Crush Security Launches Crush Dollar Exposure, Turning Cyber Risk Into Dollars and Showing Which Security Investments Reduce It Most

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New financial risk intelligence capability uses FAIR-informed modeling, Monte Carlo analysis and security data to help CISOs and CFOs quantify cyber exposure, prioritize remediation and communicate financial risk to executive leadership.

SCOTTSDALE, Ariz., Oct. 21, 2026 /PRNewswire/ — Crush Security today announced the launch of Crush Dollar Exposure, a new capability within its cybersecurity intelligence platform that translates cyber risk into financial exposure and helps organizations identify which security improvements can deliver the greatest reduction in potential financial loss.

For years, cybersecurity teams have measured their environments through vulnerabilities, risk scores, compliance percentages and control gaps. While valuable to security operations, those measurements often fail to answer the fundamental questions that executives and boards need answered:

How much could our cybersecurity weaknesses cost the business, and where should we invest to reduce that exposure?

Crush Dollar Exposure is designed to answer those questions by connecting an organization’s security posture, control coverage, threat intelligence and industry financial loss data to a quantitative view of cyber risk. The result is a financial perspective that enables security and business leaders to evaluate potential losses, compare remediation priorities and make more informed investment decisions.

From Technical Risk Scores to Financial Decisions

Traditional cybersecurity assessments often produce long lists of findings ranked by technical severity. But the most technically severe vulnerability is not necessarily the one that represents the greatest potential financial loss to the organization.

Crush Dollar Exposure changes the decision-making process by evaluating security gaps through their estimated contribution to financial risk. The capability provides four principal measurements:

Annualized Financial Exposure: An estimate of potential annual cyber losses, expressed in dollars.Financial Exposure Relative to Revenue: A view of modeled cyber exposure in relation to the organization’s annual revenue, providing business context.Value-at-Risk Analysis: Potential loss thresholds at selected probability levels, supported by loss-exceedance curves that illustrate the range of possible financial outcomes.Financially Prioritized Remediation: Security control gaps ranked by their modeled contribution to financial exposure, helping teams identify where remediation may reduce the most risk.

Rather than simply reporting that a security control is missing or a vulnerability is critical, Crush Dollar Exposure helps organizations understand the potential financial consequences and prioritize corrective action accordingly.

Connecting Every Security Gap to Business Impact

One of the capability’s key differentiators is its ability to connect security control weaknesses to modeled loss scenarios and financial consequences.

For example, a security team evaluating investments in identity protection, endpoint security and vulnerability remediation can use the model to determine which weaknesses contribute most significantly to estimated financial exposure. This allows security leaders to move beyond asking which problem is technically most severe and begin asking which investment is likely to provide the greatest financial risk reduction.

The analysis also connects control gaps to underlying loss scenarios, helping organizations understand how multiple weaknesses may contribute to the same business risk. For CFOs and executive teams, this provides a more financially grounded way to evaluate cybersecurity spending. For CISOs, it creates a defensible framework for explaining security priorities and communicating their potential business impact.

Transparent, Reproducible Risk Modeling — Not a Black-Box AI Score

Crush Dollar Exposure uses a quantitative methodology informed by the Factor Analysis of Information Risk (FAIR) framework and Monte Carlo simulation to model possible financial losses.

The methodology incorporates security control coverage, industry-relevant threat activity, recognized adversary techniques, organizational characteristics and established financial loss reference data.

Unlike opaque risk-scoring approaches, the capability is designed to make the assumptions, data inputs and modeled loss scenarios underlying its financial estimates visible and reviewable. Although Crush Security’s broader platform includes Cassandra, its AI-powered security advisor, the financial risk calculations themselves rely on defined quantitative modeling rather than generative AI.

The capability distinguishes between uncertainty in modeled financial outcomes and confidence in the quality of supporting data, helping executives understand both the estimated exposure and the limitations of the underlying analysis. This transparency is intended to support repeatable analysis, auditability and more defensible conversations with boards, regulators and financial stakeholders.

Giving CISOs and CFOs a Common Language

“Cybersecurity leaders are constantly asked to justify their budgets, but we’re still presenting information to boards that doesn’t directly answer the questions they’re asking,” said Josh Jones, CEO and Co-Founder of Crush Security. “Boards don’t just want to know how many vulnerabilities you have or how many security tools you’ve deployed. They want to understand what the risk could cost the business, where their money is going, and whether those investments are making a measurable difference.”

“With Crush Dollar Exposure, we’re connecting cybersecurity decisions to financial outcomes. Our goal is to give every CISO the ability to walk into a board meeting and explain their organization’s estimated financial exposure, identify the gaps driving it, and show which actions have the greatest potential to reduce that risk.” -Joshua Jones, CEO-

Built on the Crush Security Intelligence Platform

Crush Dollar Exposure extends Crush Security’s intelligence platform, which brings together vendor, control, compliance and threat data to support security investment decisions.

Powered by Cassandra, the platform helps organizations identify coverage gaps, compare technology and vendors, and optimize cybersecurity spending.

Risk calculations are performed within each customer’s data environment, with customer-specific information remaining within its designated security boundary. Anonymized and aggregated industry reference information supports comparative risk modeling.

Availability

Crush Dollar Exposure is available now within the Crush Security platform. Organizations interested in quantifying their financial cyber exposure, evaluating remediation priorities or scheduling a demonstration can visit www.CrushSecurity.com. Access information is available directly from Crush Security.

About Crush Security

Crush Security is a veteran-owned cybersecurity technology and advisory company headquartered in Scottsdale, Arizona.

Its proprietary intelligence platform, advisory services and cybersecurity procurement data help customers make data-driven technology purchasing decisions leveraging Crush Security’s resell capabilities.

Cassandra, its AI-powered advisor, unifies security, vendor and compliance intelligence to identify gaps, optimize investments, quantify risk and evaluate solutions to shorten the decision time and accuracy for each project.

Crush Security’s core intelligence platform is currently included at no separate subscription cost with eligible customer engagements.

Website: www.CrushSecurity.com

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SOURCE Crush Security Group Inc

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