Johnson Controls launches series of thermal management reference design guides for gigawatt-scale AI data centers

Johnson Controls (NYSE: JCI) launched a Reference Design Guide Series for 1 Gigawatt AI data centers on Feb 2, 2026.

Rhea-AI Summary

Johnson Controls (NYSE: JCI) launched a Reference Design Guide Series for 1 Gigawatt AI data centers on Feb 2, 2026. The series maps full thermal chains for water-cooled, air-cooled and absorption chiller architectures and begins with a water-cooled chiller plant blueprint.

The guides provide sizing for 220MW compute quadrants, TCS loop conditions, integration with CRAHs, CDUs and YORK centrifugal chillers, and promote options for zero water consumption, high-temperature TCS readiness, NVIDIA DSX alignment and improved PUE/WUE across diverse climates and elevations.

Argus Feb 2 session

+3.12% close to close Open Argus

Details

News Market Reaction – JCI

In the Feb 2 session, JCI gained 3.12%, reflecting a moderate positive market reaction.

Data tracked by StockTitan Argus on the day of publication.

Market Context

This announcement introduces JCI’s Reference Design Guide Series for 1 Gigawatt AI data centers, det...

Analysis

This announcement introduces JCI’s Reference Design Guide Series for 1 Gigawatt AI data centers, detailing water-cooled thermal architectures and future air-cooled and absorption chiller designs. It emphasizes zero-water heat rejection, GPU-ready high-temperature loops and alignment with NVIDIA’s DSX architecture. In context of earlier AI initiatives in OpenBlue and Sensormatic analytics, investors may monitor how effectively JCI converts these large-scale AI factory designs into tangible orders and whether future earnings calls quantify adoption and efficiency gains.

Key Figures

AI data center scale: 1 Gigawatt Compute quadrant size: 220MW Energy spend reduction: 30% +5 more

AI data center scale

1 Gigawatt

Reference Design Guide Series target capacity for AI data centers

Compute quadrant size

220MW

Sizing guidance for compute quadrants in the new thermal architecture

Energy spend reduction

30%

Potential reduction cited for OpenBlue Enterprise Manager AI features

Maintenance cost reduction

20%

Potential maintenance savings from OpenBlue AI capabilities

Space optimization

10%

Improved space utilization linked to OpenBlue AI

Share repurchase authorization

64,000,000 shares

Maximum market purchase authorization in 2026 proxy statement

Audit fees 2025

$24.8M

PwC audit and related fees in fiscal 2025

Audit fees 2024

$25.8M

PwC audit and related fees in fiscal 2024

Previous AI Reports

3 past events · Latest: Dec 09

Same Type 3 events

1. Dec 09

   AI retail analytics

   24h Move

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   Launch of AI-powered in-store guest behavior analytics using sensors and video.

2. Jul 08

   AI traffic analytics

   24h Move

   -0.5%

   Enhanced retail traffic analytics with Re-ID and deep learning AI for shopper insights.

3. Nov 12

   OpenBlue AI expansion

   24h Move

   -1.7%

   Expanded AI features in OpenBlue for energy, maintenance, and space optimization.

24h Move is the share-price change in the day after each event; other market factors may also have contributed.

Key Terms

pue, technology cooling system (tcs), gpu, coolant distribution units (cdus)

4 terms

pue technical

"outlining how to achieve industry-leading energy and water efficiency (PUE and WUE)"

Power Usage Effectiveness (PUE) measures how efficiently a data center uses energy by comparing total facility power to the power used by the computing equipment; a PUE of 1.0 means all power goes to servers, while higher numbers indicate more energy spent on cooling and infrastructure. Investors care because lower PUE usually means lower operating costs and better environmental performance, similar to choosing a fuel‑efficient car to save money and reduce waste.

technology cooling system (tcs) technical

"including Technology Cooling System (TCS) loops supporting next- generation GPUs"

A technology cooling system (TCS) is the set of equipment and processes that remove heat from electronic hardware such as servers, data centers, telecom gear, and other high-power devices to keep them within safe operating temperatures. Like a car radiator or home air conditioner for machines, it matters to investors because cooling affects reliability, energy costs, capacity limits and lifespan of assets—impacting operating expenses, uptime and the need for future capital spending.

gpu technical

"Technology Cooling System (TCS) loops supporting next- generation GPUs"

A GPU (graphics processing unit) is a specialized computer chip designed to handle many calculations at once, originally for rendering images and video but now widely used for tasks like artificial intelligence, data analysis and high-performance computing. Investors watch GPU demand and prices because strong sales often signal growth for chip makers and their customers, affect profit margins and capital spending, and can forecast wider trends in gaming, AI adoption and cloud services.

coolant distribution units (cdus) technical

"fan coil walls, coolant distribution units (CDUs) and high efficiency YORK"

Coolant Distribution Units (CDUs) are devices that manage and direct the flow of cooling liquids in large data centers or industrial systems. They help keep equipment from overheating by efficiently distributing coolant to where it's needed, ensuring smooth operation and preventing damage, much like a thermostat controls temperature in your home.

AI-generated analysis. How Rhea-AI works. Not financial advice.

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Comprehensive guides address water-cooled, air-cooled and absorption chiller use cases, integrated with advanced building controls, for next-generation AI factories

MILWAUKEE, Feb. 2, 2026 /PRNewswire/ -- Johnson Controls (NYSE: JCI), the global leader in smart, healthy and sustainable buildings, today announced the launch of its Reference Design Guide Series for 1 Gigawatt AI data centers. Each guide in the series maps the full thermal chain, offering cooling architectures tailored to diverse compute densities, geographies and elevations. The series begins with a detailed blueprint for water-cooled chiller plants with future guides to address air-cooled and absorption chiller solutions.

As AI transforms industries, the scale and complexity of data center infrastructure is rapidly evolving. The ability to efficiently manage thermal loads at gigawatt scale is now a critical enabler for AI innovation, and the industry faces mounting pressure to deliver facilities that are not only high-performing, but also sustainable and future-ready. Johnson Controls' Reference Design Guide Series responds to this challenge by outlining how to achieve industry-leading energy and water efficiency (PUE and WUE) while maintaining flexibility to scale across diverse climates and operational requirements. 

The guide outlines a complete thermal architecture supporting both liquid and air- cooled- IT loads through integrated computer room air handlers (CRAHs), fan coil walls, coolant distribution units (CDUs) and high efficiency YORK centrifugal chillers. It provides- detailed sizing guidance for 220MW compute quadrants and defines temperature and operating conditions across all major facility loops, including Technology Cooling System (TCS) loops supporting next- generation GPUs. 

Key outcomes enabled by the updated design include: 

• Zero Water Consumption: A fully water free heat rejection process using dry coolers, reducing operational costs and advancing sustainability objectives.
• Future Ready- Thermal Flexibility: High -temperature TCS loop readiness ensures compatibility with forthcoming GPU architectures.
• Optimized High Density- AI Performance: Alignment with NVIDIA DSX reference architecture  enables scalable deployment of 1-GW-class AI Factories.
• Energy Efficient- Operation: Elevated condenser water temperatures, bifurcated loops and YORK high-lift chillers deliver industry-leading PUE and improved annualized efficiency. 

"AI Factories are production facilities — the places where intelligence is manufactured at an industrial scale," said Austin Domenici, vice president & general manager, Johnson Controls Global Data Center Solutions. "By supporting the NVIDIA DSX reference architecture and improving water and energy efficiency in the cooling process while maintaining high temperature- loop compatibility, our Reference Design Guide equips customers to deploy gigawatt-scale AI infrastructure that is scalable, repeatable, resilient and sustainable." 

Learn more about Johnson Controls's Reference Guide Series at www.johnsoncontrols.com/industries/data-centers/reference-designs.

MEDIA CONTACTS: 
Louise Colledge
+4179 414 4996
Email: louise.colledge@jci.com

Kari Pfisterer
Direct: +1 414-217-1488
Email: kari.b.pfisterer@jci.com

About Johnson Controls:

At Johnson Controls (NYSE:JCI), we transform the environments where people live, work, learn and play. As the global leader in smart, healthy and sustainable buildings, our mission is to reimagine the performance of buildings to serve people, places and the planet. 

Building on a proud history of nearly 140 years of innovation, we deliver the blueprint of the future for industries such as healthcare, schools, data centers, airports, stadiums, manufacturing and beyond through OpenBlue, our comprehensive digital offering. 

Today, Johnson Controls offers the world`s largest portfolio of building technology and software as well as service solutions from some of the most trusted names in the industry. 

Visit johnsoncontrols.com for more information and follow @Johnsoncontrols on social platforms.

Johnson Controls - ©2025 - All Rights Reserved

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SOURCE Johnson Controls International plc

FAQ

AI-generated questions and answers. How Rhea-AI works. Not financial advice.

What does Johnson Controls' (JCI) 1 GW Reference Design Guide enable for AI data centers?

It provides complete thermal architectures and sizing for gigawatt-scale deployments, including 220MW compute quadrants. According to Johnson Controls, the guide maps full thermal chains, integrates CRAHs/CDUs/YORK chillers, and supports high-temperature TCS loops for next-generation GPU architectures.

How does the JCI reference guide address water use in 1 GW AI data centers?

The guide includes a zero-water consumption heat rejection approach using dry coolers to reduce water use. According to Johnson Controls, this option enables fully water-free rejection processes to lower operational costs and support sustainability objectives in large AI facilities.

Does Johnson Controls' JCI guide support NVIDIA DSX and high-density AI architectures?

Yes— the guide aligns thermal designs with NVIDIA DSX reference architecture to support high-density AI factories. According to Johnson Controls, this alignment enables scalable, repeatable deployment of 1-GW-class AI facilities and compatibility with NVIDIA-focused system designs.

What energy-efficiency measures does Johnson Controls (JCI) recommend for gigawatt AI facilities?

Recommended measures include elevated condenser temperatures, bifurcated loops and YORK high-lift chillers to improve PUE. According to Johnson Controls, these design choices aim to deliver industry-leading PUE and annualized efficiency for large-scale AI cooling systems.

When will air-cooled and absorption chiller guides be available from Johnson Controls (JCI)?

The company says the series begins with a water-cooled blueprint and will follow with air-cooled and absorption chiller guides. According to Johnson Controls, future guides will address those use cases to cover diverse geographies and operational requirements.