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Predictive Maintenance (PDM) Market to grow by USD 33.76 Billion from 2024-2028, driven by AI and cloud adoption in SMEs – Technavio

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NEW YORK, Nov. 27, 2024 /PRNewswire/ — Report with the AI impact on market trends – The global predictive maintenance (PDM) market  size is estimated to grow by USD 33.76 billion from 2024-2028, according to Technavio. The market is estimated to grow at a CAGR of  39%  during the forecast period. Increased adoption of advanced analytics by SMES owing to rise in cloud computing is driving market growth, with a trend towards proliferation of advanced technologies, AI, and IoT. However, lack of expertise and technical knowledge  poses a challenge.Key market players include Augury Inc., Avnet Inc., C3.ai Inc, Dell Technologies Inc., Deutsche Telekom AG, Fortive Corp., General Electric Co., Hitachi Ltd., Honeywell International Inc., International Business Machines Corp., PTC Inc., RapidMiner Inc., Reliability Solutions sp. Z o.o., Robert Bosch GmbH, Rockwell Automation Inc., SAP SE, SAS Institute Inc., Schneider Electric SE, Siemens AG, and Warwick Analytics Services Ltd..

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Forecast period

2024-2028

Base Year

2023

Historic Data

2017 – 2021

Segment Covered

Component (Solutions and Service), Deployment (On-premises and Cloud), and Geography (North America, Europe, APAC, South America, and Middle East and Africa)

Region Covered

North America, Europe, APAC, South America, and Middle East and Africa

Key companies profiled

Augury Inc., Avnet Inc., C3.ai Inc, Dell Technologies Inc., Deutsche Telekom AG, Fortive Corp., General Electric Co., Hitachi Ltd., Honeywell International Inc., International Business Machines Corp., PTC Inc., RapidMiner Inc., Reliability Solutions sp. Z o.o., Robert Bosch GmbH, Rockwell Automation Inc., SAP SE, SAS Institute Inc., Schneider Electric SE, Siemens AG, and Warwick Analytics Services Ltd.

Key Market Trends Fueling Growth

Predictive Maintenance (PDM) is a cutting-edge business trend revolutionizing equipment maintenance. It uses condition-based strategies to predict and prevent equipment failure, moving beyond time- and reactive-based methods. PDM leverages various technologies like electromagnetic radio fields, NFC chips, and sensor devices to gather real-time data. Devices such as vibration meters and acoustic analysis tools help identify potential issues. Machine learning algorithms analyze sensor data to predict faults, enabling action before human error or pocket dials cause problems. NFC technology facilitates transactions for maintenance work, while smart posters and maintenance software like CMMS, FTMaintenance, and mobile CMMS features streamline work orders and communication between maintenance staff, machine operators, and technicians. Predictive maintenance saves costs by minimizing downtime and extending asset life. It’s being adopted in diverse industries, from coal preparation plants to fleet maintenance and building management. Predictive maintenance is the future, combining advanced technologies like machine learning, computer-based modeling, and analytics tools with wireless internet connections to provide actionable insights. Meteorologists and Doppler radars, even satellites, contribute to predictive maintenance by providing weather data and environmental conditions. Predictive maintenance is transforming maintenance work, making it more efficient, effective, and proactive. 

Predictive maintenance (PdM) is a proactive approach to equipment maintenance that uses data analysis and machine learning algorithms to predict potential failures before they occur. By analyzing historical data and current performance indicators, PdM solutions can identify patterns and trends that may indicate an impending issue. The acceptance of advanced technologies like AI, machine learning, blockchain, cloud computing, and big data is driving the adoption of PdM in various industries. These technologies enable real-time monitoring, predictive analytics, and automated maintenance, leading to increased efficiency, cost savings, and improved asset performance. Billions of dollars are being invested in research and development to further enhance the capabilities of these technologies, making PdM an essential component of modern maintenance strategies. 

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Market Challenges

Predictive Maintenance (PDM) is a cutting-edge technology that uses machine learning and sensor data to predict equipment failures before they occur. However, implementing PDM comes with challenges. Electromagnetic radio fields from sensors can interfere with NFC chips in devices, leading to transaction errors. Human error, such as pocket dialing maintenance work orders, can also cause delays. Distance and battery life are concerns for wireless sensor devices. PDM relies on condition-based maintenance using sensor devices and real-time data. Time-based maintenance and reactive maintenance are outdated methods. Maintenance software like CMMS, FTMaintenance, and mobile CMMS features play a crucial role in managing work orders and dispatching maintenance staff. Vibration analysis, acoustic analysis, and infrared analysis are common condition-monitoring techniques. Baselines and work orders help maintenance technicians identify potential issues. Machine operators should be trained to use condition-monitoring devices like vibration meters. Predictive algorithms use data from sensors, computer-based modeling, and analytics tools to predict faults. Predictive maintenance is essential for fleet maintenance and building maintenance. Doppler radars, satellites, and meteorologists provide additional data for predictive maintenance in extreme environments. Challenges include ensuring accurate sensor data and a reliable wireless internet connection. Maintenance staff should be trained to use predictive maintenance software and understand the importance of preventive maintenance. Collaboration between maintenance technicians, machine operators, and data analysts is crucial for successful implementation of predictive maintenance.Predictive maintenance (PdM) is a crucial business strategy that helps enterprises prevent equipment failure through corrective or scheduled maintenance. However, the implementation of PdM comes with challenges. The lack of skilled labor and specialized knowledge in condition monitoring and predictive analytics is a significant hurdle. This complex process requires extensive domain expertise for micro-segmentation deployment. As historical data grows and PdM use cases expand, the complexity of the models increases, leading to management overhead and inefficiencies. To overcome these challenges, extensive training and specialized resources are necessary for successful PdM adoption.

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Segment Overview 

This predictive maintenance (pdm) market report extensively covers market segmentation by

Component 1.1 Solutions1.2 ServiceDeployment 2.1 On-premises2.2 CloudGeography 3.1 North America3.2 Europe3.3 APAC3.4 South America3.5 Middle East and Africa

1.1 Solutions-  Predictive maintenance (PdM) solutions are integrated with new or existing machinery infrastructure to monitor machine health and identify early signs of deterioration. This integration ensures a good return on investment (ROI) and helps organizations meet sustainability goals by enabling remote machine monitoring worldwide. By keeping assets in optimal working condition and available at all times, PdM solutions increase asset life expectancy and reduce high maintenance costs. The energy and utilities, manufacturing, healthcare, aerospace and defense, and automotive sectors are among those driving the growth of the global PdM market due to their increasing adoption of PdM solutions. These industries use sensors and equipment to generate data for analysis, which is then transferred to the cloud for analysis and monitoring via gateways. The cloud provides computing, data storage, and analytics reporting, while management software serves as an interface for users to handle equipment conditions from anywhere. The use of PdM solutions is expected to increase significantly, leading to market growth during the forecast period. These solutions help improve product quality and process efficiency by analyzing data generated from equipment and sensors. Gateways serve as data transporters and translators, while cloud services offer shared software resources for computing, data storage, and analytics reporting. Management software acts as an interface for users to monitor equipment conditions in real-time.

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Research Analysis

Predictive maintenance (PDM) is a proactive approach to equipment maintenance using real-time data analysis and various sensor devices. Electromagnetic radio fields and NFC chips are among the technologies utilized in PDM. NFC transactions enable data exchange between devices, providing distance information for condition-based maintenance. Human error can be minimized through smart posters and NFC technology, triggering action when maintenance is required. PDM employs NFC technology to monitor assets, collecting data for analysis in real-time. This information helps identify potential equipment failure before it occurs, moving away from time-based and reactive maintenance. Maintenance software, such as CMMS, uses baselines and work orders to manage maintenance tasks, with machine operators and maintenance staff receiving notifications for necessary actions. Vibration analysis, acoustic analysis, and infrared analysis are common methods used in PDM. A centrifugal pump motor in a coal preparation plant, for instance, can be monitored using a vibration meter to detect anomalies and prevent costly downtime. By leveraging these advanced technologies and techniques, predictive maintenance significantly improves equipment reliability and reduces maintenance costs.

Market Research Overview

Predictive Maintenance (PDM) is a cutting-edge technology that utilizes various sensors, condition-monitoring devices, and advanced analytics tools to predict equipment failures before they occur. This proactive approach to maintenance reduces downtime, lowers maintenance costs, and increases asset productivity. Electromagnetic radio fields, NFC chips, and sensor devices collect real-time data on machine performance, temperature, vibration, and other key indicators. Machine learning algorithms analyze this data to identify patterns and anomalies, predicting potential failures and suggesting preventive actions. NFC technology enables wireless transactions for maintenance work orders, while machine operators and maintenance staff receive notifications for required actions. Distance learning and smart posters provide training and instructions for maintenance technicians. Predictive maintenance applications range from centrifugal pump motors in coal preparation plants to fleet maintenance and building systems. Vibration analysis, acoustic analysis, infrared analysis, and computer-based modeling are essential tools for predictive maintenance. Predictive algorithms, wireless internet connection, and CMMS software facilitate efficient and effective maintenance work. Meteorologists, Doppler radars, and satellites provide external data for predicting weather-related maintenance needs.

Table of Contents:

1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation

ComponentSolutionsServiceDeploymentOn-premisesCloudGeographyNorth AmericaEuropeAPACSouth AmericaMiddle East And Africa

7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Trends
10 Company Landscape
11 Company Analysis
12 Appendix

About Technavio

Technavio is a leading global technology research and advisory company. Their research and analysis focuses on emerging market trends and provides actionable insights to help businesses identify market opportunities and develop effective strategies to optimize their market positions.

With over 500 specialized analysts, Technavio’s report library consists of more than 17,000 reports and counting, covering 800 technologies, spanning across 50 countries. Their client base consists of enterprises of all sizes, including more than 100 Fortune 500 companies. This growing client base relies on Technavio’s comprehensive coverage, extensive research, and actionable market insights to identify opportunities in existing and potential markets and assess their competitive positions within changing market scenarios.

Contacts

Technavio Research
Jesse Maida
Media & Marketing Executive
US: +1 844 364 1100
UK: +44 203 893 3200
Email: media@technavio.com
Website: www.technavio.com/

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SOURCE Technavio

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Horizon Petroleum Ltd. Announces Proposed $2,000,000 Secured Grid Promissory Note and Close of Its Shares for Debt Settlement

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/NOT FOR DISTRIBUTION TO U.S. NEWSWIRE SERVICES OR FOR DISSEMINATION IN THE UNITED STATES OF AMERICA. ANY FAILURE TO COMPLY WITH THIS RESTRICTION MAY CONSTITUTE A VIOLATION OF U.S. SECURITIES LAWS./

CALGARY, AB, Oct. 22, 2026 /CNW/ — Horizon Petroleum Ltd. (the “Company” or “Horizon”) (TSXV: HPL) (FRA: HPM) (Tradegate: HPM) is pleased to announce that it intends to enter into a secured grid promissory note (the “Promissory Note”) with Wilco Investments Ltd., a company controlled by Trevor Williams who is a director of the Company, in the aggregate principal amount of up to CAD $2,000,000. 

The proceeds will be used to make deposits on three generators and on production facilities. The generators will have a combined generating capacity of 3 megawatts. This equipment is Horizon’s next investment in its gas to power strategy for its Lachowice natural gas development in Poland.

The Promissory Note will bear interest from the applicable issuance date at 12% per annum. The Promissory Note and accrued interest will be due on December 31, 2026 (the “Maturity Date”). The Maturity Date may be extended by mutual agreement between the parties. The Promissory Note may be prepaid in whole or in part at any time without penalty. The Promissory Note will be immediately due and payable upon completion by the Company of a financing of equity or debt of CAD $5,000,000 or more. The Promissory Note will be secured by Horizon’s electrical generating equipment in Poland.

The closing date is anticipated to be October 22, 2026.

Entering into the Promissory Note and the advance of funds thereunder are subject to the satisfaction of customary conditions, including the approval of the TSXV.

As Trevor Williams is a director of the Company, the Promissory Note will constitute a “related party transaction” pursuant to Multilateral Instrument 61-101 – Protection of Minority Security Holders in Special Transactions (“MI 61-101”). The Company intends to rely on the exemption from the formal valuation requirement pursuant to section 5.5(b) of MI 61-101 as the Company does not have securities listed on a specified market, and on the exemption from the minority shareholder approval requirement pursuant to section 5.7(1)(a) of MI 61-101 as the fair market value of the Promissory Note will not exceed 25% of the Company’s market capitalization.

In addition, the Company announces that it has completed an agreement to settle a total of CAD $524,000 of the Company’s debt (the “Debt”) with certain arm’s length and non-arm’s length parties (the “Shares for Debt Settlement”). The Debt payable to directors and officers of the Company who are Insiders (as such term is defined under the policies of the TSXV) is an aggregate of CAD $465,000 and the Company will settle the same by issuing to such parties 2,657,143 common shares at a deemed price of CAD $0.175 per common share. The Debt payable to arm’s length service providers is an aggregate of CAD $59,000 and the Company will settle the same by issuing to such parties 337,143 common shares at a deemed price of $0.175 per common share. 

The Shares for Debt Settlement was approved by disinterested shareholders at the shareholder meeting held on July 28, 2026. All securities issued in connection with the Shares for Debt Settlement will be subject to a statutory four-month hold period in accordance with applicable securities legislation. 

The Company has received final approval for the Shares for Debt Settlement from the TSXV. 

The Company relied on exemptions from the formal valuation and minority approval requirements of sections 5.5(b) and 5.7(1)(a) of MI 61-101 in respect of such insider participation in the Shares for Debt Settlement, based on a determination that fair market value of the participation by insiders did not exceed 25% of the market capitalization of Horizon, as determined in accordance with MI 61-101.

About Horizon Petroleum Ltd.

Calgary-based Horizon Petroleum Ltd. is focused on the appraisal and development of natural gas resources and clean energy opportunities in Europe, with the objective of contributing to European energy independence and security. Horizon is advancing its Polish natural gas assets through a technically focused, phased development strategy designed to unlock their commercial potential. Horizon’s management team and Board of Directors comprise oil and gas, business and finance professionals with significant international experience.

Neither the TSX Venture Exchange nor its Regulation Services Provider (as that term is defined in the policies of the TSX Venture Exchange) accepts responsibility for the adequacy or accuracy of this release.

This press release contains “forward-looking statements” or “forward-looking information” (collectively referred to herein as “forward-looking statements”) within the meaning of applicable securities legislation. Such forward-looking statements include, without limitation, forecasts, estimates, expectations and objectives for future operations that are subject to a number of assumptions, risks and uncertainties, many of which are beyond the control of Horizon. Forward-looking statements are statements that are not historical facts and are generally, but not always, identified by the words “expects”, “plans”, “anticipates”, “believes”, “intends”, “estimates”, “projects”, “potential” and similar expressions, or that events or conditions “will”, “would”, “may”, “could” or “should” occur or be achieved. This press release contains forward-looking statements pertaining to, among other things, the Company entering into the Promissory Note, the terms of the Promissory Note, the anticipated closing date, reliance on exemptions under MI 61-101, the anticipated use of proceeds and the approval of the TSX-V.

Forward-looking information is based on current expectations, estimates and projections that involve a number of risks, which could cause actual results to vary and in some instances, to differ materially from those anticipated by Horizon and described in the forward-looking information contained in this press release.

Although Horizon believes that the material factors, expectations and assumptions expressed in such forward-looking statements are reasonable based on information available to it on the date such statements were made, no assurances can be given as to future results, levels of activity and achievements and such statements are not guarantees of future performance.

SOURCE Horizon Petroleum Ltd.

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BMO Announces Cash Distributions for Certain BMO ETFs and ETF Series of BMO Mutual Funds for October 2026

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TORONTO, Oct. 22, 2026 /CNW/ — BMO Asset Management Inc., as manager of the BMO ETFs, and BMO Investments Inc., as manager of the BMO Mutual Funds, today announced the October 2026 cash distributions for unitholders of BMO ETFs and unitholders of exchange-traded series of units of the BMO Mutual Funds (collectively, the “ETF Series”)¹ that distribute monthly, as set out in the table below. Unitholders of record of the BMO ETFs and the ETF Series of the BMO Mutual Funds at the close of business on October 29, 2026, will receive cash distributions payable on November 3, 2026.

The ex-dividend date and record date for all BMO ETFs and ETF Series of BMO Mutual Funds is October 29, 2026.

Details of the per unit cash distribution amount are as follows:

Monthly Distributions

 FUND NAME

FUND TICKER

CASH DISTRIBUTION PER UNIT $

BMO AAA CLO ETF

ZAAA

0.124

BMO AAA CLO ETF (Hedged Units)

ZAAA.F

0.117

BMO AAA CLO ETF (USD Units)*

ZAAA.U

0.120

BMO Aggregate Bond Index ETF

ZAG

0.038

BMO All-Equity ETF (Target Cash Flow Units)

ZEQT.T

0.100

BMO Asset-Backed Securities ETF

ZABS

0.123

BMO Asset-Backed Securities ETF (Hedged Units)

ZABS.F

0.119

BMO Asset-Backed Securities ETF (USD Units)*

ZABS.U

0.119

BMO Balanced ETF (Target Cash Flow Units)

ZBAL.T

0.049

BMO BBB CLO ETF

ZBBZ

0.163

BMO BBB CLO ETF (Hedged Units)

ZBBZ.F

0.155

BMO BBB CLO ETF (USD Units)*

ZBBZ.U

0.158

BMO Canadian Core Plus US Balanced ETF

ZBCB

0.060

BMO Canadian Dividend ETF

ZDV

0.075

BMO Canadian High Dividend Covered Call ETF

ZWC

0.120

BMO Canadian High Dividend Covered Call ETF (Target Cash Flow Units)

ZWC.T

0.333

BMO Canadian MBS Index ETF

ZMBS

0.082

BMO Core Bond Fund (ETF Series)

ZCRB

0.044

BMO Covered Call Canadian Banks ETF

ZWB

0.170

BMO Covered Call Canadian Banks ETF (Target Cash Flow Units)

ZWB.T

0.488

BMO Covered Call Canadian Banks ETF (USD Units)*

ZWB.U

0.210

BMO Covered Call Dow Jones Industrial Average Hedged to CAD ETF

ZWA

0.150

BMO Covered Call Dow Jones Industrial Average Hedged to CAD ETF (Target Cash Flow Units)

ZWA.T

0.413

BMO Covered Call Energy ETF

ZWEN

0.220

BMO Covered Call Energy ETF (Target Cash Flow Units)

ZWEN.T

0.488

BMO Covered Call Health Care ETF

ZWHC

0.160

BMO Covered Call Health Care ETF (Target Cash Flow Units)

ZWHC.T

0.413

BMO Covered Call Spread Gold Bullion ETF

ZWGD

0.170

BMO Covered Call Spread Gold Bullion ETF (Target Cash Flow Units)

ZWGD.T

0.333

BMO Covered Call Technology ETF

ZWT

0.350

BMO Covered Call Technology ETF (Target Cash Flow Units)

ZWT.T

0.413

BMO Covered Call US Banks ETF

ZWK

0.160

BMO Covered Call US Banks ETF (Target Cash Flow Units)

ZWK.T

0.450

BMO Covered Call Utilities ETF

ZWU

0.070

BMO Covered Call Utilities ETF (Target Cash Flow Units)

ZWU.T

0.625

BMO Credit Stress Opportunities ETF

ZCDX

0.000

BMO Credit Stress Opportunities ETF (USD Units)*

ZCDX.U

0.000

BMO Discount Bond Index ETF

ZDB

0.022

BMO Emerging Markets Bond Hedged to CAD Index ETF

ZEF

0.045

BMO Emerging Markets Bond Fund (ETF Series)

ZEMB

0.053

BMO Equal Weight Banks Index ETF

ZEB

0.150

BMO Equal Weight REITs Index ETF

ZRE

0.090

BMO Equal Weight Utilities Index ETF

ZUT

0.071

BMO Europe High Dividend Covered Call ETF

ZWP

0.110

BMO Europe High Dividend Covered Call ETF (Target Cash Flow Units)

ZWP.T

0.333

BMO Europe High Dividend Covered Call Hedged to CAD ETF

ZWE

0.120

BMO Europe High Dividend Covered Call Hedged to CAD ETF (Target Cash Flow Units)

ZWE.T

0.333

BMO Floating Rate High Yield ETF

ZFH

0.062

BMO Global Dividend Opportunities Fund (Active ETF Series)

ZGDV

0.034

BMO Global Enhanced Income Fund (ETF Series)

ZWQT

0.085

BMO Global High Dividend Covered Call ETF

ZWG

0.190

BMO Global High Dividend Covered Call ETF (Target Cash Flow Units)

ZWG.T

0.333

BMO Global Infrastructure Fund (Active ETF Series)

ZGIF

0.050

BMO Global REIT Fund (Active ETF Series)

ZGRT

0.055

BMO Government Bond Index ETF

ZGB

0.111

BMO Growth ETF (Target Cash Flow Units)

ZGRO.T

0.058

BMO High Yield US Corporate Bond Hedged to CAD Index ETF

ZHY

0.060

BMO High Yield US Corporate Bond Index ETF

ZJK

0.103

BMO High Yield US Corporate Bond Index ETF (USD Units)*

ZJK.U

0.098

BMO International Dividend ETF

ZDI

0.085

BMO International Dividend Hedged to CAD ETF

ZDH

0.085

BMO Laddered Preferred Share Index ETF

ZPR

0.060

BMO Laddered Preferred Share Index ETF (USD Units)*

ZPR.U

0.096

BMO Long Corporate Bond Index ETF

ZLC

0.053

BMO Long Federal Bond Index ETF

ZFL

0.027

BMO Long Provincial Bond Index ETF

ZPL

0.034

BMO Mid Corporate Bond Index ETF

ZCM

0.055

BMO Mid Federal Bond Index ETF

ZFM

0.035

BMO Mid Provincial Bond Index ETF

ZMP

0.043

BMO Mid-Term US IG Corporate Bond Hedged to CAD Index ETF

ZMU

0.049

BMO Mid-Term US IG Corporate Bond Index ETF

ZIC

0.071

BMO Mid-Term US IG Corporate Bond Index ETF (USD Units)*

ZIC.U

0.052

BMO Money Market Fund (ETF Series)

ZMMK

0.100

BMO Monthly Income ETF

ZMI

0.049

BMO Monthly Income ETF (USD Units)*

ZMI.U

0.026

BMO MSCI Canada IMI High Dividend Yield Index ETF

ZDIV

0.108

BMO Premium Yield ETF

ZPAY

0.200

BMO Premium Yield ETF (Hedged Units)

ZPAY.F

0.175

BMO Premium Yield ETF (USD Units)*

ZPAY.U

0.180

BMO Real Return Bond Index ETF

ZRR

0.060

BMO Short Corporate Bond Index ETF

ZCS

0.047

BMO Short Federal Bond Index ETF

ZFS

0.028

BMO Short Provincial Bond Index ETF

ZPS

0.024

BMO Short-Term US IG Corporate Bond Hedged to CAD Index ETF

ZSU

0.050

BMO Strategic Autocallable Income US Large Cap ETF

ZACU

0.305

BMO Strategic Autocallable Income US Large Cap ETF (Hedged Units)

ZACU.F

0.305

BMO Strategic Autocallable Income US Large Cap ETF (USD Units)*

ZACU.U

0.305

BMO Ultra Short-Term Bond ETF

ZST

0.110

BMO Ultra Short-Term US Bond ETF (USD Units)*

ZUS.U

0.178

BMO US Aggregate Bond Index ETF

ZUAG

0.075

BMO US Aggregate Bond Index ETF (Hedged Units)

ZUAG.F

0.069

BMO US Aggregate Bond Index ETF (USD Units)*

ZUAG.U

0.072

BMO US Dividend ETF

ZDY

0.080

BMO US Dividend ETF (USD Units)*

ZDY.U

0.060

BMO US Dividend Growth ETF

ZBDU

0.070

BMO US Dividend Growth ETF (Hedged Units)

ZBDU.F

0.070

BMO US Dividend Hedged to CAD ETF

ZUD

0.055

BMO US High Dividend Covered Call ETF

ZWH

0.140

BMO US High Dividend Covered Call ETF (Target Cash Flow Units)

ZWH.T

0.413

BMO US High Dividend Covered Call ETF (USD Units)*

ZWH.U

0.140

BMO US High Dividend Covered Call Hedged to CAD ETF

ZWS

0.120

BMO US High Dividend Covered Call Hedged to CAD ETF (Target Cash Flow Units)

ZWS.T

0.413

BMO US Preferred Share Hedged to CAD Index ETF

ZHP

0.080

BMO US Preferred Share Index ETF

ZUP

0.096

BMO US Preferred Share Index ETF (USD Units)*

ZUP.U

0.090

BMO US Put Write ETF

ZPW

0.125

BMO US Put Write ETF (USD Units)*

ZPW.U

0.125

BMO US Put Write Hedged to CAD ETF

ZPH

0.120

BMO USD Cash Management ETF

ZUCM

0.108

BMO USD Cash Management ETF (USD Units)*

ZUCM.U

0.104

*Cash distribution per unit ($) amounts are USD for ZAAA.U, ZABS.U, ZBBZ.U, ZWB.U, ZCDX.U, ZJK.U, ZPR.U, ZIC.U, ZMI.U, ZPAY.U, ZACU.U, ZUS.U, ZUAG.U, ZDY.U, ZWH.U, ZUP.U, ZPW.U, ZUCM.U.

1 BMO ETFs are managed by BMO Asset Management Inc., an investment fund manager, a portfolio manager, and a separate legal entity from Bank of Montreal. ETF Series of the BMO Mutual Funds are managed by BMO Investments Inc., an investment fund manager and a separate legal entity from Bank of Montreal

Any statement that necessarily depends on future events may be a forward-looking statement. Forward-looking statements are not guarantees of performance. They involve risks, uncertainties and assumptions. Although such statements are based on assumptions that are believed to be reasonable, there can be no assurance that actual results will not differ materially from expectations. Investors are cautioned not to rely unduly on any forward-looking statements. In connection with any forward-looking statements, investors should carefully consider the areas of risk described in the most recent prospectus.

This communication is for information purposes. The information contained herein is not, and should not be construed as, investment, tax or legal advice to any party. Investments should be evaluated relative to the individual’s investment objectives and professional advice should be obtained with respect to any circumstance.

The BMO ETFs or securities referred to herein (ZDIV) are not sponsored, endorsed or promoted by MSCI Inc. (MSCI), and MSCI bears no liability with respect to any such BMO ETFs or securities or any index on which such BMO ETFs or securities are based. The prospectus of the BMO ETFs contains a more detailed description of the limited relationship MSCI has with BMO Asset Management Inc. and any related BMO ETFs.

The Dow Jones Industrial Index is a product of S&P Dow Jones Indices LLC or its affiliates (SPDJI), and has been licensed for use by BMO Asset Management Inc. S&P®, S&P 500®, US 500, The 500, iBoxx®, iTraxx® and CDX® are trademarks of S&P Global, Inc. or its affiliates (S&P) and Dow Jones® is a registered trademark of Dow Jones Trademark Holdings LLC (Dow Jones), and these trademarks have been licensed for use by SPDJI and sublicensed for certain purposes by BMO Asset Management Inc. The relevant BMO ETF (ZWA, ZWA.T) is not sponsored, endorsed, sold or promoted by SPDJI, Dow Jones, S&P, their respective affiliates, and none of such parties make any representation regarding the advisability of investing in such product(s), nor do they have any liability for any errors, omissions, or interruptions of the Index.

BLOOMBERG® and the Bloomberg Index are service marks of Bloomberg Finance L.P. and its affiliates, including Bloomberg Index Services Limited (BISL), the administrator of the index (collectively, Bloomberg) and have been licensed for use for certain purposes by BMO Asset Management Inc. Bloomberg is not affiliated with BMO Asset Management Inc., and Bloomberg does not approve, endorse, review, or recommend any BMO ETFs. Bloomberg does not guarantee the timeliness, accuracy or completeness of any data or information relating to the BMO ETFs.

BMO ETFs are not in any way sponsored, endorsed, sold or promoted by FTSE Global Debt Capital Markets Inc. (FGDCM), FTSE International Limited (FTSE), Frank Russell Company (Frank Russell), FTSE Fixed Income LLC (FTSE FI) or the London Stock Exchange Group companies (together with FGDCM, FTSE, Frank Russell and FTSE FI, the Licensor Parties). The Licensor Parties make no claim, prediction, warranty or representation whatsoever, expressly or impliedly, either as to (i) the results to be obtained from the use of the FTSE BMO ETF Indices, (ii) the figure at which any of the FTSE BMO ETF Indices stands at any particular time on any particular day or otherwise, or (iii) the suitability of an Underlying Index for the particular purpose to which it is being put in connection with the FTSE BMO ETFs. Each of the FTSE BMO ETF Indices is compiled and calculated by FGDCM of FTSE and all copyright in any of the FTSE BMO ETF Indices values and constituent lists vests in FGDCM or FTSE, respectively. The Licensor Parties shall not be liable (whether in negligence or otherwise) to any person for any error in any of the FTSE BMO ETF Indices and the Licensor Parties shall not be under any obligation to advise any person of any error therein. FTSE® is a trade mark of the London Stock Exchange Group companies and is used under licence.

Commissions, management fees and expenses all may be associated with investments in BMO ETFs and ETF Series units of the BMO Mutual Funds. Please read the ETF facts, fund facts or prospectus of the relevant BMO ETF or ETF Series of BMO Mutual Fund before investing. BMO ETFs and ETF Series units of the BMO Mutual Funds are not guaranteed, their values change frequently and past performance may not be repeated. BMO ETFs and ETF Series units may be bought and sold at market price on a stock exchange and brokerage commissions will reduce returns.

Distributions are not guaranteed and are subject to change and/or elimination depending on market conditions. The payment of distributions should not be confused with an investment fund’s performance, rate of return or yield. If distributions paid by an investment fund are greater than the performance of the fund, investors’ original investment will shrink. Distributions of net income and net taxable gains of a BMO ETF or an ETF Series will be included in the unitholder’s income for tax purposes in the year they are paid, whether or not such amounts are reinvested in additional units. A unitholder’s adjusted cost base (“ACB”) will be reduced by the amount of any return of capital (“ROC”). If a unitholder’s ACB goes below zero, such unitholder will have to pay capital gains tax on the amount below zero. Please refer to the summary of the principal income tax considerations set out in the prospectus for the relevant BMO ETF or ETF Series. Investors should also consult their own tax advisors about their individual circumstances.

The Target Cash Flow Units are subject to capital depletion risk. Target Cash Flow Units make monthly distributions of a fixed amount which may be comprised of, in whole or in part, a ROC. A ROC reduces the amount of an original investment and may result in the return to investors of the entire amount of an original investment.

The Target Cash Flow Units’ monthly distribution dollar amount is reset at the beginning of each calendar year. The dollar amount is a factor of the annualized distribution rate for the Target Cash Flow Units (which is the rate set out in the individual BMO ETF profiles in the applicable BMO ETF’s prospectus), the net asset value per unit of a series of a BMO ETF (NAVPS) as of the end of the previous calendar year, and the number of Target Cash Flow Units of the BMO ETF held at the time of the distribution. Although not expected, we may also adjust the monthly distribution during the year, if capital market conditions have significantly affected the ability of the BMO ETF to maintain the applicable distribution. If we make any such adjustment to the monthly distribution, we will issue a press release to communicate the change. The distribution rate applicable to the Target Cash Flow Units may be higher than the rate of return or the portfolio yield of the BMO ETF that offers such units. As a result, if you elect to receive some or all of the regular monthly distributions in cash, the value of your investment in the BMO ETF may decline over time.

For a summary of the risks of an investment in the BMO ETFs or ETF Series units of the BMO Mutual Funds, please see the specific risks set out in the relevant ETF facts, fund facts or prospectus. BMO ETFs and ETF Series units of the BMO Mutual Funds trade like stocks, fluctuate in market value and may trade at a discount to their net asset value, which may increase the risk of loss.

BMO ETFs are managed by BMO Asset Management Inc., an investment fund manager, a portfolio manager, and a separate legal entity from Bank of Montreal. BMO Mutual Funds are managed by BMO Investments Inc., an investment fund manager and a separate legal entity from Bank of Montreal.

BMO Global Asset Management is a brand name under which BMO Asset Management Inc. and BMO Investments Inc. operate.

“BMO (M-bar roundel symbol)” is a registered trademark of Bank of Montreal, used under licence.

Further information about BMO ETFs and ETF Series of the BMO Mutual Funds can be found at www.bmoetfs.com.

About BMO Financial Group 

BMO Financial Group is the eighth largest bank in North America by assets, with total assets of $1.5 trillion as of July 31, 2026. Serving clients for more than 200 years, BMO provides a broad range of personal and commercial banking, wealth management, global markets and investment banking products and services across Canada, the United States, and select markets globally. BMO is innovating for business value, by deploying and integrating human, digital and artificial intelligence to personalize client experiences, augment teams, and automate its business responsibly. Driven by its purpose, to Boldly Grow the Good in business and life, BMO is committed to driving positive change in the world, and making progress for a thriving economy, sustainable future, and stronger communities.

SOURCE BMO Financial Group

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ACL Digital Launches AgentixCare, a Human-in-the-Loop Agentic AI Platform for Healthcare Payers, Providers, and MedTech

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The AI-first platform applies agentic AI, generative AI, and predictive models across clinical care, revenue cycle management, and connected MedTech, with humans in control of every critical decision.

SAN JOSE, Calif., Oct. 22, 2026 /PRNewswire/ — ACL Digital, part of the ALTEN Group, today announced the launch of AgentixCare, a Human-in-the-Loop (HITL) Agentic AI platform for healthcare payers, providers, and MedTech organizations. A trusted AI-led Digital Enterprise & Systems Engineering Partner, ACL Digital drives innovation by designing and building intelligent systems across the full technology stack, from chip-to-cloud.

Traditional healthcare platforms record what happened but rarely act on it. Fragmented EHRs, manual prior authorizations, rising claim denials, and disconnected device data bury clinicians in documentation and leave revenue teams chasing paperwork. AgentixCare closes that gap, cutting costs by up to 30–50% while improving productivity, care quality, cash flow, and asset uptime, with HITL oversight at every decision point.

“Healthcare does not need another dashboard. It needs AI that does real clinical, financial, and operational work, safely. AgentixCare puts autonomous agents to work on the tasks that slow care down, from prior authorizations to denials to documentation, while keeping clinicians firmly in control. That is how our clients will move from AI pilots to measurable outcomes in weeks, not years,” said Ramandeep Singh, CEO of ACL Digital.

Unlike point solutions that bolt AI onto legacy workflows, the platform is built AI-first. Its agents assess data, gather clinical and policy evidence, assemble submissions, trace root causes, and recommend next-best actions.

End-to-End Coverage Across the Healthcare Value Chain

Clinical Care & Intelligence: EHR-ready AI notes, predictive early warnings, real-time clinical decision support (CDS), and formulary mapping.Agentic Revenue Cycle & Payer Operations: Electronic prior authorization and end-to-end claim and denial management, from scrubbing to recovery and reconciliation.Intelligent Connected MedTech: Predictive maintenance, performance analytics, a GenAI copilot for surgical robotics fleets, and infusion pump monitoring.AI-Governed Trust, Risk & Compliance: A compliance copilot for HIPAA and HITECH readiness.Future-Ready Interoperability: HL7 v2, FHIR R4, and SMART on FHIR connectors for leading enterprise and open-source EMRs.

The platform is designed to significantly reduce manual prior authorization work and administrative costs, speed up routine authorization decisions, cut claim denials and unplanned device downtime, catch more patient anomalies, and deliver faster answers through AI copilots and natural language processing.

“We engineered AgentixCare the way we build medical-grade systems: interoperable from day one, secure by design, and governed end to end. Every agent works on FHIR and HL7 data, every recommendation shows its evidence, and every action is approved and recorded. That combination of agentic AI and Human-in-the-Loop governance is what makes enterprise adoption fast and safe,” said Suresh Venkateswaran, Head – Digital Product Engineering Services at ACL Digital.

AgentixCare draws on ACL Digital’s decades of domain and product engineering experience with healthcare, life sciences, and medical device companies. Developed by the company’s Healthcare Center of Excellence, it combines first-hand knowledge of Clinical, Payer, and MedTech workflows with interoperability standards and responsible AI practices.

AgentixCare is available now for pilot programs. To request a demonstration, visit AgentixCare programs.

About ACL Digital

ACL Digital, part of the ALTEN Group, is a trusted AI-led Digital Enterprise & Systems Engineering Partner driving innovation by designing and building intelligent systems across the full technology stack from chip to cloud. By integrating AI and data-powered solutions, we help enterprises accelerate digital transformation, optimize operations, and achieve scalable business outcomes. Partner with us to turn complexity into clarity and shape the future of your organization. Learn more at www.acldigital.com.

 

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SOURCE ACL Digital

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