The incident categorization artificial intelligence (AI) market size is expected to see exponential growth in the next few years. It will grow to $7.68 billion in 2030 at a compound annual growth rate (CAGR) of 29.3%. The growth in the forecast period can be attributed to genAI-powered incident summarization, auto-routing with context enrichment, integration across itSM and siem, continuous learning classification models, self-healing operations enablement. Major trends in the forecast period include nlp-based ticket classification, auto-priority and routing automation, context-enriched incident summarization, continuous learning from resolutions, integration with itsm and siem workflows.
The surge in cyber threats is expected to drive the growth of the incident categorization artificial intelligence (AI) market going forward. Cyber threats refer to malicious activities intended to disrupt, damage, or gain unauthorized access to digital systems, networks, and data. The rise in these threats is primarily fueled by increasing digitalization and cloud adoption, which expand the attack surface and create more entry points for cybercriminals to exploit vulnerabilities in interconnected systems. Incident categorization artificial intelligence assists organizations in managing such threats by automatically identifying, classifying, and prioritizing security incidents, enabling faster and more accurate detection and response. For instance, in 2023, according to the Australian Signals Directorate, the number of cybercrime reports in Australia increased to over 94,000, up from over 76,000 in 2022. Therefore, as cyber threats continue to escalate and digital attack surfaces broaden, the demand for incident categorization artificial intelligence solutions is expected to grow, fueling market expansion.
Major companies operating in the incident categorization artificial intelligence (AI) market are emphasizing advancements in AI technologies to strengthen operational resilience, improve system reliability, reduce downtime, and ensure continuous service delivery. Operational resilience refers to an organization’s ability to anticipate, withstand, and recover from disruptions while maintaining critical business operations. For instance, in October 2024, PagerDuty, a US-based digital operations management company, introduced new AI-powered capabilities to help organizations minimize the effects of unplanned outages and enhance operational resilience. The platform features a unified chat experience and upgrades to the Operations Console, improving coordination, reducing context switching, and accelerating incident response. These enhancements enable teams to predict, resolve, and prevent incidents more efficiently, reducing downtime costs and strengthening customer confidence.
In September 2023, Cisco Systems, Inc., a US-based digital communications technology company, acquired Splunk Inc. for approximately $28 billion. Through this acquisition, Cisco aims to integrate Splunk’s security and observability platform to enhance its cybersecurity and data analytics capabilities. Splunk Inc. is a US-based company that develops software for searching, monitoring, and analyzing machine-generated data.
Major companies operating in the incident categorization artificial intelligence (AI) market are IBM Corporation, HCL Technologies Limited, ServiceNow Inc., Palo Alto Networks Inc., Fortinet Inc., Splunk Inc., Atlassian Corporation Plc, CrowdStrike Holdings Inc., Check Point Software Technologies Ltd., Datadog Inc., Elastic NV, Rapid7 Inc., Ivanti Inc., Freshworks Inc., Qualys Inc., PagerDuty Inc., Sumo Logic Inc., LogicMonitor Inc., SolarWinds Worldwide LLC, Moogsoft Inc., BMC Software Inc., Resolve Systems LLC, BigPanda Inc.
North America was the largest region in the incident categorization artificial intelligence market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the incident categorization artificial intelligence (AI) market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the incident categorization artificial intelligence (AI) market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.
Tariffs have created both challenges and opportunities for the incident categorization artificial intelligence (AI) market by increasing the cost of importing compute hardware, networking equipment, and security components used across on-premises and cloud-connected deployments. These cost increases can slow upgrade cycles for enterprises in North America and Europe that depend on Asia-Pacific supply chains, especially for hardware-heavy segments such as accelerators, edge devices, and monitoring appliances. However, tariffs are also encouraging regional sourcing, greater use of software-based optimization, and stronger vendor partnerships to reduce total cost of ownership. Providers are improving automation, enhancing managed services, and optimizing architectures to maintain performance and reliability while controlling costs.
The incident categorization artificial intelligence (AI) market research report is one of a series of new reports that provides incident categorization artificial intelligence (AI) market statistics, including incident categorization artificial intelligence (AI) industry global market size, regional shares, competitors with a incident categorization artificial intelligence (AI) market share, detailed incident categorization artificial intelligence (AI) market segments, market trends and opportunities, and any further data you may need to thrive in the incident categorization artificial intelligence (AI) industry. This incident categorization artificial intelligence (AI) market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.
Incident categorization artificial intelligence (AI) refers to the application of artificial intelligence to automatically analyze and classify IT support tickets or security alerts. It evaluates the text and context of incoming incidents to determine the type of issue, its priority level, and the appropriate support team for resolution. This technology continuously learns from historical data to enhance its accuracy and efficiency over time.
The primary components of incident categorization artificial intelligence (AI) include software and services. The software utilizes AI to automatically categorize and prioritize incidents across various organizational workflows. The market is segmented by organization size into small and medium enterprises and large enterprises. Deployment modes include on premises and cloud solutions. Key applications encompass IT operations, security operations, customer support, and risk management. The major end users are banking, financial services, and insurance (BFSI), healthcare, IT and telecom, government, retail, manufacturing, and other sectors.
The incident categorization artificial intelligence (AI) market consists of revenues earned by entities by providing services such as mobile/web apps, root cause analysis AI, predictive threat detection, and hybrid AI deployment. The market value includes the value of related goods sold by the service provider or contained within the service offering. The incident categorization artificial intelligence (AI) market also includes sales of real-time alerts and collaboration, automated reporting and analytics, user training & support, and consulting for workflow automation. Values in this market are ‘factory gate’ values; that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods. The incident categorization AI market is segmented by component, deployment mode, organization size, application, and end-user.
The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).
The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.
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Table of Contents
Executive Summary
Incident Categorization Artificial Intelligence (AI) Market Global Report 2026 provides strategists, marketers and senior management with the critical information they need to assess the market.This report focuses incident categorization artificial intelligence (AI) market which is experiencing strong growth. The report gives a guide to the trends which will be shaping the market over the next ten years and beyond.
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Description
Where is the largest and fastest growing market for incident categorization artificial intelligence (AI)? How does the market relate to the overall economy, demography and other similar markets? What forces will shape the market going forward, including technological disruption, regulatory shifts, and changing consumer preferences? The incident categorization artificial intelligence (AI) market global report answers all these questions and many more.The report covers market characteristics, size and growth, segmentation, regional and country breakdowns, total addressable market (TAM), market attractiveness score (MAS), competitive landscape, market shares, company scoring matrix, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.
- The market characteristics section of the report defines and explains the market. This section also examines key products and services offered in the market, evaluates brand-level differentiation, compares product features, and highlights major innovation and product development trends.
- The supply chain analysis section provides an overview of the entire value chain, including key raw materials, resources, and supplier analysis. It also provides a list competitor at each level of the supply chain.
- The updated trends and strategies section analyses the shape of the market as it evolves and highlights emerging technology trends such as digital transformation, automation, sustainability initiatives, and AI-driven innovation. It suggests how companies can leverage these advancements to strengthen their market position and achieve competitive differentiation.
- The regulatory and investment landscape section provides an overview of the key regulatory frameworks, regularity bodies, associations, and government policies influencing the market. It also examines major investment flows, incentives, and funding trends shaping industry growth and innovation.
- The market size section gives the market size ($b) covering both the historic growth of the market, and forecasting its development.
- The forecasts are made after considering the major factors currently impacting the market. These include the technological advancements such as AI and automation, Russia-Ukraine war, trade tariffs (government-imposed import/export duties), elevated inflation and interest rates.
- The total addressable market (TAM) analysis section defines and estimates the market potential compares it with the current market size, and provides strategic insights and growth opportunities based on this evaluation.
- The market attractiveness scoring section evaluates the market based on a quantitative scoring framework that considers growth potential, competitive dynamics, strategic fit, and risk profile. It also provides interpretive insights and strategic implications for decision-makers.
- Market segmentations break down the market into sub markets.
- The regional and country breakdowns section gives an analysis of the market in each geography and the size of the market by geography and compares their historic and forecast growth.
- Expanded geographical coverage includes Taiwan and Southeast Asia, reflecting recent supply chain realignments and manufacturing shifts in the region. This section analyzes how these markets are becoming increasingly important hubs in the global value chain.
- The competitive landscape chapter gives a description of the competitive nature of the market, market shares, and a description of the leading companies. Key financial deals which have shaped the market in recent years are identified.
- The company scoring matrix section evaluates and ranks leading companies based on a multi-parameter framework that includes market share or revenues, product innovation, and brand recognition.
Report Scope
Markets Covered:
1) By Component: Software; Services2) By Organization Size: Small And Medium Enterprises; Large Enterprises
3) By Deployment Mode: On-Premises; Cloud
4) By Application: Information Technology Operations; Security Operations; Customer Support; Risk Management; Other Applications
5) By End-User: Banking, Financial Services, And Insurance; Healthcare; Information Technology And Telecom; Government; Retail; Manufacturing; Other End-Users
Subsegments:
1) By Software: Machine Learning Algorithms; Natural Language Processing Models; Predictive Analytics Tools; Workflow Automation Platforms; Data Integration Solutions; Incident Detection Systems; Cloud-Based Categorization Software2) By Services: Implementation Services; Consulting Services; Training And Support Services; Managed Services; System Integration Services; Maintenance And Upgradation Services; Data Analysis And Reporting Services
Companies Mentioned: IBM Corporation; HCL Technologies Limited; ServiceNow Inc.; Palo Alto Networks Inc.; Fortinet Inc.; Splunk Inc.; Atlassian Corporation Plc; CrowdStrike Holdings Inc.; Check Point Software Technologies Ltd.; Datadog Inc.; Elastic NV; Rapid7 Inc.; Ivanti Inc.; Freshworks Inc.; Qualys Inc.; PagerDuty Inc.; Sumo Logic Inc.; LogicMonitor Inc.; SolarWinds Worldwide LLC; Moogsoft Inc.; BMC Software Inc.; Resolve Systems LLC; BigPanda Inc.
Countries: Australia; Brazil; China; France; Germany; India; Indonesia; Japan; Taiwan; Russia; South Korea; UK; USA; Canada; Italy; Spain.
Regions: Asia-Pacific; South East Asia; Western Europe; Eastern Europe; North America; South America; Middle East; Africa
Time Series: Five years historic and ten years forecast.
Data: Ratios of market size and growth to related markets, GDP proportions, expenditure per capita.
Data Segmentation: Country and regional historic and forecast data, market share of competitors, market segments.
Sourcing and Referencing: Data and analysis throughout the report is sourced using end notes.
Delivery Format: Word, PDF or Interactive Report + Excel Dashboard
Added Benefits:
- Bi-Annual Data Update
- Customisation
- Expert Consultant Support
Companies Mentioned
The companies featured in this Incident Categorization AI market report include:- IBM Corporation
- HCL Technologies Limited
- ServiceNow Inc.
- Palo Alto Networks Inc.
- Fortinet Inc.
- Splunk Inc.
- Atlassian Corporation Plc
- CrowdStrike Holdings Inc.
- Check Point Software Technologies Ltd.
- Datadog Inc.
- Elastic NV
- Rapid7 Inc.
- Ivanti Inc.
- Freshworks Inc.
- Qualys Inc.
- PagerDuty Inc.
- Sumo Logic Inc.
- LogicMonitor Inc.
- SolarWinds Worldwide LLC
- Moogsoft Inc.
- BMC Software Inc.
- Resolve Systems LLC
- BigPanda Inc.
Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 250 |
| Published | February 2026 |
| Forecast Period | 2026 - 2030 |
| Estimated Market Value ( USD | $ 2.75 Billion |
| Forecasted Market Value ( USD | $ 7.68 Billion |
| Compound Annual Growth Rate | 29.3% |
| Regions Covered | Global |
| No. of Companies Mentioned | 24 |


