Intelligent Apps Market By Share, Size and Forecast 2028

Summary

Report Description

Forecast Period	2024-2028
Market Size (2022)	USD 28.16 Billion
CAGR (2023-2028)	30.76%
Fastest Growing Segment	Cloud
Largest Market	North America

Market Overview

The projected market size for the global intelligent apps market is expected to reach USD 28.16 billion by the end of 2022, with a compound annual growth rate (CAGR) of 30.76% during the forecast period. The global intelligent apps market is experiencing remarkable expansion driven by the integration of artificial intelligence, machine learning, and data analytics into applications. These intelligent apps, also known as smart apps, offer personalized, context-aware, and proactive user experiences by utilizing insights derived from user interactions and data. They find application in various sectors such as healthcare, finance, retail, and entertainment, enhancing decision-making and productivity. The proliferation of IoT devices and data generation further fuels their growth, enabling real-time data processing and insights. However, challenges such as privacy concerns and integration complexities exist. Despite this, organizations are investing in the development of intelligent apps to gain a competitive edge, fostering innovation and competition in the market.

Key Market Drivers

Advancements in Artificial Intelligence (AI) and Machine Learning (ML)

Advancements in Artificial Intelligence (AI) and Machine Learning (ML) are serving as the driving force behind the rapid expansion of the global intelligent apps market. AI and ML technologies have reached new levels of sophistication, enabling intelligent apps to process, analyze, and interpret vast amounts of data with unprecedented accuracy. These technologies empower intelligent apps to learn from user interactions, predict user preferences, and make real-time decisions, culminating in highly personalized and contextually relevant experiences. AI-powered algorithms can identify patterns, trends, and anomalies within data, allowing intelligent apps to offer predictive insights and actionable recommendations to users. As AI and ML continue to evolve, intelligent apps are becoming more adept at understanding natural language, interpreting images, and even making informed decisions autonomously. Businesses across various industries are harnessing these capabilities to enhance customer engagement, streamline operations, and drive innovation. The integration of AI and ML into intelligent apps is not only reshaping user experiences but also revolutionizing how organizations leverage data to make informed decisions, amplifying the global adoption and growth of these transformative applications.

The Proliferation of Data Generated by IoT Devices, social media, and Other Sources Provides

The proliferation of data generated by IoT devices, social media platforms, and various other sources is serving as a significant driving force behind the global intelligent apps market. With the exponential growth of connected devices in the Internet of Things (IoT) ecosystem, an immense volume of data is being generated in real time. Additionally, social media platforms generate massive amounts of user-generated content, interactions, and behaviors. These data sources provide a rich reservoir of information that intelligent apps can tap into, enabling them to gain deeper insights into user preferences, behaviors, and patterns. By harnessing this diverse and abundant data, intelligent apps can offer personalized experiences, predictive recommendations, and data-driven insights that cater to individual users' needs. The ability to process and analyze this vast and complex data landscape is reshaping the capabilities of intelligent apps, allowing them to understand context, anticipate user intent, and deliver valuable solutions across industries. As the generation of data continues to accelerate, the global intelligent apps market is poised to thrive, capitalizing on the data-driven era to provide enhanced user experiences and data-driven decision-making.

The growing Demand for Data-Driven Insights

The growing demand for data-driven insights is a pivotal driver propelling the global intelligent apps market forward. In today's information-rich landscape, businesses and individuals alike are increasingly seeking actionable insights derived from data to guide their decisions. Intelligent apps leverage advanced technologies like artificial intelligence and machine learning to analyze vast datasets and extract meaningful patterns and trends. By providing users with real-time, data-driven insights, these apps enable informed decision-making, whether in business strategies, consumer choices, or operational optimizations. The ability of intelligent apps to transform raw data into actionable insights not only enhances user experiences but also empowers organizations to gain a competitive edge, streamline processes, and respond swiftly to changing market dynamics. As the demand for real-time insights continues to rise, the global intelligent apps market remains positioned to address this need and shape the digital landscape across various sectors.

The evolving Consumer Expectations

Evolving consumer expectations are playing a pivotal role in driving the growth of the global intelligent apps market. As consumers become increasingly accustomed to personalized and seamless experiences in their interactions with technology, their expectations have shifted towards applications that understand their preferences, anticipate their needs, and deliver tailored solutions. Intelligent apps, powered by AI and machine learning, are uniquely positioned to meet these evolving demands by offering hyper-personalized content, predictive recommendations, and context-aware interactions. The ability of intelligent apps to adapt and learn from user behaviors aligns with the desire for effortless and intuitive interactions. Businesses across industries are recognizing the significance of catering to these changing consumer expectations, leading to a surge in the development and adoption of intelligent apps that prioritize user-centric experiences. In this dynamic landscape, intelligent apps are reshaping how individuals engage with technology, fostering loyalty, engagement, and satisfaction, and thus driving the expansion of the global intelligent apps market.

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Key Market Challenges

Concern Related to Data Security and Privacy

A significant concern related to data security and privacy is hampering the growth of the global intelligent apps market. As intelligent apps rely heavily on collecting, analyzing, and utilizing user data to provide personalized experiences, the potential for data breaches, unauthorized access, and misuse of sensitive information raises apprehensions among both users and organizations. The increasingly stringent data protection regulations, such as GDPR and CCPA, impose strict compliance requirements on how user data is collected, stored, and processed. Addressing these concerns necessitates robust security measures, transparent data usage policies, and proactive steps to safeguard user information. Building trust through responsible data handling practices is essential for encouraging user adoption and maintaining credibility in an era where data breaches can have severe consequences. Resolving these data security and privacy concerns is crucial to unlocking the full potential of intelligent apps and ensuring their continued growth in a way that respects user rights and meets regulatory expectations.

Lack of Clear Return on Investment (ROI)

The lack of a clear return on investment (ROI) is posing a challenge to the growth of the global intelligent apps market. While the potential benefits of intelligent apps, such as enhanced user experiences and data-driven insights, are well understood, quantifying their concrete financial impact can be challenging for businesses. Demonstrating the measurable ROI of implementing intelligent apps requires thorough analysis of factors such as increased revenue, cost savings, improved operational efficiency, and customer retention. Additionally, the time required for the benefits to materialize and the complexities of attributing outcomes solely to intelligent apps can make ROI assessment intricate. Overcoming this challenge necessitates comprehensive tracking of key performance indicators and a diligent approach to measuring the tangible impact of intelligent apps. Clear and compelling ROI calculations are crucial for organizations to confidently invest in and prioritize the integration of intelligent apps into their operations, thereby fostering their wider adoption and continued success in the global market.

Key Market Trends

The trend towards Hyper-Personalization

The trend towards hyper-personalization is a significant driver propelling the global intelligent apps market. With the increasing reliance on technology and digital interactions, consumers now expect applications that go beyond generic experiences and offer tailored solutions aligned with their individual preferences and behaviors. Intelligent apps leverage advanced AI algorithms to analyze vast datasets, enabling them to understand user context and preferences, anticipate needs, and deliver content, services, and recommendations that are highly relevant to everyone. This hyper-personalized approach enhances user engagement, satisfaction, and loyalty by creating seamless and intuitive interactions that cater to unique requirements. Businesses recognize the value of meeting these expectations, resulting in a surge of interest in developing and deploying intelligent apps that can deliver hyper-personalized experiences across industries. As the demand for individualized interactions continues to rise, the global intelligent apps market remains poised to thrive, reshaping user experiences and elevating the standard of digital engagement.

The Rise of No-Code/Low-Code Platforms

The rise of No-Code/Low-Code platforms is exerting a significant influence on the global intelligent apps market. These platforms empower individuals with varying levels of technical expertise to create and deploy intelligent apps without the need for extensive coding skills. By providing intuitive visual interfaces and pre-built components, No-Code/Low-Code platforms democratize the app development process, enabling a wider range of professionals to participate in creating innovative solutions. This trend is accelerating the pace of app development, reducing time-to-market, and fostering a culture of innovation within organizations. With these platforms, businesses can swiftly respond to changing market demands, experiment with new ideas, and iterate on intelligent app concepts. Moreover, the accessibility of No-Code/Low-Code solutions fuels the expansion of the intelligent apps market by enabling a broader pool of developers and users to contribute to its growth, thereby contributing to the overall momentum of innovation and adoption in the digital landscape.

Segmental Insights

Store Type Insights

Based on store type, the google play segment emerges as the predominant segment, exhibiting unwavering dominance projected throughout the forecast period. With its widespread reach and accessibility across diverse Android devices, Google Play has established a significant foothold in the distribution of intelligent apps. The sheer volume of Android users contributes to its prominent position, making it a favored platform for developers to showcase and deliver their innovative applications. As the Android ecosystem continues to expand and evolve, the Google Play segment is anticipated to sustain its commanding influence, facilitating the dissemination of intelligent apps to a vast and diverse user base, thereby shaping the market's trajectory in the foreseeable future.

End User Insights

Based on end user, the retail segment emerges as a formidable frontrunner, exerting its dominance and shaping the market's trajectory throughout the forecast period. The retail industry's adoption of intelligent apps, enriched by AI and data analytics, is transforming customer engagement, inventory management, and personalized shopping experiences. Retailers leverage these apps to decipher consumer preferences, offer targeted recommendations, optimize supply chains, and enhance overall operational efficiency. The competitive retail landscape compels businesses to harness the power of intelligent apps to stay relevant, cater to evolving consumer demands, and drive growth. As technology continues to shape consumer behavior, the retail segment's ascendancy in embracing intelligent apps is expected to persist, solidifying its position as a driving force that steers the market's direction and catalyzes innovation across the retail domain.

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Regional Insights

North America stands poised to uphold its dominant stance in the global work order management market, underscoring its pivotal role in molding the industry's landscape. With a robust technological infrastructure, strong digital adoption, and a mature industrial sector, North America has been at the forefront of embracing work order management systems. The region's businesses and enterprises recognize the imperative of efficient workflow management and resource allocation, driving the demand for sophisticated solutions. As industries across North America continue to prioritize operational optimization and seamless task management, the region's established presence in the work order management arena is anticipated to persist. Its sustained dominance underscores North America's proactive approach to technological advancements and positions it as a major influencer shaping the trajectory of the global work order management market.

Recent Developments

In June 2023, Finsemble and Glue42, two leading companies specializing in financial technology solutions, announced their merger to form a new entity named interop.io. This strategic merger aimed to create a powerful force in the realm of interoperability within capital markets and beyond. Both Finsemble and Glue42 were known for their expertise in providing solutions that facilitate seamless integration and communication between different applications and systems in the financial sector. The merger into interop.io signaled a commitment to addressing the growing need for efficient data and workflow interoperability within the complex landscape of capital markets.
In June 2023, Databricks, a prominent data and AI platform, announced its acquisition of MosaicML for a reported $1.3 billion. This strategic move was aimed at bolstering Databricks' generative artificial intelligence (AI) capabilities. MosaicML, known for its expertise in generative AI technology, had developed solutions that focus on using AI to generate novel content, designs, and insights. By acquiring MosaicML, Databricks sought to enhance its AI offerings, particularly in the domain of generative models. Generative AI involves creating AI models that can generate new and original data based on patterns learned from existing data.
In April 2023, Alphabet, Google's parent company, announced its decision to merge two of its prominent artificial intelligence (AI) research groups, DeepMind, and Google Brain. This strategic move aimed to consolidate and synergize the expertise and research efforts of both groups under a unified AI research division. DeepMind, known for its breakthroughs in machine learning and AI algorithms, was acquired by Alphabet in 2014. By merging these two influential AI-focused groups, Alphabet aimed to pool their talents, resources, and research initiatives to accelerate AI innovation and tackle more complex challenges collaboratively.

Key Market Players

Google LLC
Microsoft Corporation
IBM Corporation
SAP SE
Amazon Web Services
Oracle Corporation
Apple Inc.
Intel Corporation
Baidu Inc.
Salesforce.com

By Type	By Deployment Mode	By Providers	By Services	By Store Type	By End User	By Region
Consumer Apps Enterprise Apps	On-premises Cloud	Infrastructure Data Collection & Preparation Machine Intelligence	Professional Services Managed Services	Google Play Apple App Store Others	BFSI Telecommunication Retail Healthcare Education Others	North America Europe South America Middle East & Africa Asia Pacific

Report Scope:

In this report, the global intelligent apps market has been segmented into the following categories, in addition to the industry trends which have also been detailed below:

Global Intelligent Apps Market, By Type:

o Consumer Apps

o Enterprise Apps

Global Intelligent Apps Market, By Deployment Mode:

o On-premises

o Cloud

Global Intelligent Apps Market, By Providers:

o Infrastructure

o Data Collection & Preparation

o Machine Intelligence

Global Intelligent Apps Market, By Services:

o Professional Services

o Managed Services

Global Intelligent Apps Market, By Store Type:

o Google Play

o Apple App Store

o Others

Global Intelligent Apps Market, By End User:

o BFSI

o Telecommunication

o Retail

o Healthcare

o Education

o Others

Global Intelligent Apps Market, By Region:

o North America

o Europe

o South America

o Middle East & Africa

o Asia Pacific

Competitive Landscape

Company Profiles: Detailed analysis of the major companies present in the Global Intelligent Apps Market.

Available Customizations:

Global Intelligent Apps market report with the given market data, Tech Sci Research offers customizations according to a company's specific needs. The following customization options are available for the report:

Company Information

Detailed analysis and profiling of additional market players (up to five).

Global Intelligent Apps Market is an upcoming report to be released soon. If you wish an early delivery of this report or want to confirm the date of release, please contact us at [email protected]

Table of content

1. Service Overview

1.1. Market Definition

1.2. Scope of the Market

1.2.1. Markets Covered

1.2.2. Years Considered for Study

1.2.3. Key Market Segmentations

2. Research Methodology

2.1. Objective of the Study

2.2. Baseline Methodology

2.3. Key Industry Partners

2.4. Major Association and Secondary Sources

2.5. Forecasting Methodology

2.6. Data Triangulation & Validation

2.7. Assumptions and Limitations

3. Executive Summary

4. Impact of COVID-19 on Global Intelligent Apps Market

5. Voice of Customer

6. Global Intelligent Apps Market Overview

7. Global Intelligent Apps Market Outlook

7.1. Market Size & Forecast

7.1.1. By Value

7.2. Market Share & Forecast

7.2.1. By Type (Consumer Apps, Enterprise Apps)

7.2.2. By Deployment Mode (Cloud, On-Premises)

7.2.3. By Providers (Infrastructure, Data Collection & Preparation, Machine Intelligence)

7.2.4. By Services (Professional Services, Managed Services)

7.2.5. By Store Type (Google Play, Apple App Store, Others)

7.2.6. By End User (BFSI, Telecommunication, Retail, Healthcare, Education, Others)

7.2.7. By Region (North America, Europe, South America, Middle East & Africa, Asia Pacific)

7.2.8. By Region

7.3. By Company (2022)

7.4. Market Map

8. North America Intelligent Apps Market Outlook

8.1. Market Size & Forecast

8.1.1. By Value

8.2. Market Share & Forecast

8.2.1. By Type

8.2.2. By Deployment Mode

8.2.3. By Providers

8.2.4. By Services

8.2.5. By Store Type

8.2.6. By End User

8.2.7. By Country

8.3. North America: Country Analysis

8.3.1. United States Intelligent Apps Market Outlook

8.3.1.1. Market Size & Forecast

8.3.1.1.1. By Value

8.3.1.2. Market Share & Forecast

8.3.1.2.1. By Type

8.3.1.2.2. By Deployment Mode

8.3.1.2.3. By Providers

8.3.1.2.4. By Services

8.3.1.2.5. By Store Type

8.3.1.2.6. By End User

8.3.2. Canada Intelligent Apps Market Outlook

8.3.2.1. Market Size & Forecast

8.3.2.1.1. By Value

8.3.2.2. Market Share & Forecast

8.3.2.2.1. By Type

8.3.2.2.2. By Deployment Mode

8.3.2.2.3. By Providers

8.3.2.2.4. By Services

8.3.2.2.5. By Store Type

8.3.2.2.6. By End User

8.3.3. Mexico Intelligent Apps Market Outlook

8.3.3.1. Market Size & Forecast

8.3.3.1.1. By Value

8.3.3.2. Market Share & Forecast

8.3.3.2.1. By Type

8.3.3.2.2. By Deployment Mode

8.3.3.2.3. By Providers

8.3.3.2.4. By Services

8.3.3.2.5. By Store Type

8.3.3.2.6. By End User

9. Europe Intelligent Apps Market Outlook

9.1. Market Size & Forecast

9.1.1. By Value

9.2. Market Share & Forecast

9.2.1. By Type

9.2.2. By Deployment Mode

9.2.3. By Providers

9.2.4. By Services

9.2.5. By Store Type

9.2.6. By End User

9.2.7. By Country

9.3. Europe: Country Analysis

9.3.1. Germany Intelligent Apps Market Outlook

9.3.1.1. Market Size & Forecast

9.3.1.1.1. By Value

9.3.1.2. Market Share & Forecast

9.3.1.2.1. By Type

9.3.1.2.2. By Deployment Mode

9.3.1.2.3. By Providers

9.3.1.2.4. By Services

9.3.1.2.5. By Store Type

9.3.1.2.6. By End User

9.3.2. United Kingdom Intelligent Apps Market Outlook

9.3.2.1. Market Size & Forecast

9.3.2.1.1. By Value

9.3.2.2. Market Share & Forecast

9.3.2.2.1. By Type

9.3.2.2.2. By Deployment Mode

9.3.2.2.3. By Providers

9.3.2.2.4. By Services

9.3.2.2.5. By Store Type

9.3.2.2.6. By End User

9.3.3. France Intelligent Apps Market Outlook

9.3.3.1. Market Size & Forecast

9.3.3.1.1. By Value

9.3.3.2. Market Share & Forecast

9.3.3.2.1. By Type

9.3.3.2.2. By Deployment Mode

9.3.3.2.3. By Providers

9.3.3.2.4. By Services

9.3.3.2.5. By Store Type

9.3.3.2.6. By End User

9.3.4. Spain Intelligent Apps Market Outlook

9.3.4.1. Market Size & Forecast

9.3.4.1.1. By Value

9.3.4.2. Market Share & Forecast

9.3.4.2.1. By Type

9.3.4.2.2. By Deployment Mode

9.3.4.2.3. By Providers

9.3.4.2.4. By Services

9.3.4.2.5. By Store Type

9.3.4.2.6. By End User

9.3.5. Italy Intelligent Apps Market Outlook

9.3.5.1. Market Size & Forecast

9.3.5.1.1. By Value

9.3.5.2. Market Share & Forecast

9.3.5.2.1. By Type

9.3.5.2.2. By Deployment Mode

9.3.5.2.3. By Providers

9.3.5.2.4. By Services

9.3.5.2.5. By Store Type

9.3.5.2.6. By End User

10. South America Intelligent Apps Market Outlook

10.1. Market Size & Forecast

10.1.1. By Value

10.2. Market Share & Forecast

10.2.1. By Type

10.2.2. By Deployment Mode

10.2.3. By Providers

10.2.4. By Services

10.2.5. By Store Type

10.2.6. By End User

10.2.7. By Country

10.3. South America: Country Analysis

10.3.1. Brazil Intelligent Apps Market Outlook

10.3.1.1. Market Size & Forecast

10.3.1.1.1. By Value

10.3.1.2. Market Share & Forecast

10.3.1.2.1. By Type

10.3.1.2.2. By Deployment Mode

10.3.1.2.3. By Providers

10.3.1.2.4. By Services

10.3.1.2.5. By Store Type

10.3.1.2.6. By End User

10.3.2. Argentina Intelligent Apps Market Outlook

10.3.2.1. Market Size & Forecast

10.3.2.1.1. By Value

10.3.2.2. Market Share & Forecast

10.3.2.2.1. By Type

10.3.2.2.2. By Deployment Mode

10.3.2.2.3. By Providers

10.3.2.2.4. By Services

10.3.2.2.5. By Store Type

10.3.2.2.6. By End User

10.3.3. Colombia Intelligent Apps Market Outlook

10.3.3.1. Market Size & Forecast

10.3.3.1.1. By Value

10.3.3.2. Market Share & Forecast

10.3.3.2.1. By Type

10.3.3.2.2. By Deployment Mode

10.3.3.2.3. By Providers

10.3.3.2.4. By Services

10.3.3.2.5. By Store Type

10.3.3.2.6. By End User

11. Middle East & Africa Intelligent Apps Market Outlook

11.1. Market Size & Forecast

11.1.1. By Value

11.2. Market Share & Forecast

11.2.1. By Type

11.2.2. By Deployment Mode

11.2.3. By Providers

11.2.4. By Services

11.2.5. By Store Type

11.2.6. By End User

11.2.7. By Country

11.3. Middle East & America: Country Analysis

11.3.1. Israel Intelligent Apps Market Outlook

11.3.1.1. Market Size & Forecast

11.3.1.1.1. By Value

11.3.1.2. Market Share & Forecast

11.3.1.2.1. By Type

11.3.1.2.2. By Deployment Mode

11.3.1.2.3. By Providers

11.3.1.2.4. By Services

11.3.1.2.5. By Store Type

11.3.1.2.6. By End User

11.3.2. Qatar Intelligent Apps Market Outlook

11.3.2.1. Market Size & Forecast

11.3.2.1.1. By Value

11.3.2.2. Market Share & Forecast

11.3.2.2.1. By Type

11.3.2.2.2. By Deployment Mode

11.3.2.2.3. By Providers

11.3.2.2.4. By Services

11.3.2.2.5. By Store Type

11.3.2.2.6. By End User

11.3.3. UAE Intelligent Apps Market Outlook

11.3.3.1. Market Size & Forecast

11.3.3.1.1. By Value

11.3.3.2. Market Share & Forecast

11.3.3.2.1. By Type

11.3.3.2.2. By Deployment Mode

11.3.3.2.3. By Providers

11.3.3.2.4. By Services

11.3.3.2.5. By Store Type

11.3.3.2.6. By End User

11.3.4. Saudi Arabia Intelligent Apps Market Outlook

11.3.4.1. Market Size & Forecast

11.3.4.1.1. By Value

11.3.4.2. Market Share & Forecast

11.3.4.2.1. By Type

11.3.4.2.2. By Deployment Mode

11.3.4.2.3. By Providers

11.3.4.2.4. By Services

11.3.4.2.5. By Store Type

11.3.4.2.6. By End User

12. Asia Pacific Intelligent Apps Market Outlook

12.1. Market Size & Forecast

12.1.1. By Value

12.2. Market Share & Forecast

12.2.1. By Type

12.2.2. By Deployment Mode

12.2.3. By Providers

12.2.4. By Services

12.2.5. By Store Type

12.2.6. By End User

12.2.7. By Country

12.3. Asia Pacific: Country Analysis

12.3.1. China Intelligent Apps Market Outlook

12.3.1.1. Market Size & Forecast

12.3.1.1.1. By Value

12.3.1.2. Market Share & Forecast

12.3.1.2.1. By Type

12.3.1.2.2. By Deployment Mode

12.3.1.2.3. By Providers

12.3.1.2.4. By Services

12.3.1.2.5. By Store Type

12.3.1.2.6. By End User

12.3.2. Japan Intelligent Apps Market Outlook

12.3.2.1. Market Size & Forecast

12.3.2.1.1. By Value

12.3.2.2. Market Share & Forecast

12.3.2.2.1. By Type

12.3.2.2.2. By Deployment Mode

12.3.2.2.3. By Providers

12.3.2.2.4. By Services

12.3.2.2.5. By Store Type

12.3.2.2.6. By End User

12.3.3. South Korea Intelligent Apps Market Outlook

12.3.3.1. Market Size & Forecast

12.3.3.1.1. By Value

12.3.3.2. Market Share & Forecast

12.3.3.2.1. By Type

12.3.3.2.2. By Deployment Mode

12.3.3.2.3. By Providers

12.3.3.2.4. By Services

12.3.3.2.5. By Store Type

12.3.3.2.6. By End User

12.3.4. India Intelligent Apps Market Outlook

12.3.4.1. Market Size & Forecast

12.3.4.1.1. By Value

12.3.4.2. Market Share & Forecast

12.3.4.2.1. By Type

12.3.4.2.2. By Deployment Mode

12.3.4.2.3. By Providers

12.3.4.2.4. By Services

12.3.4.2.5. By Store Type

12.3.4.2.6. By End User

12.3.5. Australia Intelligent Apps Market Outlook

12.3.5.1. Market Size & Forecast

12.3.5.1.1. By Value

12.3.5.2. Market Share & Forecast

12.3.5.2.1. By Type

12.3.5.2.2. By Deployment Mode

12.3.5.2.3. By Providers

12.3.5.2.4. By Services

12.3.5.2.5. By Store Type

12.3.5.2.6. By End User

13. Market Dynamics

13.1. Drivers

13.2. Challenges

14. Market Trends and Developments

15. Company Profiles

15.1. Google LLC

15.1.1. Business Overview

15.1.2. Key Financials & Revenue

15.1.3. Key Contact Person

15.1.4. Headquarters Address

15.1.5. Key Product/Service Offered

15.2. Microsoft Corporation

15.2.1. Business Overview

15.2.2. Key Financials & Revenue

15.2.3. Key Contact Person

15.2.4. Headquarters Address

15.2.5. Key Product/Service Offered

15.3. IBM Corporation

15.3.1. Business Overview

15.3.2. Key Financials & Revenue

15.3.3. Key Contact Person

15.3.4. Headquarters Address

15.3.5. Key Product/Service Offered

15.4. SAP SE

15.4.1. Business Overview

15.4.2. Key Financials & Revenue

15.4.3. Key Contact Person

15.4.4. Headquarters Address

15.4.5. Key Product/Service Offered

15.5. Amazon Web Services

15.5.1. Business Overview

15.5.2. Key Financials & Revenue

15.5.3. Key Contact Person

15.5.4. Headquarters Address

15.5.5. Key Product/Service Offered

15.6. Oracle Corporation

15.6.1. Business Overview

15.6.2. Key Financials & Revenue

15.6.3. Key Contact Person

15.6.4. Headquarters Address

15.6.5. Key Product/Service Offered

15.7. Apple Inc.

15.7.1. Business Overview

15.7.2. Key Financials & Revenue

15.7.3. Key Contact Person

15.7.4. Headquarters Address

15.7.5. Key Product/Service Offered

15.8. Intel Corporation

15.8.1. Business Overview

15.8.2. Key Financials & Revenue

15.8.3. Key Contact Person

15.8.4. Headquarters Address

15.8.5. Key Product/Service Offered

15.9. Baidu Inc.

15.9.1. Business Overview

15.9.2. Key Financials & Revenue

15.9.3. Key Contact Person

15.9.4. Headquarters Address

15.9.5. Key Product/Service Offered

15.10.Salesforce.com

15.10.1. Business Overview

15.10.2. Key Financials & Revenue

15.10.3. Key Contact Person

15.10.4. Headquarters Address

15.10.5. Key Product/Service Offered

16. Strategic Recommendations

17. About Us & Disclaimer

Figures and Tables

Frequently asked questions

What was the market size of the Global Intelligent Apps Market in 2022?

The market size of the global intelligent apps market was estimated to be USD 28.16 Billion in 2022.

Which was the dominant segment by type in the Global Intelligent Apps Market in 2022?

In 2022, enterprise apps were the dominant segment by type in the global intelligent apps market. Enterprise apps, enriched by AI and machine learning capabilities, offer businesses valuable tools to streamline operations, enhance decision-making, and optimize resource allocation. The increasing emphasis on digital transformation across industries fuels the demand for intelligent solutions that cater to enterprise-level complexities, making the enterprise apps segment a driving force in shaping the market's trajectory.

Which are the key players in the Global Intelligent Apps Market?

Key players in the market are Google LLC, Microsoft Corporation, IBM Corporation, SAP SE, Amazon Web Services, Oracle Corporation, Apple Inc., Intel Corporation, Baidu Inc., Salesforce.com and others.

What are the major drivers for the Global Intelligent Apps Market?

The advancements in Artificial Intelligence (AI) and Machine Learning (ML) and the proliferation of data generated by IoT devices, social media, and other sources provides are the major drivers for the global intelligent apps market.

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Sakshi Bajaal

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Press Release

Intelligent Apps Market to be Led by Growing Data-Driven Insights across the Globe Through 2028

Nov, 2023

Advancements in Artificial Intelligence (AI) and Machine Learning (ML) is driving the Implementation of Intelligent Apps market across the Globe.

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