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Multimodal AI Market Size reaching USD 23 Billion by 2035

The size of the global multimodal AI market was estimated to be USD 3.67 billion in 2024 and will grow at a compound annual growth rate (CAGR) of 35.8% from 2025 to 2035. Multimodal artificial intelligence (AI) uses a variety of data types, such as video, audio, speech, images, text, and conventional numerical data sets, to enhance its ability to make accurate predictions, draw insightful conclusions, and provide correct solutions to actual problems. This approach involves the training of AI systems to simultaneously synthesize and process multiple data sources so that they can have a better comprehension of content and context. With the growing usage of multimodal AI in a wide range of industries, the stakeholders are being offered a substantial opportunity to ride the growing market. By offering innovative multimodal AI solutions designed to address the unique requirements of different industries, stakeholders have a significant impact on fueling market growth.

Multimodal AI Market
Multimodal AI Market
Segments covered By Component, By Data Modality, By Technology, By Type, By Industry Vertical
Growth Drivers
  • Enhanced human-machine interaction
  • Industry-specific applications
  • 5G and edge computing
  • Corporate investments and partnerships
  • Advancements in natural language processing (NLP)
Pitfalls & Challenges
  • Data privacy and security concerns
  • Bias and fairness issues

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Multimodal AI Market Trends

One of the most significant trends in the multimodal AI industry is the combination of augmented reality (AR) and virtual reality (VR) technology. In multiple contexts, such as gaming, education, training, and distant collaboration, the combination creates immersive experiences that enhance user engagement. Multimodal AI in games can interpret voice instructions, facial expressions, and user gestures to create more responsive and engaging game worlds.

Through the combination of visual, aural, and kinesthetic learning styles, multimodal AI-driven AR and VR in learning deliver immersive and personalized learning experiences. These technologies provide authentic simulations for professional training skill enhancement, particularly in emergency response, aviation, and healthcare. Integrating AR, VR, and multimodal AI enhances user interaction and opens up new avenues for applications that need a high level of immersion and interactivity.

The use of edge computing and deployment of 5G networks is another prominent trend driving the multimodal AI industry. For real-time multimodal AI, edge computing reduces latency and bandwidth usage by processing information nearer to where it is created. This is particularly beneficial for intelligent systems and IoT devices, which rely on fast data processing to function optimally. The rollout of 5G has resulted in enhanced network capabilities that provide the speed and reliability needed to handle enormous volumes of multimodal data.

Multimodal AI Market Analysis
Discover more about the major segments defining this market

On the basis of data modality, the market is segmented into image data, text data, speech & voice data, video data, audio data. The speech & voice data segment is anticipated to hold a CAGR of more than 30% over the forecast period.

Within the multimodal AI field, the segment of voice data focuses on voice analysis and deployment of vocal features to obtain crucial information that lies beyond what a person speaks. This includes speaker recognition, emotions, and voice biometrics to authenticate individuals. Voice biometrics is a convenient and secure means of verifying individuals in financial transactions, security measures, and customer care uses via unique aspects of the voice. In order to determine the mood of the speaker, emotion detection analyzes tone, pitch, and speech patterns. This data is then used in mental health assessment, consumer attitude analysis, and personalized user experience.
The speech data segment significantly drives the multimodal AI industry, with that segment concentrating on technologies that allow for spoken language processing, recognition, and understanding. The use of applications such as voice recognition, speech-to-text transcription, and natural language understanding (NLU) in this section is because they play a key role in the evolution of more intuitive and accessible user interfaces. Speech data is utilized by AI call centers, for example, to understand and immediately respond to consumer questions in customer service, which increases productivity and satisfaction. Medical professionals are aided by speech recognition software in terms of patient note transcription and clinical documentation effectiveness. Advances in deep learning and acoustic modeling have significantly enhanced the accuracy and reliability of voice recognition systems, resulting in their wider application across industries.
Discover more about the most important segments influencing this market

On the basis of component, the multimodal AI market is segmented into solution and services. The solution segment held the largest share in the global market with a revenue of more than USD 8 billion in 2032.

In order to offer detailed insights and enhanced functionality, multimodal AI systems consist of an extensive array of applications designed to combine and interpret multiple sources of data, including text, images, video, and sensory input. The solutions consist of high-end analytics platforms that combine information from numerous sources to provide actionable insights in various sectors like health, finance, and marketing. They also encompass virtual assistants and chatbots with sophisticated features that can understand and respond to multiple input forms.
These systems, which possess capabilities such as real-time processing of data, automated decision-making, and predictive analysis, are tailored to directly meet the needs of different industries. In order to take advantage of multimodal AI, companies are continually developing new platforms and tools as a response to increasing demands for more responsive and smart systems.
Increasing data environment complexity and the need for solutions that can integrate and comprehend multiple data streams seamlessly are fueling market growth.

Segments covered Component, data modality, end-use, enterprise size, and region
Regional scope North America; Europe; Asia Pacific; Latin America; MEA
Country scope U.S.; Canada; Germany; UK; France; China; Japan; India; South Korea; Australia; Brazil; Mexico; KSA; UAE; South Africa
Key companies profiled Aimesoft; Amazon Web Services, Inc.; Google LLC; IBM Corporation; Jina AI GmbH; Meta.; Microsoft; OpenAI, L.L.C.; Twelve Labs Inc.; Uniphore Technologies Inc.
Customization scope Free report customization (equivalent up to 8 analysts working days) with purchase. Addition or alteration to country, regional & segment scope.

 

 

Market, By Component

  • Solution
  • Service

Market, By Data Modality

  • Image data
  • Text data
  • Speech & voice data
  • Video data
  • Audio data

Market, By Technology

  • Machine learning
  • Natural language processing
  • Computer vision
  • Context awareness
  • Internet of things

Market, By Type

  • Generative multimodal AI
  • Translative multimodal AI
  • Explanatory multimodal AI
  • Interactive multimodal AI

Market, By Industry Vertical

  • BFSI
  • Retail & E-commerce
  • IT & telecommunication
  • Government & Public sector
  • Healthcare
  • Manufacturing
  • Media & Entertainment
  • Others

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Banking and Finance News

India Wealth Management Market: Trends, Growth, and Forecast (2025-2029)

Introduction

The India Wealth Management Market was valued at USD 429.1 billion in 2023 and is expected to grow at a CAGR of 4.56% from 2024 to 2029. Driven by the rising number of High-Net-Worth Individuals (HNWIs), increased financial literacy, and advancements in digital wealth solutions, the market is undergoing a major transformation. Banks, NBFCs, and consulting firms are strengthening their wealth management portfolios to cater to an evolving investor base.

Market Trends

  1. Rise in Digital Wealth Platforms – The increasing adoption of AI-driven robo-advisors and mobile-based investment apps is simplifying wealth management.
  2. Growth of Portfolio Management Services – Investors are shifting towards customized portfolio solutions to optimize risk and returns.
  3. Alternative Investment Boom – HNWIs are increasingly diversifying into private equity, real estate, and ESG (Environmental, Social, and Governance) investments.
  4. Regulatory Reforms Enhancing Transparency – SEBI regulations and the Investment Adviser Regulations have strengthened compliance in the sector.
  5. Hybrid Advisory Models – A combination of automated tools and human advisory services is redefining wealth management strategies.
  6. Expansion of Wealth Services in Tier 2 & Tier 3 Cities – Growing financial awareness in smaller cities is unlocking new opportunities for wealth managers.

𝐑𝐞𝐪𝐮𝐞𝐬𝐭 𝐏𝐃𝐅 𝐒𝐚𝐦𝐩𝐥𝐞 𝐂𝐨𝐩𝐲 𝐨𝐟 𝐑𝐞𝐩𝐨𝐫𝐭: (𝐈𝐧𝐜𝐥𝐮𝐝𝐢𝐧𝐠 𝐅𝐮𝐥𝐥 𝐓𝐎𝐂, 𝐋𝐢𝐬𝐭 𝐨𝐟 𝐓𝐚𝐛𝐥𝐞𝐬 & 𝐅𝐢𝐠𝐮𝐫𝐞𝐬, 𝐂𝐡𝐚𝐫𝐭) @

👉https://www.marketinsightsresearch.com/request/download/9/56253/India-Wealth-Management-Market 

 

Market Challenges

  • Regulatory Compliance – New regulations demand strict adherence to fiduciary standards, posing challenges for traditional wealth managers.
  • Competition from Fintech Firms – Established players face competition from tech-driven startups offering low-cost investment solutions.
  • Economic Volatility – Fluctuations in global and domestic markets impact investment decisions and portfolio strategies.
  • Shifting Investor Preferences – Growing demand for sustainable and impact investing requires wealth managers to expand their offerings.

Dominating & Fastest-Growing Segments

Dominating Provider: Banks lead the market due to their trusted customer relationships and diverse investment products.

Fastest-Growing Segment: Portfolio Management Services are witnessing high demand as investors seek personalized wealth solutions and risk-managed investments.

𝗕𝘂𝘆 𝗡𝗼𝘄 𝗟𝗮𝘁𝗲𝘀𝘁 𝗘𝗱𝗶𝘁𝗶𝗼𝗻 𝗼𝗳 India Wealth Management 𝗠𝗮𝗿𝗸𝗲𝘁 𝗥𝗲𝗽𝗼𝗿𝘁

https://www.marketinsightsresearch.com/report/buy_now/9/56253/India-Wealth-Management-Market 

Segmental Insights

Type

  • Financial Advice Management – Offering tailored investment strategies and tax planning.
  • Portfolio Management – Managing diversified portfolios for optimized returns.
  • Performance Management – Tracking and evaluating asset performance in real time.

End-User

  • High Net Worth Individuals (HNWIs) – Individuals with assets over $1 million, seeking expert wealth management solutions.
  • Ultra-High Net Worth Individuals (UHNWIs) – Investors with assets exceeding $30 million, requiring specialized investment and estate planning services.
  • Corporates – Businesses managing investment funds and corporate wealth strategies.
  • Others – Includes institutional investors and family offices.

Provider

  • Banks – Dominating segment, offering a comprehensive range of wealth management services.
  • NBFCs (Non-Banking Financial Companies) – Emerging players providing customized financial solutions.
  • Consulting Firms – Offering specialized investment planning and wealth advisory services.

𝗚𝗲𝘁 𝟭𝟬-𝟮𝟱% 𝗗𝗶𝘀𝗰𝗼𝘂𝗻𝘁 𝗼𝗻 𝗜𝗺𝗺𝗲𝗱𝗶𝗮𝘁𝗲 𝗽𝘂𝗿𝗰𝗵𝗮𝘀𝗲

https://www.marketinsightsresearch.com/report/buy_now/9/56253/India-Wealth-Management-Market 

 

Regional Market Analysis

Forecast Period 2025-2029
Market Size (2023) USD 429.1 Billion
CAGR (2024-2029) 4.56%
Fastest Growing Segment Portfolio Management
Largest Market South Region

Key Market Players

  • 360 One WAM Limited
  • Kotak Investment Advisors Limited
  • Aditya Birla Finance Limited
  • Avendus Capital Pvt. Ltd.
  • Anand Rathi Wealth Limited
  • Bajaj Capital Limited
  • HDFC Bank Ltd.
  • Morgan Stanley Financial Advisors
  • Motilal Oswal Financial Services Ltd.
  • ICICI Bank Limited

Recent Developments

  • 2023: SEBI introduced new guidelines for Registered Investment Advisors (RIA) to enhance transparency and investor protection.
  • 2023: Wealth management firms launched AI-powered financial planning tools to provide automated, real-time investment strategies.
  • 2022: Expansion of alternative investment funds (AIFs) in India, offering investors access to hedge funds, venture capital, and private equity.

Conclusion

The India Wealth Management Market is set for steady growth, fueled by technological advancements, regulatory support, and evolving investor needs. With increasing adoption of digital investment platforms, AI-driven wealth management, and personalized portfolio solutions, the industry is on a path of transformation. As financial awareness grows and investment trends evolve, customized and technology-driven wealth management solutions will be key to sustaining market expansion.

 

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SVoD Market Valuation 2025-2035

Increased internet penetration and increased usage of smart devices have greatly contributed to the growth of the Subscription Video on Demand (SVoD) market, as content availability has been increased among different demographics. As per the analyst at Verified Market Research, the SVoD Market is expected to achieve a valuation of USD 39.46 Billion in the forecast period dominating approximately USD 29.38 Billion worth in 2024.

The fast growth of the SVoD market is mainly fueled by the growing consumer demand for original content, as streaming platforms are increasingly investing in exclusive content to attract and retain subscribers. It allows the market to grow at a CAGR of 16.51% during 2024-2035.

SVoD Market
SVoD Market
Report Attribute Details
Base Year 2024
SVOD Market Size in 2024 USD 29.38 Billion
Forecast Period 2024 – 2035
Forecast Period 2024 – 2032 CAGR 16.51%
2035 Value Projection USD 39.46 Billion
Historical Data for 2021 – 2024
No. of Pages 460
Tables, Charts & Figures 300
Segments covered Content, Pricing Model, Device
Growth Drivers
  • Increasing internet penetration
  • Rising adoption of smart devices
  • Increasing consumer demand for flexibility
  • Rising innovations in streaming technology
Pitfalls & Challenges
  • High content licensing and production costs
  • Growing digital piracy and unauthorized distribution of content

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https://www.marketinsightsresearch.com/request/download/8/620/SVOD-Market

What Effect is the Rising Investment in Original Content Having on Subscriber Growth within the SVoD Market?
The growing investment in original content is identified as a key contributor to subscriber growth in the SVoD market, as exclusive content is in demand by consumers looking for differentiated entertainment experiences. It has been observed that Netflix, Amazon Prime Video, and Disney+ have invested heavily in creating original series and movies, thus enriching their content. Netflix’s spend on original content was USD 13 Billion in 2023. Disney+ spent USD 33 Billion on content in financial year 2022, out of which about 40% went towards originals.

This approach has been taken to distinguish services in an oversaturated market, where customer options are growing at a high rate. Therefore, it has been seen that the presence of high-quality, premium content is directly related to subscriber acquisition and retention, creating a strong growth path for SVoD operators.

How is the Increasing Competition Among Streaming Services Influencing Pricing Strategies in the SVoD Market?
The increasing competition between streaming services is influencing pricing tactics in the SVoD market, where aggressive pricing strategies are being more extensively adopted to gain and retain customers. It has been reported that a majority of platforms have adopted promotional pricing, bundling, and tiered subscription levels to be better positioned in the market.

Since competitors struggle to achieve bigger market shares, pricing strategies are often sustainability assessed to maintain profitability while also being attractive to consumers. Moreover, consumers have been found to become increasingly price-conscious, forcing providers to re-evaluate their pricing models and introduce more elastic subscription plans, hence determining the competitive dynamics of the SVoD industry.

SVOD Market Trends

Upgrade of the SVOD experience mostly depends on technical enhancements. Upgrade in streaming technology, particularly in immersive audio forms like Dolby Atmos, 4K Ultra HD, and High Dynamic Range (HDR), are beginning to be provided as part of basic offerings. Improved image and sound quality is made possible by these technologies, adding depth and delight to the viewing experience. In addition, improved streaming protocols like adaptive bitrate streaming ensure smooth play even in dynamic internet conditions. Moreover, interfaces of platforms are evolving with greater interactive elements, voice search functionality, and artificial intelligence-based content discovery features incorporated.
As the streaming universe becomes increasingly populated, new streaming platforms are emerging left and right, but with a twist: they’re not attempting to be all things to all people. Rather, these “niche” streaming platforms are going after specific groups of individuals with very specific tastes. They realize there are many people who adore horror films, anime, docs, or indie features, but won’t necessarily discover what they want on the larger streaming giants such as Netflix or Hulu. That’s where the niche services step in, plunging into that particular category and building a destination for its followers. For instance, look at Shudder. It only has horror content and TV programs. Or Crunchyroll, the destination for anime fans. By doing one thing, these sites are able to create a genuinely dedicated following of fans and provide programming and films that the giants may not even be aware of. This movement indicates that there’s space for any type of streaming site in the world. The large ones have a little of everything, but these niche operations can delve deeply into what their audience loves and are thus ideal for fans who wish to experience their preferred genres to the fullest.

SVOD Market Share
Netflix and Amazon Prime Video hold a big market share of more than 45% of the SVOD market. They are companies that have distinctive styles and content portfolios that speak for themselves. Being the pioneer in the streaming era, companies possess a huge global user base that is drawn towards its enormous library of original content, including highly acclaimed series and an extensive catalog of films. The commitment of the platform to producing original, high-quality content has boosted its image and sustained subscriber loyalty worldwide.

Alternatively, the companies have readily captured market share due to its mythical properties, including masterpieces of animation. The strategy for the platform, aided by proprietary releases, focuses on nostalgia and family-friendly content. International growth initiatives, technology innovations, and strategic partnerships drive companies disrupting and cementing positions as industry titans shaping global entertainment consumption.

Quantitative Units Value in USD Billion
Report Coverage Historical and Forecast Revenue Forecast, Historical and Forecast Volume, Growth Factors, Trends, Competitive Landscape, Key Players, Segmentation Analysis
Segments Covered
  • Content Type
  • Device Type
  • Subscription Type
  • Revenue Model
  • Platform Type
  • End-User
Regions Covered
  • North America
  • Europe
  • Asia Pacific
  • Latin America
  • Middle East & Africa
Key Players Amazon Prime Instant Video, Claro Video, Crackle, Globo Play, HBO, Hulu, Netflix.
Customization Report customization along with purchase available upon request

SVoD Market, By Category

Content Type:

  • Movies
  • TV Shows
  • Sports
  • Kids’ Content
  • Documentaries
  • Original Content

Device Type:

  • Smartphones and Tablets
  • Laptops and Desktops
  • Smart TVs
  • Gaming Consoles
  • Set-top Boxes
  • Streaming Media Players

Subscription Type:

  • Monthly Subscription
  • Annual Subscription
  • Pay-Per-View
  • Freemium

Revenue Model:

  • Ad-free Subscription
  • Ad-supported Subscription
  • Hybrid

Platform Type:

  • International Platforms
  • Regional/Local Platforms
  • Niche Platforms

End-User:

  • Individual Subscribers
  • Households
  • Enterprises

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SVOD Industry News
The Walt Disney Company’s partnership with Apple Vision Pro in January 2024 was giant strides into the future of entertainment and storytelling. Leveraging the power of Apple’s state-of-the-art Augmented Reality (AR) technology, Disney sought to transform the way audiences engage with their favorite stories and characters.
In December 2023, IPG Media brands and Amazon signed a landmark three-year agreement to help brands reach audiences via Prime Video ads. The alliance highlighted the growing role of streaming platforms in ad strategies and the expanding role of Amazon in the digital ad ecosystem. With this alliance, they gained access to a treasure trove of targeting and measurement capabilities to reach viewers on Prime Video. This involved taking advantage of Amazon’s wealth of data intelligence to identify precise audience segments and fine-tune ad campaigns for optimal performance.

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Banking and Finance Cybersecurity News

India Home Insurance Market: Size, Share, Trends, Growth, and Forecast (2025-2029)

Introduction

The India Home Insurance Market was valued at USD 13.23 billion in 2023 and is projected to grow at a CAGR of 6.50% from 2024 to 2029. The increasing awareness of home insurance benefits, rising incidences of natural disasters, and growing homeownership rates are key drivers of market expansion. Additionally, digital transformation and online distribution channels are making home insurance more accessible, contributing to market growth.

Market Trends

  1. Digital Transformation & Online Purchases – The online segment is the fastest-growing mode of purchase, offering convenience and easy policy comparisons.
  2. Rising Demand for Structural & Content Coverage – Homeowners are opting for comprehensive insurance policies that cover structural damage, fire, theft, and personal belongings.
  3. Government Initiatives & Regulatory Push – Government-backed schemes are encouraging greater penetration of home insurance.
  4. Customized & Flexible Premium Options – Insurers are introducing flexible payment models, including regular and single premium options.
  5. Emerging Role of Insurtech Companies – Technology-driven companies are simplifying the policy-buying process and enhancing customer experience.
  6. Increased Awareness of Disaster Protection – Growing concerns over floods, earthquakes, and cyclones are leading to higher demand for home insurance.

𝐑𝐞𝐪𝐮𝐞𝐬𝐭 𝐏𝐃𝐅 𝐒𝐚𝐦𝐩𝐥𝐞 𝐂𝐨𝐩𝐲 𝐨𝐟 𝐑𝐞𝐩𝐨𝐫𝐭: (𝐈𝐧𝐜𝐥𝐮𝐝𝐢𝐧𝐠 𝐅𝐮𝐥𝐥 𝐓𝐎𝐂, 𝐋𝐢𝐬𝐭 𝐨𝐟 𝐓𝐚𝐛𝐥𝐞𝐬 & 𝐅𝐢𝐠𝐮𝐫𝐞𝐬, 𝐂𝐡𝐚𝐫𝐭) @

👉https://www.marketinsightsresearch.com/request/download/9/56254/India-Home-Insurance-Market 

 

Market Challenges

  • Low Awareness & Penetration – Despite growing interest, home insurance adoption remains low compared to other insurance segments.
  • Price Sensitivity & Affordability Issues – Many homeowners hesitate to invest in home insurance due to perceived high costs.
  • Trust Deficit in Insurance Providers – Concerns over claim settlements and policy transparency affect consumer confidence.
  • Limited Distribution & Accessibility – Rural regions have lower accessibility to insurance providers and awareness programs.

Dominating & Fastest-Growing Segments

Dominating Provider: Insurance Companies hold the largest market share due to their extensive policy offerings and established trust.

Fastest-Growing Segment: Online Mode of Purchase is experiencing rapid adoption due to convenience, seamless policy issuance, and digital payment integration.

Segmental Insights

Type

  • Structural Cover – Protects the physical structure from fire, vandalism, and natural calamities.
  • Home Content Cover – Covers personal belongings like furniture, electronics, and appliances.
  • Fire Cover – Provides financial protection against fire and smoke damage.
  • Theft Cover – Covers loss or damage due to burglary or forced entry.
  • Others – Includes landlord and tenant insurance, offering rental property protection.

Provider

  • Insurance Companies – The dominant segment offering comprehensive home insurance policies.
  • Insurance Agents & Brokers – Play a crucial role in advising customers and tailoring policies.
  • Insurtech & Third-Party Providers – Technology-driven firms simplifying policy issuance and claims.

Premium Type

  • Regular Premium – Preferred for long-term policies with flexible payments.
  • Single Premium – Gaining popularity for one-time, hassle-free coverage.

Mode of Purchase

  • Online – Fastest-growing due to digital adoption, offering quick comparisons and seamless transactions.
  • Offline – Still relevant for customers who prefer traditional agent-assisted services.

𝗕𝘂𝘆 𝗡𝗼𝘄 𝗟𝗮𝘁𝗲𝘀𝘁 𝗘𝗱𝗶𝘁𝗶𝗼𝗻 𝗼𝗳 India Home Insurance Market 𝗥𝗲𝗽𝗼𝗿𝘁

https://www.marketinsightsresearch.com/report/buy_now/9/56254/India-Home-Insurance-Market 

 

Regional Market Analysis

Forecast Period 2025-2029
Market Size (2023) USD 13.23 Billion
CAGR (2024-2029) 6.50%
Fastest Growing Segment Online Mode of Purchase
Largest Market Insurance Companies

Key Market Players

  • The New India Assurance Co. Ltd.
  • ICICI Lombard General Insurance Company Limited
  • HDFC ERGO General Insurance Co. Ltd.
  • Bajaj Allianz General Insurance Company Limited
  • National Insurance Company Limited
  • The Oriental Insurance Company Ltd.
  • SBI General Insurance Company Limited
  • United India Insurance Company Limited
  • Tata AIG General Insurance Company Limited
  • Reliance General Insurance Company Limited

Recent Developments

  • 2023: The New India Assurance Co. Ltd. launched an AI-driven home insurance claims processing system to improve claim settlements.
  • 2022: HDFC ERGO introduced a customizable home insurance policy with modular coverage options and digital onboarding.

𝗚𝗲𝘁 𝟭𝟬-𝟮𝟱% 𝗗𝗶𝘀𝗰𝗼𝘂𝗻𝘁 𝗼𝗻 𝗜𝗺𝗺𝗲𝗱𝗶𝗮𝘁𝗲 𝗽𝘂𝗿𝗰𝗵𝗮𝘀𝗲

https://www.marketinsightsresearch.com/request/discount/9/56254/India-Home-Insurance-Market 

Conclusion

The India Home Insurance Market is witnessing steady growth, fueled by digital transformation, customized policies, and increased consumer awareness. The shift towards online policy purchases, government support, and innovative insurance solutions will further drive market expansion. Addressing price sensitivity, transparency, and accessibility issues will be key to unlocking the market’s full potential.

 

Categories
Banking and Finance Cybersecurity News

Global Digital Banking Platform Market: Size, Share, Trends, Growth, and Forecast (2018-2028)

Introduction

The Global Digital Banking Platform Market was valued at USD 7.38 billion in 2022 and is projected to grow at a CAGR of 13.82% from 2023 to 2028. With increasing digital adoption, financial institutions are shifting towards cloud-based banking solutions, open banking, and API integrations to enhance customer experiences and improve operational efficiency.

Market Trends

  1. Mobile-First Approach – Financial institutions prioritize mobile banking for seamless, on-the-go banking experiences with enhanced security and biometric authentication.
  2. Open Banking & API Integration – APIs enable seamless data sharing, enhancing customer engagement and financial product accessibility.
  3. Cloud-Based Solutions Dominance – Cloud deployment is accelerating, reducing IT costs and enabling faster scalability and real-time data access.
  4. Blockchain & AI Integration – AI-driven insights and blockchain security innovations are transforming banking operations and fraud detection.
  5. Financial Inclusion & Digital Expansion – Digital banking is bridging gaps in financial access, especially in emerging markets.
  6. Regulatory Compliance & Cybersecurity – Increased focus on data security, compliance, and fraud prevention in digital banking solutions.

Market Challenges

  • Regulatory Complexities – Evolving compliance requirements across regions add operational challenges.
  • Cybersecurity Threats – Rising digital fraud and cyberattacks require advanced security measures.
  • Infrastructure Costs & Integration Issues – Transitioning from legacy systems to cloud-based platforms requires investment and technical expertise.

𝐑𝐞𝐪𝐮𝐞𝐬𝐭 𝐏𝐃𝐅 𝐒𝐚𝐦𝐩𝐥𝐞 𝐂𝐨𝐩𝐲 𝐨𝐟 𝐑𝐞𝐩𝐨𝐫𝐭: (𝐈𝐧𝐜𝐥𝐮𝐝𝐢𝐧𝐠 𝐅𝐮𝐥𝐥 𝐓𝐎𝐂, 𝐋𝐢𝐬𝐭 𝐨𝐟 𝐓𝐚𝐛𝐥𝐞𝐬 & 𝐅𝐢𝐠𝐮𝐫𝐞𝐬, 𝐂𝐡𝐚𝐫𝐭) @

👉https://www.marketinsightsresearch.com/request/download/9/56255/Digital-Banking-Platform-Market 

 

Dominating & Fastest-Growing Regions

Dominating Region: North America leads due to high digital banking adoption, cloud innovations, and advanced cybersecurity measures.

Fastest-Growing Region: Asia-Pacific is witnessing rapid growth due to increasing mobile banking penetration and government initiatives promoting financial digitization.

Segmental Insights

Deployment

  • Cloud-Based Solutions – The fastest-growing segment, offering scalability, cost efficiency, and enhanced digital banking capabilities.
  • On-Premises Solutions – Preferred by institutions with stringent data security and compliance requirements.

Type

  • Retail Banking – Driving growth with user-friendly mobile apps, AI-driven financial services, and digital payment integration.
  • Corporate Banking – Increasing adoption of digital banking solutions for business transactions, real-time payments, and automated financial management.

𝗕𝘂𝘆 𝗡𝗼𝘄 𝗟𝗮𝘁𝗲𝘀𝘁 𝗘𝗱𝗶𝘁𝗶𝗼𝗻 𝗼𝗳Digital Banking Platform Market 𝗥𝗲𝗽𝗼𝗿𝘁

https://www.marketinsightsresearch.com/report/buy_now/9/56255/Digital-Banking-Platform-Market 

 

Regional Market Analysis

Forecast Period 2024-2028
Market Size (2022) USD 7.38 Billion
CAGR (2023-2028) 13.82%
Fastest Growing Segment Cloud-Based Solutions
Largest Market North America

Key Market Players

  • Appway AG
  • CREALOGIX Holding AG
  • EdgeVerve Systems Limited
  • Fiserv, Inc.
  • Oracle Corporation
  • SAP SE
  • Sopra Steria
  • Tata Consultancy Services Limited
  • Temenos Headquarters SA
  • Worldline SA

Recent Developments

  • 2023: Axis Bank partnered with OPEN to launch a fully digital business banking platform for SMEs and freelancers.
  • 2022: Capco and Savana collaborated to accelerate digital banking transformation and improve customer experience.
    𝗚𝗲𝘁 𝟭𝟬-𝟮𝟱% 𝗗𝗶𝘀𝗰𝗼𝘂𝗻𝘁 𝗼𝗻 𝗜𝗺𝗺𝗲𝗱𝗶𝗮𝘁𝗲 𝗽𝘂𝗿𝗰𝗵𝗮𝘀𝗲

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Conclusion

The Global Digital Banking Platform Market is evolving rapidly, driven by mobile-first strategies, cloud-based adoption, AI innovations, and API-driven open banking. As financial institutions embrace digital transformation, cybersecurity, and personalized banking experiences, the market is set for continued expansion, reshaping the global financial ecosystem.

 

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Metaverse for Automotive Market will hit USD 25.34 Billion by 2035

Metaverse in Automotive Market size was USD 3.99 billion in 2024 and the overall Metaverse in Automotive revenue is anticipated to grow at a CAGR of 38.34% during the forecast period from 2024 to 2035, reaching almost USD 25.34 Billion by 2035.

Metaverse in Automotive Market Overview

Metaverse is a virtual reality environment that has the ability to accommodate a variety of online interactions. From designing products to procuring, from manufacturing to inventory, Metaverse technology can be utilized to tighten and optimize supply chain management for the Automotive Industry.

Segments covered Component, Application, Technology
Growth Drivers
  • Growing improvements in VR and AR technologies enable more immersive and interactive experiences
  • Rising consumers preferences towards more personalized and engaging experiences
  • Advancements in technology such as mixed reality in automobile sectors
  • Increasing focus towards software and cloud services in automotive applications
  • Rising digitalization in the automotive industry
Pitfalls & Challenges
  • High development costs
  • Increased connectivity and data exchange in the metaverse pose significant cybersecurity risks

Metaverse for Automotive Market image

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What are the growth prospects in this industry?

The constant innovations in VR and AR technologies are unlocking new opportunities for the automotive industries, from design & manufacturing to sales & customer care. These technologies not only add value to the user experience but also enhance efficiency, safety, and innovations in the car industry. As VR and AR advance, their application in the automotive sector is also likely to increase, with even more revolutionary changes. AR is proving to be helpful in supporting technicians while working on maintenance and repairs by projecting instructions and diagrams onto the actual vehicle.

As cars and user information become part of an integrated digital world, the threat of hacking and data theft is steadily increasing. Cybercriminals are after personal data, vehicle control units, and proprietary data, which may result in serious financial and reputational losses to the users and the organizations. Most of today’s vehicles have IoT devices that communicate with outside systems, and if businesses are not experiencing strong security, such devices can act as doors to cyberattacks, potentially undermining the safety of vehicles and user privacy.

The automotive sector needs to put in place strong incident response procedures to quickly deal with and reduce the effects of cybersecurity attacks. Moreover, the use of continuous monitoring systems to identify and respond to possible threats in real-time is essential in ensuring a secure metaverse.

Metaverse for Automotive Industry Trends

The latest developments in Mixed Reality (MR) technology have the potential to transform the automotive industry because it provides a combination of physical and virtual experiences that improve everything from car design to customer engagement. MR, which combines aspects of Virtual Reality (VR) and Augmented Reality (AR), is being more widely incorporated into all areas of automobile innovation and consumer interaction. For example, in January 2024, Porsche began to integrate MR technology into its customer experience strategy. This new development is designed to provide an unmatched degree of immersion and interactivity, revolutionizing the manner in which customers interact with cars.

With more emphasis on cloud and software integration to aid metaverse applications, numerous organizations are embracing cloud services. This includes the use of cloud-based platforms for real-time data processing, vehicle connectivity, and immersive virtual experiences like virtual test drives and showrooms. Beyond that, sophisticated software solutions allow for complete integration of AR and VR technologies, making it possible to perform complex product customization, simulation, and remote diagnostics, ultimately driving innovations and enhancing customer interaction in the automotive sector.

For example, in February 2024, Capgemini and Unity Technologies revealed a broadened strategic partnership, disclosing Capgemini’s acquisition of Unity’s Digital Twin Professional Services business. As part of this deal, Unity’s Digital Twin Professional Services team will become part of Capgemini, creating one of the largest teams of Unity enterprise developers in the world. This is to speed up the development and deployment of real-time 3D (RT3D) visualization software, particularly for industrial digital twin use cases. The integration will allow end users to better visualize, understand, and interact with physical systems, promoting intelligent industry capabilities.

Metaverse for Automotive Market Share
BMW Group & Mercedes-Benz AG collectively owned more than 30% stake in metaverse for automotive industry in 2023. BMW Group, one of the prominent luxury automobile manufacturers, has been actively involved in exploring and investing in metaverse technologies to increase its brand presence, customer experience, and product development process. The company recognizes the capability of the metaverse to transform the automotive sector and has undertaken a number of initiatives to place itself at the vanguard of this new technology.

Mercedes-Benz AG is a world-famous German luxury car manufacturer with a rich history and global presence. Mercedes-Benz is utilizing metaverse technologies to develop digital replicas of their cars and manufacturing facilities. This enables more effective design iterations, virtual testing, and optimization of the manufacturing process, which could shorten development time and expenses.

Metaverse for Automotive Market Companies
Key players involved in the metaverse for automotive sector are

BMW Group
Mercedes-Benz AG
Toyota Motor Corporation
Ford Motor Company
General Motors (GM)
Unity Technologies
Nvidia Corporation

The metaverse for automotive market research report  has segmented like below

Market, By Component

  • Hardware
    • VR headsets
    • AR glasses
    • Haptic devices
    • 3D projectors
  • Software
    • Metaverse platforms
    • Simulation software
    • Design and prototyping software
    • Customer experience software
  • Services
    • Consulting services
    • Implementation services
    • Training and support services
    • Maintenance and upgrades

Market, By Application

  • Virtual showrooms and dealerships
  • Training and education
  • Design and prototyping
  • Customer experience and engagement
  • Marketing and advertising
  • Others

Market, By Technology

  • Virtual Reality (VR)
  • Augmented Reality (AR)
  • Mixed Reality (MR)
  • Blockchain and NFTs

Metaverse in Automotive Market Segment By Technology

According to Technology, the Virtual Reality (VR) segment dominated with the highest market share of around 60% of the Global Metaverse in the Automotive Market. Based on the analysis by MMR, the segment is also expected to develop at a growth rate of CAGR 34.6% during the forecast period and remains the largest segment in the Global Metaverse in the Automotive Market. The growing adoption of Virtual reality (VR) platforms in the development of in-car reality entertainment systems is expected to be supported by the rapid expansion of virtual platforms. The leading players such as Oculus (acquired by Facebook), HTC, Sony, Microsoft, and Google are leaders in VR technology development, developing innovative VR experiences and immersive spaces for different applications, including automotive, entertainment, and training.

VR technology adds value to the automotive experience of customers in various ways like replicating the feel of driving a vehicle, and assisting in designing, developing, and testing cars, thus enabling designers to design and test vehicle features virtually. VR technology is utilized to boost customer experiences by offering interactive and immersive 360-degree virtual tours, thus speeding up the purchasing process and improving customer retention rates. Also, VR is employed to develop virtual showrooms, which allow consumers to browse various cars, enhance the car buying experience, and make informed choices without biased sales environments. VR is also being utilized for staff training to offer realistic settings for learning and enabling staff to rehearse activities like component installation within given time limits. Application of VR technology by the automotive segment provides advantages that include enhanced employee training, efficient product design, and development along with engaging experiences for customers allowing the segment to dominate the industry.

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Causal AI Market is projected to grow USD 17.84 Billion by 2035

Causal AI Market is projected to grow from USD 2.71 Billion in 2025 to USD 17.84 Billion by 2034, exhibiting a compound annual growth rate (CAGR) of 19.83% during the forecast period (2025 – 2035).

Key Causal AI Market Trends Identified

As more companies seek to comprehend cause-and-effect relationships more deeply, the demand for Causal AI is increasing across the world. The demand for better predictive analytics, the rising complexity of business environments, and the broadening acceptance of decision-making via AI are the primary drivers of the industry.
There are numerous opportunities to discover and capture the market. There is immense potential for enhancing predictive abilities and decision-making processes by combining Causal AI with other technologies, such as data analytics and machine learning.
More chances for growth are brought about by increased application of Causal AI in supply chain management, finance, and healthcare.
Probabilistic causal models that provide more accurate and understandable results are increasingly in demand in the Causal AI industry. Organisations are also able to easily utilize this technology due to increased access to Causal AI tools and platforms.

Causal AI Market

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Casual AI Market Analysis

According to the offering, the market is bifurcated into platform and services. The platform segment controls the market and is anticipated to exceed USD 362 million by 2032.

In the tech sector, software or hardware environments that allow programmers to build apps, services, or solutions are known as platforms. These platforms provide frameworks, interfaces, and required tools making it simpler to plan, implement, and manage diverse technologies. Cloud computing platforms (e.g., AWS, Azure), AI development frameworks (e.g., TensorFlow, PyTorch), and application platforms (e.g., iOS, Android) are platforms when it comes to AI and tech innovation.
They offer attributes such as data analysis, security, and integration capability, and they are interoperable and scalable. Through the ability to help developers build and deploy new technologies efficiently, platform providers play an important role in fostering innovation and driving growth and development throughout industries.

Segmented on the basis of end-user industry, the market for casual AI is classified into consumer electronics, healthcare, retail and e-commerce, media and entertainment automotive, BFSI, education, travel and hospitality, utilities and energy, others. The segment of healthcare is the most rapid growing segment with a CAGR of more than 44% during 2032.

The healthcare industry encompasses a wide range of services and technologies aimed at improving patient care, medical treatment, and administrative efficiency in the healthcare industry. This range of technologies encompasses wearable health devices, medical imaging equipment, telemedicine solutions, electronic health records (EHR), and AI-based diagnostics. These technologies enhance the delivery of healthcare by enabling data-driven decision-making for treatment plans, real-time monitoring of patient vital signs, and remote consultations.

In addition, through simplifying tasks such as billing and scheduling, healthcare IT systems reduce operating expenditures and improve the quality of outcomes. In their effort to provide more personalized, convenient, and efficient healthcare services globally, the healthcare sector continually evolves in association with developments in medical technology.

Casual AI Market Share
Hello! Microsoft and IBM are big boys in the casual AI marketplace, with a combined market share of over 23%. Microsoft is a giant here, leveraging its Azure cloud as a springboard for AI services across various sectors. They’re also integrating AI into our living rooms with gadgets such as Xbox consoles, smartening and making them more fun. Consider those AI-driven capabilities in Office 365 or Cortana, the digital assistant. That’s purely Microsoft. And they’re investing heavily in AI research, on areas such as machine learning, computer vision, and natural language processing. This makes it easier for developers to build even more awesome AI solutions.

IBM is a well-known name in the latenight AI Market, especially through its Watson AI platform. IBM uses AI technologies in customer-facing applications like AI chatbots and virtual assistants, which increase customer interaction and support. IBM also uses AI in enterprise products like IBM Watson Analytics so that businesses can utilize AI to make informed decisions and derive insights. IBM’s AI initiatives are directed toward the world-wide transformation of consumer experiences and operational effectiveness, targeting sectors like healthcare, banking, and retail.

Casual AI Market Companies
Key players in the Casual AI market are

Amazon.com, Inc.
Facebook, Inc.
Google LLC
IBM Corporation
Microsoft Corporation
Oracle Corporation
SAP SE

Casual AI Industry News

Google launched major enhancements to its everyday AI models in March 2024, deepening user experience with Google Assistant. The updates target enhancing the understanding of voice commands and contextualized responses towards a more seamless user experience across devices. These updates are crafted to streamline interactions and make them more natural for users to get involved with Google Assistant in various aspects of day-to-day operations and queries.
In February of 2024, Amazon introduced new features, which utilized casual AI for tailored shopping suggestions. Utilizing advanced AI algorithms, Amazon currently personalizes product recommendations through user browsing history and shopping behavior. This feature is designed to enhance the shopping experience by displaying relevant products more accurately in line with personal preferences. Utilizing AI potential, Amazon aims to increase customer satisfaction and interaction through a more personalized and user-friendly shopping experience

The casual AI market research report has the following segments

Market, Offering

  • Platform
    • Deployment
      • Cloud
      • On-premises
  • Services
    • Consulting
    • Deployment & integration
    • Training, support and maintenance

Market, By Application

  • Personal Assistance
  • Smart Home Devices
  • Gaming
  • Autonomous Vehicles
  • Fraud Detection Systems
  • Wearable Technology
  • Language Learning Apps
  • Travel Planning and Booking
  • Health Monitoring Devices
  • Music and Video Streaming
  • Smart Grid Management
  • Navigation Systems
  • Others

Market, By End-user industry

  • Consumer electronics
  • Healthcare
  • Retail and e-commerce
  • Media and entertainment
  • Automotive
  • BFSI
  • Education
  • Travel and hospitality
  • Utilities and energy
  • Others
Tables, Charts & Figures 305
Segments covered Offering, Application, End- user industry, Region
Growth Drivers
  • Advancements in machine learning algorithms
  • Increased adoption of AI technologies
  • Growing demand for personalized experiences
  • Expansion of IoT-connected devices
  • Rise in data availability and analytics
Pitfalls & Challenges
  • Data privacy and security concerns
  • High implementation and maintenance costs

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Explainable AI Market about to hit USD 51.29 billion by 2035

Explainable AI Market Size and Forecast 2024 to 2034

Explainable AI Market size was estimated at USD 7.85 billion in 2024 and is anticipated to grow at a CAGR of more than 15.67% from 2025 to 2035.

The explainable AI market is likely to evolve significantly, in part because of ethical and regulatory reasons. Governments and regulatory bodies all over the world are increasingly concerned with the potential risks that AI systems could pose such as bias, discrimination, and the absence of accountability. They are implementing regulations mandating AI models to be transparent and explainable to mitigate these risks.

Report Attribute Details
Base Year 2024
Explainable AI Market Size in 2024 USD 7.85 Billion
Forecast Period 2024 – 2035
Forecast Period 2024 – 2032 CAGR 15.67%
2035 Value Projection USD 51.29 Billion
Historical Data for 2021 – 2023
No. of Pages 450
Tables, Charts & Figures 350
Segments covered Component, Software Type, Method, Industry Vertical
Growth Drivers
  • Regulatory compliance and ethical requirements
  • Enhancing model performance and debugging
  • Customer and market demand
  • Growing importance of accountability
  • International collaboration and standards development
Pitfalls & Challenges
  • Complexity and trade-offs
  • Standardization and best practices

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Explainable AI Market Trends

One of the key trends driving the market is the application of explainable AI in core business processes. Companies in various industries are recognizing the value of transparency in AI to convince stakeholders and customers. Companies can provide understandable insights into their decision-making by incorporating explainable AI into their business.

Explainable AI is applied; for example, in financial institutions to inform credit decisions and detect fraud, and in healthcare to explain proposed diagnoses & treatments. This trend not only supports regulatory compliance but also enhances client satisfaction and trust. For this reason, to enhance business operations and maintain competitiveness, more businesses are making explainable AI a priority.
The market for explainable AI is growing because of significant advances in explainability methods. In order to deliver more sophisticated and real-world techniques for interpreting complex AI models, developers and researchers are always seeking new concepts. Approaches like SHapley Additive exPlanations (SHAP), Local Interpretable Model-agnostic Explanations (LIME), and attention mechanisms are being refined and employed more.

Users will be able to better understand and believe in AI systems due to these advancements, which enable more precise & transparent explanations of its decision-making. The adoption of explainable AI solutions is also driven by the development of model-agnostic interpretability methods, which make it possible to apply them to a range of different types of AI models.

Explainable AI Market Analysis
Discover more about the major segments defining this market

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On the basis of software type, the market is segmented into model-agnostic approaches and model-specific approaches. The model-agnostic approaches segment is anticipated to exhibit a CAGR of 19.1% over the forecast period.

Model-agnostic techniques offer a flexible and versatile method for assessing and understanding the output of various AI models, hence a crucial resource in the field of explainable AI. Compared to model-specific techniques, which are tailored to work with a particular type of algorithm (e.g., neural networks/decision trees), model-agnostic techniques can be applied to any AI model, no matter its design.
Their substantial utility across diverse application scenarios is based on their universality. LIME and SHAP are two popular model-agnostic approaches. To build interpretable models that locally behave similarly to the black-box model, LIME initially disturbs the input data and subsequently observes changes in the output.
On the other hand, SHAP offers a single measure of feature importance through the application of concepts from cooperative game theory to attribute the model’s output to its input features. These methods enable users to gain insights into the decision-making of complex models, identify biases, and effectively analyze model outputs.

They are particularly useful for companies that need transparency and accountability for a variety of AI applications. Model-agnostic methods are gaining popularity in the explainable AI market due to their flexibility and broad spectrum of applications, addressing the needs of various businesses, looking for reliable and understandable AI solutions.

Market Dynamics
Drivers
Increasing human and artificial intelligence collaborative activities

Human and AI collaboration is needed to fulfill compliance and regulatory demands. Explainable AI allows companies to present justifications and proof for the choices taken by AI programs, allowing transparency and fulfillment of regulation compliance. Human collaboration within AI choice interpretation and explanation serves to satisfy legal compliance and regulatory needs. Human-AI collaboration enables continuous learning and evolution. Human professionals can impart their experience and skills to AI systems, allowing them to learn based on human inputs and evolve to respond to changing situations. The process of collaborative learning enhances the performance of the AI system as time passes. In general, the human-AI collaboration enhances the expansion of the explainable AI market through mutual strengths.

Restraints
Performance limitations

In competitive markets, organizations might value the performance of AI models over interpretability. If black-box models always perform better than explainable AI models, companies might be reluctant to implement explainable AI solutions because they fear losing a competitive advantage. There is usually a compromise between model interpretability and performance. As models get more interpretable, they tend to simplify or leave out some of the complicated relationships in the data, potentially reducing performance. Overcoming such performance constraints needs continuous research and development work in the area of explainable AI.

Opportunities
Increasing education and awareness regarding AI

Education and awareness regarding AI open up opportunities for the explainable AI market by building understanding, dispelling concerns, encouraging regulatory compliance, closing the gap between technical and non-technical stakeholders, empowering users, and stimulating research and innovation in the area of explainable AI. Education and awareness programs can motivate researchers, developers, and innovators to investigate and develop the area of explainable AI. By emphasizing the value and possible use of explainability, these projects can draw people, capital, and resources toward creating new techniques and solutions. This establishes a virtuous feedback loop, whereby more research and innovation fuel yet more growth in the explainable AI market.

Component Insights
The solution segment led the market in 2023, the segment is forecast to continue to experience a visible growth throughout the forecast period. The segment is growing due to the rising use of AI technologies across various industries. The major portion where the explainable AI operates is fraud detection. Explainable AI identifies fraud and develops thoughtful solutions for it. Cybercrime is one of the biggest problems for the government and private organizations as well, and in the technology age, it has been a challenge.

Explainable AI Market Companies

Amelia US LLC
BuildGroup
DataRobot, Inc.
Ditto.ai
DarwinAI
Factmata
Google LLC
IBM Corporation
Kyndi
Microsoft Corporation

Recent Development
In June 2023, Reprocell announced the launch of advanced commercial services ‘Pharmacology-AI’. The launch of new services was followed by the completion of the first excellerate project by the National Center for Digital Innovation.
IBM has announced the introduction of a new platform for companies ‘IBM Watsonx’ in June 2023. IBM’s new platform introduced enables organizations to speed up operations with artificial intelligence solutions. In May 2023, the Singaporean government partnered with Google Cloud, to make it easier for artificial intelligence to be available to city-state public sector agencies through the new AI cloud platform.
In May 2023, Singapore government declared collaboration with Google Cloud. The collaboration will ensure availability of artificial intelligence platforms for public sector agencies through AI cloud platforms.

Segments Included in the Report:

By Component

Solution
Services

By Deployment

Cloud
On-premises

By Application

Fraud and Anomaly Detection
Drug Discovery & Diagnostics
Predictive Maintenance
Supply Chain Management
Identity and Access Management
Others

By End-use

Healthcare
BFSI
Aerospace & Defense
Retail and e-commerce
Public Sector & Utilities
IT & Telecommunication
Automotive
Others

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Cybersecurity Technology

AI in Industrial Machinery Market: Global Industry Analysis and Forecast (2025-2035)

Global AI in Industrial Machinery Market size was valued at USD 6.56 Billion in 2024 and the total AI in Industrial Machinery Market revenue is expected to grow at a CAGR of 27.34 % from 2023 to 2035, reaching nearly USD 34.34 Billion.

AI in Industrial Machinery Market Overview

AI in Industrial Machinery Market refers to applying AI technologies and algorithms in industrial machinery and equipment manufacturing design and operation. The aim is to enhance automation, streamline processes, to drive AI in Industrial Machinery Market Growth. The success of incorporating AI features such as machine learning, computer vision, and predictive analytics into industrial systems. AI is a significant force for disruption and an instrument to attain industrial manufacturing competitive advantage. Those manufacturing firms that fail to understand the significance of AI will likely lose their competitiveness. The primary motivations for applying AI technologies in industrial Machinery settings are fueled by the desire to help make decisions or act, automate repetitive and Reduce cost and enhance reliability, and decision-making through revolutionizing AI in industrial Machinery market.

AI in Industrial Machinery

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Growing demand for Industrial Machinery to increase the market growth

AI in Industrial Machinery Market has been Increasing the demand and development in manufacturing over the past few years, making factories less labor-intensive and more efficient than ever before. The entry of AI in Industrial Machinery Market is a breakthrough for the machinery and manufacturing industry. Industrial machinery is completely reliant on programming to take own decisions based on AI-based information. The uses of AI in Industrial Machinery Market are various ranging from sophisticated forecasts to quality control and waste minimization. AI in Industrial Machinery is applied for planning, scheduling, optimization, robotics, and machine vision. Additionally, AI gives manufacturers more capacity and space to grow the business, but it also offers us a prospect for a greener and more convenient AI in Industrial Machinery Future. The AI in Industrial Machinery manufacturing sector has always been on hand to adopt new-age technologies. Drones have been a part of the Industrial Machinery Market along with industrial robots. The next automation revolution is on the way with the adoption of AI if businesses are able to maintain lean inventories and cut the cost, there is a strong likelihood that the manufacturing sector will be facing an en-abling evolution. The application of AI in the industrial machinery sector is phenomenal.

AI in Industrial Machinery Market robot collaboration allows manufacturers to provide generative products quicker. AI in Industrial Machinery Market revolutionizing how manufacturers create products. The AI solution for industrial machinery provides insights into optimal design. AI provides advantages to manufacturing businesses. These elements are propelling the market growth in the forecast period. For example, BMW employs AI in product quality, General Motors employs AI in intelligent maintenance, and Nissan employs AI in manufacturing for designing Ultra- Modern vehicles. And numerous biggest brands are employing AI in manufacturing operations.

AI in Industrial Machinery Market Trends

AI Development and Future Trends in Industrial Machinery Market

AI in Industrial Machinery Market is anticipating huge growth fueled by market trends and prospects. AI has become highly entrenched in industrial and other applications, with early applications utilizing AI in industrial machinery and portraying their uses, and widening the primary production. Industrial machinery is evolving together with society, and digitalization is fast pushing market growth. AI technologies combined with IoT devices form a strong alliance called AIoT. AI in the industrial machinery industry has been an increasing demand for robots. AI in Industrial Machinery Market has continued to improve computer visualization and has been utilized for years for quality control by identifying product defects in real-time. But with manufacturing now using more information than ever combined with the fact that plant managers don’t want to compensate workers for inputting information AI with computer vision can make sense of how information is captured. Knowledge work is being automated within the AI in the Industrial Machinery market revolution; through creating new ways of automating manufacturing jobs, are creating the way people and machines live, work, and interact to build a stronger digital economy. The AspenTech, Industrial AI Research discovered that 83% of large industrial companies believe AI creates better results, but only 20% have utilized it. There won’t be extensive use of artificial intelligence in the industrial sector unless a major investment is made in gaining domain knowledge. Both of them constitute what is called AI in Industrial Machinery Market that is the use of machine learning technologies to normally non-academic environments.

AI is automating Factories

Robotics coupled with AI can disburden you from very specialized tasks. AI in Industrial Machinery Market is applying intelligent technology to reduce cost of production, safeguard human workers, and maximize efficiency. AI in Industrial Machinery Market can very well cut costs on labor and enhance productivity and efficiency at their factories. The other applications are among the several applications. The finest example of factory automation is Siemens. The firm has tied up with Google to enhance shop floor productivity with the help of computer vision, cloud-based analytics, and artificial intelligence algorithms.

AI for Quality Inspection

Quality control in the industrial machinery segment is where AI is most urgently required. Industrial robots, too, can go wrong, even though this is far less frequently than a human. Having substandard products roll off the assembly shipped to the consumer can cost dearly. Machine learning (ML) and artificial intelligence (AI) merge human minds with advanced technologies to create revolution in manufacturing operations. AI Industrial Machinery Market is able to find small defects in industrial machinery or products that cannot be found by robots. Products are scanned by AI software to identify defects automatically through hardware like cameras and Internet of Things sensors. The computer makes decisions about what to do with faulty products automatically. Producers maintain quality products with a shorter production time by carrying out rigorous quality testing with Ai in the industrial machinery industry.

AI assists in accelerating sustainable development goals in the industrial machinery industry

The Industrial Machinery Market for AI employs AI to save GHG emissions between 2.6 and 5.3 gigatonnes of CO2 and generate USD 1.3 trillion to USD 26 trillion in value through incremental revenues and cost savings. Businesses will employ AI and analytics to track their own carbon footprint and discover methods for lowering carbon emissions. Such as reading waste, i.e., decreasing plastic pollution in the sea, and creating environmentally friendly products and production techniques. AI applied to industrial equipment can utilize AI and Analytics to make workers safe due to improved technology in the industrial equipment market

by Components Hardware Software Services
by Application Cybersecurity Energy management HMI Maintenance Motion planning Safety Quality control
by EndUser Banking Government Healthcare Manufacturing Retail Professional services

AI in Industrial Machinery Market, by Region

North America (United States, Canada and Mexico) Europe (UK, France, Germany, Italy, Spain, Sweden, Austria, Turkey, Russia and Rest of Europe) Asia Pacific (China, India, Japan, South Korea, Australia, ASEAN and Rest of APAC) Middle East and Africa (South Africa, GCC, Egypt, Nigeria and Rest of ME&A) South America (Brazil, Argentina, Columbia and Rest of South America)

AI in Industrial Machinery Market Players

The industrial machinery market consists of leading industrial technology companies. These players are concentrating on using AI-based solutions in machinery to enable predictive maintenance, real-time analytics, and automation. Strategy includes increasing the product line equipped with AI and strategic partnerships to enhance innovation as well as drive operational efficiency by acquiring technology startup companies.

1. General Electric Company
2. ABB Ltd.
3. Mitsubishi Electric Corporation
4. Schneider Electric SE
5. Honeywell International Inc.
6. Rockwell Automation, Inc.
7. Fanuc Corporation
8. IBM Corporation
9. Microsoft Corporation
10. Intel Corporation
11. Rockwell Automation
12. GE
13. Mythic
14. VIDIA
15. Uptake
16. Veo Robotics
17. Automation Anywhere
18. Machina Labs, Inc.
19. Bosch Rexroth AG
20. Yaskawa Electric Corporation
21. KUKA AG
22. FANUC Corporation
23. Omron Corporation
24. Cognex Corporation
25. Intel Corporation
26. NVIDIA Corporation
27. Google LLC
28. Amazon Web Services, Inc.

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Generative AI in Logistics Market – By Type (Variational Autoencoder (VAE), Generative Adversarial Networks (GANs), Recurrent Neural Networks (RNNs), Long Short-term Memory (LSTM) Networks), By Component, By Deployment Model, By Application, By End User Forecast 2025 – 2035

Generative AI in Logistics Market size was USD 969.89 million in 2024 and is expected to record a CAGR of more than 35.67% from 2025 to 2035.

Generative AI optimizes supply chains by forecasting demand, detecting potential disruptions, and proposing alternative routes or solutions, improving efficiency and lowering costs.

AI-driven automation in warehouse management, including inventory tracking, space utilization, and predictive maintenance, streamlines operations and improves accuracy. Generative AI algorithms enable more efficient route planning and optimization, reducing delivery times and fuel consumption by analyzing traffic patterns, weather conditions, and other variables.

Generative AI in Logistics Market Report Attributes

Report Attribute Details
Base Year 2024
Generative AI in Logistics Market Size in 2024 USD 969.44  Million
Forecast Period 2024-2032
Forecast Period 2024-2032 CAGR 33.2%
2035 Value Projection USD 12.45 Billion
Historical Data for 2021-2023
No. of Pages 270
Tables, Charts & Figures 350
Segments covered Type, Component, Deployment Model, Application, End User
Growth Drivers
  • Supply chain and route planning optimization
  • Increased demand for warehouse management
  • Accuracy in demand forecasting
  • Achieving cost efficiency
Pitfalls & Challenges
  • Data quality and availability
  • Complexity in integration

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Generative AI in Logistics Market Trends

The logistics industry’s generative AI is experiencing a significant trend in the form of new-age solution providers emerging within the industry. These new ventures are transforming the dynamics of generative AI within the logistics space by utilizing strategic partnerships with larger players to deliver innovative and bespoke solutions. The demand is more accurately predicted through the use of generative AI. Through the examination of huge datasets, AI models can predict demand patterns, which helps logistics firms to make optimal use of inventory management and minimize both overstock and stockouts.

Generative AI is revolutionizing route optimization through the analysis of real-time data on traffic, weather, and delivery timetables. This enables logistics providers to select the most efficient routes, which leads to fuel efficiency and quicker deliveries. Warehouse automation through AI is on the rise, with generative AI facilitating more advanced robotic functions. This encompasses activities, including sorting, packing, and even handling returns, to improve operational efficiency and lower labor expenses. Generative AI is being used to provide more customized services to customers. This encompasses offering real-time tracking details, customized delivery choices, and proactive updates on shipment status, thus enhancing customer satisfaction.

For example, in February 2024, container ship player Maersk tried generative AI models for its demand forecasting in an effort to improve the precision of predictions and allow capacity planning.

Generative AI in Logistics Market Share

Google Cloud and IBM are the leaders of the generative AI in logistics market, with market share of more than 15%. Google Cloud’s ML and AI technologies, such as TensorFlow and AutoML, enable logistics firms to create advanced generative AI models. Its cloud platform offers scalability and flexibility, allowing real-time data processing and analysis for optimizing logistics. Google’s data analytics and AI-powered insights enable logistics firms to enhance supply-chain visibility, demand forecasting, and route optimization.

IBM’s AI products, including Watson AI and IBM Cloud Pak for Data, include sophisticated generative AI features suited for the logistics sector. Its AI-based solutions support predictive analysis, anomaly identification, and informed decision-making for logistics operations. IBM’s proficiency in hybrid cloud and edge computing supports the implementation of AI within distributed logistics networks with low latency and data confidentiality.

Generative AI in Logistics Market Company

Key companies in the generative AI in logistics market include

Blue Yonder
C. H. Robinson
FedEx Corp
Google Cloud
International Business Machines (IBM)
Microsoft
PackageX
Salesforce

The generative AI in logistics market research report includes in-depth coverage of the industry with estimates & forecasts in terms of revenue (USD Billion) from 2025 to 2035, for the following segments

Market, By Type

  • Variational Autoencoder (VAE)
  • Generative Adversarial Networks (GANs)
  • Recurrent Neural Networks (RNNs)
  • Long Short-Term Memory (LSTM) networks
  • Others

Market, By Component

  • Software
  • Services

Market, By Deployment Mode

  • Cloud
  • On-premises

Market, By Application

  • Route optimization
    • Variational Autoencoder (VAE)
    • Generative Adversarial Networks (GANs)
    • Recurrent Neural Networks (RNNs)
    • Long Short-Term Memory (LSTM) networks
    • Others
  • Demand forecasting
    • Variational Autoencoder (VAE)
    • Generative Adversarial Networks (GANs)
    • Recurrent Neural Networks (RNNs)
    • Long Short-Term Memory (LSTM) networks
    • Others
  • Warehouse and inventory management
    • Variational Autoencoder (VAE)
    • Generative Adversarial Networks (GANs)
    • Recurrent Neural Networks (RNNs)
    • Long Short-Term Memory (LSTM) networks
    • Others
  • Supply chain automation
    • Variational Autoencoder (VAE)
    • Generative Adversarial Networks (GANs)
    • Recurrent Neural Networks (RNNs)
    • Long Short-Term Memory (LSTM) networks
    • Others
  • Predictive maintenance
    • Variational Autoencoder (VAE)
    • Generative Adversarial Networks (GANs)
    • Recurrent Neural Networks (RNNs)
    • Long Short-Term Memory (LSTM) networks
    • Others
  • Risk management
    • Variational Autoencoder (VAE)
    • Generative Adversarial Networks (GANs)
    • Recurrent Neural Networks (RNNs)
    • Long Short-Term Memory (LSTM) networks
    • Others
  • Customized logistics solutions
    • Variational Autoencoder (VAE)
    • Generative Adversarial Networks (GANs)
    • Recurrent Neural Networks (RNNs)
    • Long Short-Term Memory (LSTM) networks
    • Others
  • Others
    • Variational Autoencoder (VAE)
    • Generative Adversarial Networks (GANs)
    • Recurrent Neural Networks (RNNs)
    • Long Short-Term Memory (LSTM) networks
    • Others

Market, By End User

  • Road transportation
  • Railway transportation
  • Aviation
  • Shipping, and ports

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Market Dynamics

Driver
Requirement for precise anticipation and supply planning

With the abilities of generative AI, organizations can make use of up-to-date facts in their planning processes. In turn, machine learning-based methods of demand forecast have much fewer error rates in comparison to historic forecasting methods. Companies can allocate trucks to bordering warehouses in a better manner and reduce working expenses by upgrading their workforce plan. Customers are less likely to suffer from stockouts that decrease customer satisfaction if local warehouses and retailers can minimize holding costs. Real-time analysis of demand is made possible by generative artificial intelligence, which allows companies to dynamically change their supply planning parameters and improve the effectiveness of supply chains. Waste reduction is brought about by dynamic supply planning, which means companies consume fewer resources.

Conversely, the world logistics and supply chain industry is facing a significant transformation due to rampant online businesses and online shopping. Given the predictive and supply planning capabilities of generative AI, the industry tends to embrace such sophisticated generative solutions by spearheading the market growth.

Restraint
Lack of visibility

Even though there are numerous advantages of the usage of generative AI in the logistics industry. There are a few the demerits to the generative AI in the logistics industry such as absence of visibility between producer and consumer. Generative AI provides solutions to consumers directly without any human touch, this could lead to visibility problems for the customers. Shortage of transparency and lack of communication between the two parties are most likely to hinder the growth of the market.

Opportunity
Increased emphasis on marketing and sales analytics approaches

Generative AI solutions can deliver more precise sales and marketing figures. Logistics service providers can analyze client behavior and apply predictive analytics to better predict what their customers will do next using AI-enabled solutions. AI-powered solutions can be utilized to track market trends, providing logistics service providers with a competitive edge and the capacity to make informed decisions that will enhance efficiency. Consequently, market opportunities were established based on sales and marketing analytics. This aspect is seen to create several opportunities for the market to expand.

Deployment Mode Insights
The segment which is cloud-based is anticipated to develop at a high growth rate throughout the forecast period. The reasons behind the growth of the segment lie in the advantages of cloud technology for logistics and how it can make operations more efficient. The heavy demand for storage of data by logistics companies in order to handle and analyze operations serves as a driving factor for the segment.