AI Research

Generative AI Research Report 2025-2030

Published

7 days ago

September 4, 2025

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Generative AI, which creates original content using advanced algorithms like neural networks, is transforming industries such as art, healthcare, and finance. Key growth drivers include the rise of VR/AR technologies, deployment of large language models (LLMs), and demand for personalized content. Services in generative AI are gaining traction for scalability and cost-effectiveness. North America leads the market, while Asia Pacific emerges as the fastest-growing region, driven by investments in AI innovation. Challenges include combating deepfakes and misinformation, while trends like AI integration with robotics and democratization of AI platforms drive sector expansion. Key players, including Amazon, Microsoft, and OpenAI, are enhancing their competitive edge through strategic acquisitions and collaborations.

Dublin, Sept. 04, 2025 (GLOBE NEWSWIRE) — The “Generative AI Market: Analysis by Component, Technology, End User, and Region – Size, Trends and Forecasts to 2030” report has been added to ResearchAndMarkets.com’s offering.

The global generative AI market in 2024 was valued at US$20.21 billion. The market is expected to grow at a CAGR of approx. 37% during the forecasted period of 2025-2030.

Generative AI finds applications in various fields, including art, design, content creation, drug discovery, and natural language processing, where its ability to generate novel and diverse outputs contributes to innovation and problem-solving.

The global generative AI market is highly fragmented, characterized by the presence of numerous small and medium-sized companies competing for market share, and the presence of a substantial number of regional market players with limited business offerings and customer base.

The continuous growth of the global generative AI market can be attributed to several key factors. Firstly, the proliferation of virtual and augmented reality (VR/AR) technologies has propelled the demand for generative AI. These technologies rely heavily on realistic and immersive content, driving the need for advanced AI models capable of generating life-like visuals and interactive experiences.

Deployment of Large Language Models (LLMs) has emerged as another crucial driver. LLMs, such as GPT-3, have revolutionized natural language processing tasks, enabling the generation of human-like text, translation, and summarization. This adoption fuels the demand for generative AI solutions tailored to language-related applications. Moreover, the rising demand for creative and personalized content across various industries, including marketing, entertainment, and e-commerce, acts as a significant growth driver.

Furthermore, the healthcare and life sciences sectors are increasingly leveraging generative AI for various applications, such as drug discovery, medical imaging analysis, and patient data synthesis. These advancements contribute to improved diagnosis, treatment, and healthcare outcomes. Advancements in deep learning and neural networks play a fundamental role in driving generative AI market growth. Overall, the convergence of these factors fosters a conducive environment for the expansion of the generative AI market, facilitating innovation, and driving adoption across industries, and unlocking new opportunities for growth and development.

North America emerges as the largest region in the generative AI market, showcasing a promising landscape shaped by countries like the US, Canada, and Mexico, each with distinctive elements influencing their generative AI sector. Industry giants like OpenAI, Google, and Microsoft have significantly contributed to the region’s market, driving substantial investments in research and development to push the boundaries of AI capabilities. Both venture capital firms and tech giants are injecting billions into generative AI technology development, fostering innovation and market expansion.

This influx of capital has led to the creation of cutting-edge AI platforms, widely adopted across industries such as healthcare, finance, and entertainment. Moreover, the presence of leading market players and technology organizations, alongside a pool of experts, is anticipated to propel regional market growth, with the US expected to exhibit the fastest CAGR, fueled by increased adoption of deep learning and machine learning across diverse industries, including SMEs.

On the other hand, Asia Pacific emerges as the fastest-growing region in the generative AI sector, driven by a significant surge in AI technology adoption across various industries. With countries like China, Japan, India, and South Korea leading AI innovation, the region spearheads progress in generative AI technologies. The availability of vast data sets, particularly in language processing and computer vision, is crucial for training and improving GenAI models, with Asia Pacific’s large and diverse population providing a rich data source.

China dominates the industry, backed by significant investments in AI research, infrastructure, and talent development, with tech giants Alibaba, Tencent, and Baidu leading innovation across various sectors. Japan, renowned for technological prowess, hosts leading AI research institutions and companies, while India’s GenAI market is poised for significant growth, driven by skill development, research advancements, and government support initiatives. For instance, In July 2023, Singapore’s digital government agencies partnered with Google Cloud to develop GenAI capabilities in the public and private sectors.

Market Segmentation Analysis:

By Component: The report provides bifurcation of the global generative AI market into two segments namely, Software and Services.

Software Generative AI currently dominates the market as it encompasses a range of AI software tools, platforms, and applications tailored for generating content such as images, text, and music. These software solutions enable businesses to streamline processes, enhance creativity, and drive innovation. On the other hand, Services Generative AI is poised for rapid growth as businesses increasingly seek specialized assistance in implementing and leveraging generative AI technologies effectively.

Cloud-based generative AI services are expected to gain popularity as they provide scalability, flexibility, and cost-effectiveness, fueling the segment’s growth. For instance, in December 2023, Mistral AI, an artificial intelligence solutions provider, partnered with Google Cloud, optimized proprietary language models, and distributed both its open weights on Google Cloud’s AI-optimized infrastructure. As the demand for generative AI continues to rise, the services segment is expected to expand significantly to meet the growing need for expertise and support in this field.

By Technology: The report provides bifurcation of the global generative AI market into four segments namely, Transformer, Generative Adversarial Networks, Variational Auto-encoder, and Diffusion Networks.

The Transformer segment currently dominates the market due to its versatility and widespread adoption across various applications. Transformers, based on attention mechanisms, excel in tasks such as natural language processing, image recognition, and sequence generation. Their ability to capture long-range dependencies and model complex relationships has made them indispensable in numerous industries, including healthcare, finance, and entertainment.

Conversely, the Diffusion Networks segment is anticipated to experience fastest growth owing to its ability to generate high-quality images and text samples. Diffusion networks employ a diffusion process to generate outputs that closely match the distribution of training data, enabling the creation of realistic and diverse content. This capability makes them increasingly sought after in applications such as image synthesis, text generation, and creative content production, thus driving the growth in the forecasted period.

By End User: The report provides the bifurcation of the global generative AI market into six segments based on end-user, namely, Media & Entertainment, IT & Telecommunication, Healthcare, BFSI, Automotive & Transportation, and Others.

The Media & Entertainment segment held the highest share in the market and BFSI is expected to be the fastest-growing segment in the forecasted period. Generative AI in Media & Entertainment drives content creation, production, and enhancement, meeting the demand for immersive experiences and personalized storytelling. This technology’s adoption is fueled by the sector’s quest for high-quality content and engaging experiences to remain competitive amid evolving consumer preferences.

Conversely, the BFSI sector is embracing generative AI rapidly due to digital transformation initiatives and increasing demands for fraud detection, risk management, personalized customer experiences, and regulatory compliance. With countries like the UK, Spain, and Italy leading AI innovation, BFSI organizations are leveraging generative AI’s advanced capabilities in data analysis and automation to enhance operational efficiency and deliver tailored services. As the BFSI sector prioritizes digital transformation to address complex challenges, the adoption of generative AI is expected to soar in the coming years.

Competitive Landscape

Some of the strategies among key players in the market are new launch, mergers, acquisitions, and collaborations. For instance, on May 21, 2025, OpenAI announced the acquisition of io, an AI-hardware startup founded by Jony Ive, for US$6.5?billion, marking its largest acquisition to date and signaling a move toward integrated AI hardware-software solutions. Similarly, on May 19, 2025, Microsoft announced about amplifying its Azure AI ecosystem with new coding agents and partnerships (OpenAI, Nvidia, Elon Musk’s xAI), aiming to generate over US$13 billion in annual AI revenue.

Market Dynamics

Growth Drivers

Expansion of Virtual and Augmented Reality
Deployment Of LLM
Increasing Demand for Creative and Personalized Content
Enhanced Computing Power and Increased Availability of Data
Growing Applications in Healthcare and Life Sciences
Advancements in Deep Learning and Neural Networks

Challenges

Market Trends

Integration of Generative AI with Robotics and Automation
Democratization of AI Tools and Platforms
Growing Integration With Cloud Computing
Generative AI For Scientific Research
Continued Innovation in Generative Adversarial Networks
Emphasis on Explainable AI and Interpretability
Automation and Efficiency in Enterprise Workloads
Focus on Ethical AI
Chatbot-powered Customer Service

Key Players in the Global Generative AI Market: Business Overview, Operating Segments, Business Strategy

Amazon.Com, Inc. (Amazon Web Services, Inc.)
Microsoft Corp.
Alphabet Inc.
IBM
Salesforce, Inc.
Nvidia Corporation
Accenture
Cognizant Technology Solutions Corporation
Capgemini
Adobe Inc.
Infosys
SAP SE
Synthesis AI
D-ID
OpenAI Inc.

For more information about this report visit https://www.researchandmarkets.com/r/nhnb78

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Companies Bet Customer Service AI Pays

Published

48 minutes ago

September 11, 2025

PYMNTS

Klarna’s $15 billion IPO was more than a financial milestone. It spotlighted how the Swedish buy-now-pay-later (BNPL) firm is grappling with artificial intelligence (AI) at the heart of its operations.

Back in 2023, Chief Executive Sebastian Siemiatkowski suggested AI could replace large parts of the company’s customer-service workforce. The remarks sparked pushback from employees and skepticism from customers, many of whom doubted whether the technology was advanced enough to provide empathy and reliability at scale.

Pivoting and Learning

Klarna’s first wave of AI adoption proved too rigid, with customers finding the experience inconsistent. The company now pivoted toward a blended approach: AI for speed and scale, humans for empathy and trust. That adjustment echoes a lesson resonating across industries. AI works best when it augments, rather than replaces, human agents.

The company’s focus on human-powered customer support shows how the firm is hiring again to ensure customers always have the option of speaking to a person. “From a brand perspective, a company perspective, I just think it’s so critical that you are clear to your customer that there will be always a human if you want,” Siemiatkowski told Bloomberg News, as reported by PYMNTS.

As Vinod Muthukrishnan, vice president and chief operating officer of Webex Customer Experience Solutions at Cisco, explained, many financial institutions are moving past pilots and into deployment.

“These firms are increasingly leveraging their AI focus on hyper-personalized CX [customer experience] such as personal financial advice or dynamic credit limit adjustments and offers, all enabled via real-time analytics,” he told PYMNTS. Retailers and service providers face similar opportunities, provided they align strategy with measurable ROI.

Five Areas for AI, Customer Care

1. Proactive Issue Resolution

AI can anticipate problems before customers complain. Declined payments, unexpected fees or delivery delays can be flagged and addressed in real time, turning frustration into loyalty. Most firms still operate reactively, in part because data remains siloed across payments, logistics and support and closing these gaps could sharply reduce call volumes.

2. Hyper-Personalized Support

Consumers now expect service that reflects their history and preferences. AI can tailor repayment options, loyalty incentives, or offers based on real-time data. Walmart, for example, has deployed AI-powered personalization tools to refine its app and eCommerce experience. Predictive analytics can also flag anomalies that suggest fraud or disputes, thereby reducing chargebacks. Yet many retailers still rely on generic scripts.

3. Multilingual, 24/7 Coverage

Global commerce does not keep office hours. AI chatbots and voice systems provide round-the-clock, multilingual support. New multimodal systems can handle voice, text, and even images, creating richer customer interactions. PYMNTS has reported that customers value this always-on flexibility, but many firms still lean on nine-to-five call centers or outsourced night shifts.

4. Sentiment Detection and Emotional Intelligence

Speed matters, but empathy builds loyalty. AI can read tone and phrasing in real time, alerting human agents when a customer is upset. This hybrid model ensures efficiency without sacrificing trust. Rezolve’s Brain Suite applies empathy-driven AI to reduce cart abandonment, which accounts for nearly 70% of lost online sales. Yet sentiment detection remains rare in many call centers.

5. Insights Beyond the Call Center

Complaints can expose flaws in checkout flows, packaging or design. AI can analyze these patterns, turning customer service into a source of business intelligence. Google’s Vision Match tools, for example, feed insights from shopping behavior back into product strategy. Few enterprises close this loop.

ROI as the Deciding Factor

For executives, ROI is the real test. Projects that fail to deliver lower handle times, better satisfaction scores, or reduced churn rarely scale. “AI as with any new technology risks adoption and integration without a clear strategic alignment,” Muthukrishnan warned. “Too many pilots or implementations can lead to a fragmented focus.”

“We’re already in market with our AI agent for autonomous and scripted self-service,” Todd Fisher, CEO and co-founder of CallTrackingMetrics, told PYMNTS.

“In a recent survey, 72% of respondents rated Webex AI Agent as equal, if not better, than a human agent. And our customers have reported an 85% reduction in agent call escalations, a 22% reduction in average handle time, and a 39% increase in CSAT [customer satisfaction] scores.”

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AI Research

Artificial intelligence (AI)-powered anti-ship missile with double the range

Published

1 hour ago

September 11, 2025

John Keller

Questions and answers:

What is the primary feature of the LRASM C-3 missile compared to earlier variants? It has nearly double the range of previous versions, with a range of about 1,000 miles, compared to 200 to 300 miles for the C-1 and 580 miles for the C-2.
How does artificial intelligence enhance the LRASM C-3’s capabilities? AI helps the missile with autonomous mission planning, target discrimination, and attack coordination, adjust flight paths based on real-time data, identify and track moving targets, and adapt to changing conditions like jamming and interference.
What can launch the LRASM C-3 missile? U.S. Air Force B-1B bombers, Navy F/A-18E/F Super Hornets, and F-35 Lightning II jets, with possible future launches from Navy ships and attack submarines.

PATUXENT RIVER NAS, Md. – U.S. Navy surface warfare experts are asking Lockheed Martin Corp. to move forward with developing the new LRASM C-3 anti-ship missile with double the range of previous versions.

Officials of the Naval Air Systems Command at Patuxent River Naval Air Station, Md., announced a $48.1 million order last month to the Lockheed Martin Missiles and Fire Control segment in Orlando, Fla., for engineering to establish the Long Range Anti-Ship Missile (LRASM) C-3 variant.

The subsonic LRASM is for attacking high-priority enemy surface warships like aircraft carriers, troop transport ships, and guided-missile cruisers from Navy, U.S. Air Force, and allied aircraft.

LRASM is designed to detect and destroy high-priority targets within groups of ships from extended ranges in electronic warfare jamming environments. It is a precision-guided, standoff anti-ship missile based on the Lockheed Martin Joint Air-to-Surface Standoff Missile-Extended Range (JASSM-ER).

1,000-mile range

The LRASM C-3 variant has a range of nearly 1,000 miles, compared to the 200-to-300-mile C-1 variant, and 580-mile range of the LRASM C-2 variant.

LRASM C-3 also introduces machine learning and advanced artificial intelligence (AI) algorithms to enhance autonomous mission planning, target discrimination, and attack coordination, even amid intense electronic warfare (EW) jamming.

The C-3 also can exchange information from military satellites, and has an enhanced imaging infrared and RF seeker for survivability and target identification.

The C-3 also can be launched form the Air Force from B-1B strategic jet bomber, as well as the Navy F/A-18E/F Super Hornet jet fighter-bomber and the F-35 Lightning II attack jet. Navy leaders also envision using the Navy MK 41 shipboard vertical launch system with the LRASM C-3, and are considering options to launch the missile from attack submarines.

Tell me more about applying artificial intelligence to missile guidance …

Applying artificial intelligence to missile guidance will enhance precision, adapt to dynamic environments, and improve decision-making in real-time. AI can help missiles navigate autonomously by using real-time data from radar, infrared sensors, and GPS to adjust flight paths. AI also can help missiles visually identify targets from images or video feeds, and not only enhance the missile’s ability to recognize and track moving targets, but also to predict and follow moving targets even if they change direction or speed. Using AI, missile guidance systems can make real-time adjustments to their trajectory based on changing conditions like wind, RF interference, and jamming. Missiles also may use AI to other weapons in swarm tactics, and operate effectively against countermeasures.

Helping to extend the LRASM C-3’s range are an advanced multi-mode sensor suite; enhanced data exchange and communications; digital anti-jam GPS and navigation; and AI and machine learning capabilities.

The missile’s multi-mode sensor suite is expected to blend imaging infrared and RF sensors to help the weapon identify and attack targets. Its communications will have data links for secure real-time communication with satellites, drones, and strike aircraft.

Digital anti-jam GPS and navigation will provide midcourse guidance to target areas far beyond the effective range of traditional systems. AI and machine learning, meanwhile, should help the missile identify targets and plan its routes autonomously. The LRASM C-3 version should enter service next year.

On this order, Lockheed Martin will do the work in Orlando and Ocala, Fla.; and in Troy, Ala., and should be finished in November 2026. For more information contact Lockheed Martin Missiles and Fire Control online at https://www.lockheedmartin.com/en-us/products/long-range-anti-ship-missile.html, or Naval Air Systems Command at www.navair.navy.mil.

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