Generative AI In Analytics Market Forecast 2025-2034: Evaluating Growth Factors, Segments, and Emerging Trends

How Are the key drivers contributing to the expansion of the generative ai in analytics market?
The increasing need for content created by artificial intelligence is projected to fuel the advancement of generative AI in the data analysis sector. AI-produced content, including text, images, or films, is formed using advanced AI algorithms and technologies. The high demand for such content is attributed to its remarkable ability to provide tailored and relevant content on a large scale, improving user involvement and cutting down production costs for companies. Generative AI models have the capabilities to dissect huge datasets, identifying patterns, tendencies, and valuable insights that can be utilized to create content like articles, reports, and artistic pieces. For example, DOIT Software, an American company specializing in business software and AI tools, reported in February 2024 that an estimated 57 million people interacted with the generative AI platform ChatGPT in 2022, and this number jumped to 100 million by January 2023. Consequently, the escalating demand for AI-created content propels the expansion of the generative AI in the analytics market.

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What growth opportunities are expected to drive the generative ai in analytics market's CAGR through 2034?
In recent times, there has been a significant growth in the market size of generative AI in analytics. It is projected to surge from $1.3 billion in 2024 to $1.7 billion in 2025, with a compound annual growth rate (CAGR) of 31.2%. The surge in growth during the past period has been propelled by factors such as the increment in data volumes, improvements in deep learning algorithms, enhanced computational power, expansion in the cloud computing infrastructure and the proliferation of big data analytics.

In the coming years, the generative AI in analytics market is predicted to experience a surge in its value, reaching a whopping $4.98 billion by 2029, with a compound annual growth rate (CAGR) of 30.9%. This exponential growth during the projected period can be linked to several factors - integration with Internet of Things (IoT) devices, the advent of explainable AI (XAI), the embrace of federated learning methods, the extension of AI-driven automation into business processes, and the incorporation of generative AI with natural language processing (NLP) applications. The period of prediction will be marked by the democratization of generative AI instruments, heightened emphasis on ethical AI construction, the spread of generative adversarial networks (GANs), the ascendance of AI-enhanced creativity in content generation, as well as the broadening of generative AI utilization in the healthcare and life sciences sectors.

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What are the most significant trends transforming the generative ai in analytics market today?
Leading corporations in the generative AI in analytics sector are resorting to innovative tech advancements, such as AI-driven video analytics, to maintain their market dominance. This kind of software tool leverages machine learning and deep learning algorithms to assess video data, and from it, distil actionable insights and outcomes. For example, Dallmeier Electronic GmbH & Co. KG, a German firm with expertise in devising video security tech solutions, launched Sedor AI, an AI-powered video analytics tool intended for maritime uses, in September 2022. This software is designed to recognize ships on unencumbered water surfaces in standard conditions and difficult environmental variables such as waves and water reflections. Compliant with legal guidelines like the ISPS (International Ship and Port Facility Security) Code, the software offers support to port managers and refineries in guarding against unauthorized waterside access and associated threats like piracy and terrorist attacks.

Which growth-oriented segments of the generative ai in analytics market are leading the industry's development?
The generative AI in analytics market covered in this report is segmented -

1) By Technology: Machine Learning, Natural Language Processing, Deep Learning, Computer Vision, Robotic Process Automation
2) By Deployment: Cloud-Based, On-Premise
3) By Application: Data Augmentation, Anomaly Detection, Text Generation, Simulation And Forecasting

Subsegments:
1) By Machine Learning: Supervised Learning, Unsupervised Learning, Reinforcement Learning, Semi-Supervised Learning
2) By Natural Language Processing (NLP): Text Generation, Sentiment Analysis, Language Translation, Speech Recognition
3) By Deep Learning: Neural Networks, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Generative Adversarial Networks (Gans)
4) By Computer Vision: Image Classification, Object Detection, Image Generation, Facial Recognition
5) By Robotic Process Automation (RPA): Workflow Automation, Intelligent Process Automation, Cognitive Automation, Chatbot Integration

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What regions are leading the charge in the generative ai in analytics market?
North America was the largest region in the generative AI in analytics market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the generative AI in analytics market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.

What companies are at the forefront of innovation in the generative ai in analytics market?
Major companies operating in the generative AI in analytics market report are Amazon Inc.; Apple Inc.; Alphabet Inc.; Microsoft Corporation; Dell Technologies Inc.; Siemens AG; accenture* PLC; International Business Machines Corporation (IBM); Oracle Corporation; SAP SE; NVIDIA Corporation; Adobe Inc.; Block Inc.; Automatic Data Processing Inc.; ServiceNow Inc.; Workday Inc.; Atlassian Corporation; Slack Technologies Inc.; OpenAI; MongoDB Inc.; Box Inc.; SG Analytics Pvt. Ltd.; Decimal Point Analytics Pvt; Gramener Inc.; Anthropic PBC; Valiance Solutions Inc.

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What Is Covered In The Generative AI In Analytics Global Market Report?

• Market Size Forecast: Examine the generative ai in analytics market size across key regions, countries, product categories, and applications.
• Segmentation Insights: Identify and classify subsegments within the generative ai in analytics market for a structured understanding.
• Key Players Overview: Analyze major players in the generative ai in analytics market, including their market value, share, and competitive positioning.
• Growth Trends Exploration: Assess individual growth patterns and future opportunities in the generative ai in analytics market.
• Segment Contributions: Evaluate how different segments drive overall growth in the generative ai in analytics market.
• Growth Factors: Highlight key drivers and opportunities influencing the expansion of the generative ai in analytics market.
• Industry Challenges: Identify potential risks and obstacles affecting the generative ai in analytics market.
• Competitive Landscape: Review strategic developments in the generative ai in analytics market, including expansions, agreements, and new product launches.

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