Generative AI in Analytics Market is expected to grow at a CAGR of 27.60% through 2029
The global generative AI in analytics
market is to be led by advancements in natural language processing and deep
learning technologies during 2025-2029
According to TechSci Research
report, “Generative AI in
Analytics Market - Global Industry Size, Share, Trends, Opportunity, and
Forecast 2019-2029F", The Global generative AI in analytics market was valued at USD 928.75 million in 2023 and is expected to reach USD 4008.77 million by 2029 with a CAGR of 27.60% through 2029.
Advancements
in artificial intelligence technologies are a significant factor driving the
growth of the generative AI in analytics market. Recent developments in machine
learning, deep learning, and natural language processing have enhanced the
capabilities of generative models, making them more accurate, efficient, and
accessible. Innovations such as improved neural network architectures, advanced
training techniques, and increased computational power have expanded the
potential applications of generative artificial intelligence in analytics.
These technological advancements enable generative models to generate
high-quality synthetic data, simulate complex scenarios, and provide more
precise and actionable insights. As artificial intelligence technology
continues to evolve, it becomes increasingly feasible for organizations to
adopt and integrate generative models into their analytics processes. This
continuous progress in technology is a key driver of market growth, as
businesses seek to leverage cutting-edge solutions to stay ahead in a rapidly
changing environment.
The
growing emphasis on ethical and responsible artificial intelligence practices
is a notable trend in the generative AI in analytics market. As the technology
becomes more integrated into critical business processes, there is increasing
awareness of the need to address ethical considerations and ensure that
generative artificial intelligence is used in a fair and transparent manner.
Companies are implementing guidelines and frameworks to address issues such as
bias, privacy, and transparency in their artificial intelligence systems. This
includes developing strategies to detect and mitigate biases in generative
models, ensuring compliance with data protection regulations, and promoting
transparency in how artificial intelligence algorithms operate and make
decisions. The focus on ethical practices is driven by the need to build trust
with stakeholders and avoid potential legal and reputational risks.
Organizations are investing in ethical artificial intelligence initiatives and
seeking certifications and standards that demonstrate their commitment to
responsible use of generative artificial intelligence. This trend reflects a
broader movement towards creating artificial intelligence systems that are not
only technologically advanced but also aligned with societal values and ethical
principles.
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Based on application, the
forecasting and predictions segment dominated the generative AI in analytics
market in 2023 and is expected to maintain its leading position throughout the
forecast period. This dominance is driven by the critical role that accurate
forecasting and predictive analytics play in helping organizations make
informed decisions and strategize effectively. Businesses across various
sectors, including finance, retail, and healthcare, rely heavily on forecasting
models to predict future trends, manage risks, and optimize operations.
Generative AI enhances these capabilities by creating advanced models that
offer more precise and actionable predictions based on complex datasets. The
ability to simulate various scenarios and forecast outcomes with high accuracy
provides significant value, leading to increased adoption of generative
artificial intelligence solutions focused on forecasting and predictions. As
organizations continue to prioritize data-driven decision-making and seek to
gain competitive advantages, the demand for robust predictive analytics tools
is expected to grow, reinforcing the segment's market leadership. The
continuous advancements in generative AI technologies further support this
trend by improving the accuracy and reliability of forecasting models, ensuring
that they remain a critical component of analytics strategies in the future.
The Asia Pacific (APAC) region is emerging as the fastest-growing market for Generative AI in analytics, driven by a combination of technological advancements, increased investments, and the region's rapid digital transformation. Several APAC countries, particularly China, India, Japan, and South Korea, are at the forefront of adopting and integrating artificial intelligence (AI) technologies into various industries, including analytics. These countries have seen a surge in the demand for generative AI solutions to improve decision-making, streamline operations, and drive business innovation. Generative AI in analytics allows businesses to generate insights, predictions, and recommendations from large volumes of data more efficiently and accurately. This capability is highly valuable in APAC’s rapidly evolving business landscape, where companies are increasingly relying on data-driven strategies to stay competitive. The integration of generative AI can help businesses uncover hidden patterns, simulate different scenarios, and create customized analytics solutions in real-time, ultimately boosting their agility and responsiveness.
Additionally, the APAC region benefits from a large, tech-savvy workforce and the increasing availability of AI talent, especially in countries like India and China. This has led to a rise in the development of AI-driven analytics solutions tailored to local market needs. The region’s strong focus on digitalization across sectors like finance, healthcare, retail, and manufacturing further accelerates the adoption of generative AI for analytics. With significant investments in AI research and government initiatives promoting innovation, the APAC region is well-positioned to maintain its dominance in the generative AI in analytics market, offering tremendous growth potential for businesses and technology providers.
Key market players in the Generative AI
in Analytics Market are: -
- OpenAI OpCo, LLC
- IBM Corporation
- Microsoft Corporation
- Google LLC
- Amazon Web Services, Inc.
- NVIDIA Corporation
- Salesforce, Inc.
- SAP SE
- Oracle Corporation
- Palantir Technologies Inc.
- DataRobot, Inc.
- H2O.ai, Inc.
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“The generative AI in analytics market
is poised for significant growth as advancements in technology drive increased
adoption across various industries. Innovations in natural language processing,
deep learning, and machine learning are enhancing the capabilities of generative
models, enabling more accurate and actionable insights from complex data. As
businesses seek to leverage data for competitive advantage, the demand for
sophisticated predictive and prescriptive analytics solutions will rise. The
integration of generative artificial intelligence with cloud computing and the
emphasis on real-time analytics and personalized experiences will further
accelerate market expansion, driving continuous innovation and application
across sectors.” said Mr. Karan Chechi, Research Director of TechSci Research,
a research-based global management consulting firm.
“Generative AI in Analytics Market – Global Industry Size, Share, Trends, Opportunity, and Forecast, Segmented By Deployment (Cloud-based, On-premises), By Technology (Natural Language Processing, Machine Learning, Deep Learning, Others), By Application (Forecasting and Predictions, Automated Reporting, Anomaly Detection, Personalization), By Region & Competition 2019-2029F”, has evaluated the
future growth potential of generative AI in analytics market and
provides statistics & information on market size, structure, and future
market growth. The report intends to provide cutting-edge market intelligence
and help decision makers take sound investment decisions. Besides the report
also identifies and analyzes the emerging trends along with essential drivers,
challenges, and opportunities in generative AI in analytics market.
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