Global Augmented Analytics Market Surges at 27.2% CAGR as Digital Transformation Accelerates Worldwide

The global augmented analytics market is estimated at USD 9.2 billion in 2024, and is projected to skyrocket to USD 39.2 billion by 2030, registering a robust CAGR of 27.2% over 2025–2030. This growth is being fuelled by the rising urgency among organizations to automate data collection and data preparation, enabling them to convert raw data into actionable insights — ultimately driving revenue growth. As enterprises across sectors demand greater efficiency, cost-effectiveness, and productivity, conventional analytics tools are increasingly being augmented with artificial intelligence (AI) and machine learning (ML) for enhanced accuracy and predictive power — pushing companies to adopt advanced analytics at scale.

Similarly, the accelerating wave of global digitization — from widespread smartphone and internet adoption among consumers to government and enterprise digital transformations — is dramatically increasing the volume of usable data. As more processes digitize and industrial automation spreads, companies are deriving deeper, real-time insights from this data. This dual push — of data explosion plus demand for smarter decision-making — is setting the stage for augmented analytics to become central in enterprise strategies worldwide.

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Key Insights

• The component-wise segmentation reveals that software accounted for the largest share in 2024, making up around 65% of the market. Meanwhile, services — including consulting, deployment, operations, and managed support — are identified as the fastest-growing segment over the forecast period. This reflects increasing demand for end-to-end implementation and ongoing support solutions as organizations adopt complex augmented-analytics platforms.
• In terms of organization size, large enterprises currently dominate, thanks to their financial and technical capacity to procure and deploy advanced analytics solutions. Their large customer bases and extensive data generation make analytics especially valuable for optimizing operations and improving customer experiences. At the same time, small and medium-sized enterprises (SMEs) are projected to grow fastest (around 29% CAGR), driven by broader cloud adoption, cost-effective deployment, and increasing availability of AI-powered tools tailored for smaller firms.
• Across industry verticals, Banking, Financial Services & Insurance (BFSI) leads in 2024 with about 25% revenue share — attributable to growing demand for data-driven transaction management, customer analytics, fraud detection, and personalized financial services. Meanwhile, healthcare is expected to witness the fastest growth as hospitals, life-sciences firms, and health insurers adopt AI-powered analytics to manage patient data, optimize operations, and support decision-making — often leveraging “no-code” platforms to minimize dependence on technical experts. Other industries covered include retail, telecom & IT, manufacturing, government, and logistics.
• On the deployment mode front, cloud-based solutions represent the larger share in 2024 and are forecast to maintain the higher CAGR (≈ 28.0%) through 2030. The appeal lies in cost-effectiveness, scalable storage and computing, automatic updates, and flexibility — especially beneficial for SMEs and geographically distributed teams.
• From a business-function perspective, sales and marketing commands the largest slice (≈ 35% share in 2024) and also shows the fastest growth trajectory. This highlights how companies increasingly rely on augmented analytics to understand customer behavior, optimize pricing and promotions, tailor digital marketing strategies, and derive insights from consumer data streams. 
• Regional trends indicate that North America remains the largest regional market in 2024, benefiting from strong R&D activity and early adoption of advanced analytics tools by major industry players. At the same time, Asia-Pacific (APAC) is forecast to be the fastest-growing region, with rapid adoption of AI-based business intelligence in countries like India, China, and Japan — driven by rising demand to handle unstructured data and real-time streaming data analytics. Emerging investments from local firms — for example, the launch of platforms such as HyperSense — underscore growing regional momentum. 
• On market structure and competition, the landscape remains moderately consolidated: a handful of major players hold significant market share, while numerous smaller vendors offer customized solutions for niche requirements. Larger IT firms benefit from financial strength and broad enterprise clients; many are actively acquiring promising startups to expand their analytics portfolios. This consolidation underscores ongoing competitive dynamics but also suggests opportunities for emerging players — especially those specializing in domain-specific analytics or offering agile, cost-effective solutions to SMEs or emerging markets.
• The technological evolution — including integration of AI, ML, and natural language processing (NLP) — is increasingly enabling augmented-analytics software to generate sophisticated, actionable insight, support forecasting, trend analysis, and decision support. As per analysis, ML-based analytics may power over 300 enterprise use cases, potentially delivering an average 15% return on investment for businesses leveraging these tools.
• The global wave of digital transformation and industrial automation — from consumer online services to industrial IoT and healthcare diagnostics — is creating massive volumes of data from devices, applications, and services. Augmented analytics is increasingly critical in turning this data into insight — from recommending e-commerce products to healthcare diagnosis, infrastructure energy-use optimization, or predictive maintenance in manufacturing — thus boosting operational efficiency and sustainability.
• However, the market faces headwinds, notably around data privacy, security risks and regulatory compliance. Use of sensitive personal, financial, or medical data heightens risk of breaches — which could lead to severe financial losses, reputational damage, and compliance costs. Also, the high cost and technical complexity of augmented-analytics solutions — often requiring legacy system upgrades, specialized expertise, and ongoing maintenance — can deter small and medium enterprises or startups from adoption.