Embedded Analytics Stats That Will Shape 2025 and Beyond

These embedded analytics stats show how SaaS and ISV leaders are using data to scale faster, improve retention, and launch features users actually need. Get clear benchmarks and trendlines that will shape your roadmap in 2025 and beyond.

Low-Code Market Trends for 2025 & Beyond
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51% of tech leaders identify security as their top software development challenge for 2025. [1]

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45% feel AI code reliability is the biggest software development challenge for 2025, while 41% see data privacy at the top of the list. [2]

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The main priority in 2025 is AI adoption, with 73% of tech leaders planning to expand the use of AI within organizations in the next year. [3]

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55% find that AI deployment will be the biggest challenge they face. [4]

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42% of tech leaders will incorporate or increase the use of AI to effectively utilize resources in 2025. [5]

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Only 13% will use data to improve their decision making to utilize their resources more effectively. [6]

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81% of tech leaders noticed a significant increase in interest in Business Intelligence or Embedded Analytics in 2024. [7]

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81% of data analytics users use embedded analytics in 2025. [8]

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47% of users utilize BI for productivity tracking. 42% – for trend analytics, 33% for decision-making, 31% for CRM. [9]

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42% of users pinpoint struggling with tech resources as the main challenge in adopting embedded analytics. [10]

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35% of users pinpoint shifting analytics needs as the main challenge in adopting embedded analytics. [11]

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32% of users claim legacy infrastructure is the key barrier to embedded analytics adoption. 30% see cost justification as the main hurdle, while 29% claim it’s user adoption. [12]

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For 20.2% of customers, the main reason for wanting and turning to embedded analytics is to make better decisions. [13]

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39% of survey respondents say that their organizations is using embedded analytics to monitor and improve productivity. [14]

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31.4% of survey respondents say that their organization are using embedded analytics to generate higher revenue. [15]

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Understanding business problems is the top reason for using embedded analytics for 29.6% of survey respondents. [16]

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The ability to make informed business decisions is the primary reason for 24.8% of survey respondents to use embedded analytics. [17]

Reveal, Reveal Survey Report: Top Software Development Challenges for 2025.
Reveal, From Adoption to Integration: Overcoming AI Deployment Challenges in 2025-2029.
Reveal survey 2024, Embedded Analytics Survey Report 2024.
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47% of sales operations and RevOps leaders list data integration across different systems and platforms as a top data-quality challenge. [1]

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40% report inaccurate data stemming from user input as an issue. [2]

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By 2026, more than 80% of software vendors will have embedded GenAI capabilities in their products. [3]

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By 2025, context-driven analytics and AI models will replace 60% of existing models built on traditional data. [4]

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74% of CDAOs report that executive leadership has confidence in their D&A function, yet only 49% have established business outcome-driven metrics that allow stakeholders to track D&A value. [5]

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23% of CDAOs take lead in ownership of Gen AI. [6]

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82% of Gartner D&A survey respondents say they can identify the data assets needed for new D&A projects. [7]

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80% commonly share a data asset across more than one use case. [8]

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Only 46% of users have value-oriented KPIs for D&A governance. [9]

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By 2025, synthetic data and transfer learning will reduce the volume of real data needed for AI by more than 50%. [10]

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By 2026, 75% of CDAOs who fail to make organization-wide influence and measurably impact their top priority will be assimilated into technology functions. [11]

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Through 2025, at least 30% of GenAI projects will be abandoned after proof of concept due to poor data quality, inadequate risk controls, escalating costs, or unclear business value. [12]

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90% of current analytics content consumers will become content creators enabled by AI-powered tools offered by their BI solutions by the end of 2025. [13]

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60% of organizations will fail to realize the value of their AI analytics use cases with augmented analytics solutions due to incohesive data governance frameworks. [14]

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79% of corporate strategists see AI and analytics as critical to their success. [15]

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50% of strategic planning and execution activities could be partially or fully automated; currently, only 15% are. [16]

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Only 20% of strategists reported using AI-related tools, such as machine learning or natural language processing, for their function. [17]

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94% of the respondents reported using third-party APIs. [18]

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By 2025, for organizations to remain competitive, analytical and soft skills will be the most sought-after skills in the data and analytics talent market. [19]

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Gartner predicts that by 2025, 95% of decisions that currently use data will be at least partially automated. [20]

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Gartner surveyed 400 finance executives and found the most selected combination of value and technology was self-service data and analytics as a driver of employee productivity, with 49% of respondents indicating this perception of the technology. [21]

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Gartner survey reveals 80% of executives think automation can be applied to any business decision. [22]

Gartner, Sales Analytics.
Gartner, Product Development & GenAI.
Gartner, AI for Data Analytics.
Gartner, Data Analytics Summit 2024.
Gartner, Data Trends.
Gartner, Data Governance.
Gartner, Corporate Strategists Survey 2023.
Gartner, Emerging Tech Trends.
Gartner, Data & Analytics Essential Guides.
Gartner, Finance Executives Survey 2022.
Gartner, Automation in Business Decision Survey 2022.
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According to Gartner, only 29% of organizations can evaluate data fast enough to stay on top of their game. Cloudtalk.io (citing Gartner)

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40% of highly regulated enterprises will combine data and AI governance in 2025. [1]

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The other 80% still rely on the 20% for data sourcing, data discovery, data integration, building metrics and KPIs, running analytics, and delivering insights. [2]

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Embedded analytics may be the key to empowering over half of all non-tech decision-makers to utilize data-driven insights. [3]

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Data and analytics decision-makers who say that their firms have advanced insights-driven business capabilities are 8.5 times more likely than those at firms at the beginner stage to report that their firm’s annual revenue grew by 20% or more. [4]

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61% of organizations still use four or more business intelligence platforms, which means that analysts and insights professionals are constantly task- and context-switching, losing as much as 40% of their productivity. [5]

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40% of data and analytics decision-makers surveyed by Forrester in 2023 indicated that the most important scenario for AI was to streamline IT processes via AI-driven automation and decision-making. [6]

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In Forrester’s Marketing Survey, 2023, B2B respondents cite a lack of trust in the quality of data supporting analysis (40%), insufficient understanding by their teams (39%), and too many unconnected data sources (38%) as the top obstacles to executing measurement and analytics. [7]

Forrester, Predictions 2025: Artificial Intelligence.
Forrester, Bring Data to the Other 80% of Business Intelligence Users.
Forrester, Is Your B2B Organization Insights-Driven?
Forrester, The Key to Insights-Driven Decisions is Curiosity Velocity.
Forrester, Outcomes Drive Your Data Architecture Strategy.
Forrester, Leverage Data in Your Sales Strategy to Win 2023.
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The Embedded Analytics Market is expected to reach $55.54 billion by 2030. [1]

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Poor-quality data can cause enterprises and organizations approximately USD 12.9 million in losses every year. [2]

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In 2022, IT and Telecommunications were the biggest end-users of Embedded Analytics, with 27.4%. [3]

Fortune Business Insights, Embedded Analytics Market Report 2023-2030.
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The Embedded Analytics Market size was valued at USD 54.95 Billion in 2024. [1]

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The Embedded Analytics Market Size is expected to swell to 149 Billion dollars by 2031, growing at a CAGR of 14.65%. [2]

Verified Market Research, Global Embedded Analytics Market Size and Forecast.
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65% of respondents report that their organizations are regularly using GenAI. [1]

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AI adoption has surged to 72% in 2024, a massive change from the 50% adoption in previous years. [2]

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Companies already see 20% of their earnings before interest and taxes (EBIT) contributed by artificial intelligence (AI). [3]

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Data and analytics could create value worth between $9.5 trillion and $15.4 trillion a year if embedded at scale. [4]

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Only a small fraction of the value that could be unlocked by advanced-analytics approaches has been unlocked—as little as 10% in some sectors. [5]

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Companies may be squandering as much as 70% of their data-cleansing efforts. [6]

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More than half of all data lakes are not fit for purpose. [7]

McKinsey, The State of AI 2024.
McKinsey, The Data-Driven Enterprise of 2025.
McKinsey, Accelerating Data and Analytics Transformations in the Public Sector.
McKinsey, Ten Red Flags Signaling Your Analytics Program Will Fail.