Data Statistics

What the latest research says about the cost, quality and trustworthiness of enterprise data, and how ready it is for AI, from IBM, Salesforce, Gartner, Deloitte and more, alongside DoubleTrack’s own research. Search it, or filter by theme and type of evidence.

Last updated November 2026 · 35 statistics

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Bad Data Is Expensive

The cost of bad data shows up in lost revenue, wasted engineering time, and AI projects trained on data nobody trusts.

$617B

is what dirty data costs US businesses each year, about 2% of GDP, across roughly 139.8 million employees.

DoubleTrack, The Hidden Cost of Dirty Data, 2026

EstimateDoubleTrack research

Sample and caution

Sample: Built from Gartner’s $12.9M enterprise baseline (2020), Census Bureau employment data and industry IT-spend multipliers.

Caution: A modeled estimate meant to show scale, not a measurement of any one company.

$1.2T

is where the annual cost of dirty data could reach by 2030 if data volumes keep doubling about every four years.

DoubleTrack, The Hidden Cost of Dirty Data, 2026

ForecastDoubleTrack research

Sample and caution

Sample: A projection from the same model.

Caution: Built on an assumed doubling time, not a measurement.

37%

of organizations lose revenue as a direct result of poor CRM data quality, and companies lose an average of 16 sales deals a quarter.

Validity, State of CRM Data Management in 2025

Survey

Sample and caution

Sample: 602 CRM users and administrators in the US, UK and Australia, released July 2025.

Caution: Validity sells CRM data-quality software, and respondents estimated their own losses.

55%

of data and analytics leaders at companies training or fine-tuning their own AI models say they wasted significant resources doing so with bad data.

Salesforce, State of Data and Analytics, 2025

Survey

Sample and caution

Sample: 3,800 analytics and IT decision makers in 18 countries, fielded June 27 to August 13, 2025.

Caution: Salesforce sells data and analytics products.

$49,600

an hour is what enterprise data leaders estimate pipeline downtime costs the business. Enterprises average about 60 hours of downtime a month.

Fivetran, Enterprise Data Infrastructure Benchmark Report 2026

Survey

Sample and caution

Sample: 500 senior data and technology leaders at companies with 5,000+ employees, fielded Q4 2025.

Caution: A respondent estimate, and Fivetran sells managed data pipelines. Its headline “$36M a year” is this hourly figure multiplied out.

114%

is the spread in the annual cost of dirty data per employee between the lowest and highest US counties ($3,092 to $6,621). State averages differ by only 18%.

DoubleTrack, The Hidden Cost of Dirty Data, 2026

EstimateDoubleTrack research

Sample and caution

Sample: A county-level model across US business establishments.

Caution: Modeled, and county figures lean on local industry mix.

Annual cost of dirty data per employee, by industryIndustry rates range from $2,995 to $12,161 per employee. The industry-adjusted US average is about $4,400.
  • Information$12,161
  • Finance & Insurance$5,991
  • 13 industries at the baseline*$4,912
  • Professional, Scientific, Technical$4,014
  • Retail Trade$3,714
  • Transportation & Warehousing$3,175
  • Healthcare & Social Assistance$2,995
  • Manufacturing$2,995

*Thirteen of the 20 industries use the $4,912 baseline because no IT-spend data exists for them. Information covers software, tech hosting, media and telecom.

Source: DoubleTrack, The Hidden Cost of Dirty Data, 2026 Estimate DoubleTrack research

Confidence Outruns Reality

Most leaders say their data is ready. The same surveys show otherwise.

Nearly 9 in 10

data and analytics leaders say they have the data readiness AI requires, yet 43% name data readiness as the biggest obstacle to aligning AI with business goals.

Precisely and Drexel LeBow, 2026 State of Data Integrity and AI Readiness

Survey

Sample and caution

Sample: 505 leaders at companies with 1,000+ employees or $250M+ revenue in the US, UK, France and Germany, fielded in the second half of 2025.

Caution: Precisely sells data integrity software. The report says 87% in one place and 88% in another. Last year’s edition reported 12% from a broader, less senior sample, so the two years are not comparable.

81% → 26%

of chief data officers say their data strategy is integrated with their technology roadmap, but only 26% are confident their data can support new AI-enabled revenue streams.

IBM Institute for Business Value, 2025 CDO Study

Survey

Sample and caution

Sample: 1,700 senior data and analytics leaders in 27 geographies and 19 industries, with Oxford Economics, fielded July to September 2025.

Caution: Leaders’ self-assessments, and IBM sells data and AI products.

84%

of data and analytics leaders say their data strategies need a complete overhaul before their AI ambitions can succeed.

Salesforce, State of Data and Analytics, 2025

Survey

Sample and caution

Sample: The 3,800 data and analytics leaders.

Caution: Salesforce sells data and analytics products.

65% vs. 75%

of data leaders believe most employees trust the data used for AI, while 75% say those employees need training in data literacy.

Informatica, CDO Insights 2026

Survey

Sample and caution

Sample: 600 data leaders in the US, UK/EU and APAC, released January 2026.

Caution: Informatica sells data management software.

19% vs. 84%

of CRM users say leaders change course when shown countering data, though 84% of leaders say they do. 37% of staff say they regularly fabricate data to tell leaders what they want to hear.

Validity, State of CRM Data Management in 2025

Survey

Sample and caution

Sample: The same 602 CRM users and administrators.

Caution: Validity sells CRM data-quality software.

7%

of enterprises say their data is completely ready for AI, and 27% say it is not very or not at all ready.

Cloudera and Harvard Business Review Analytic Services, Taming the Complexity of AI Data Readiness, 2026

Survey

Sample and caution

Sample: More than 230 members of the Harvard Business Review audience involved in AI data decisions, fielded October 2025.

Caution: A small, self-selected sample, and Cloudera sponsored it. Readiness figures swing widely by who is asked: compare the first card in this section.

Eric Heine, Chief Executive Officer at DoubleTrack

Data is the lifeblood of AI, and getting it organized and passing the four Rs test (Reliable, Revealing, Reusable, and Relevant) is foundational to have any chance of success in your AI initiatives.

Eric HeineChief Executive Officer, DoubleTrackNot sure where your data stands? Try the 844 Snapshot →

Where It Breaks: Quality, Silos and Pipelines

Data fails in ordinary ways: inaccurate records, systems that don’t connect, and pipelines that break.

76%

of CRM users say less than half of their organization’s CRM data is accurate and complete, and 45% say their CRM data isn’t prepared for AI.

Validity, State of CRM Data Management in 2025

Survey

Sample and caution

Sample: 602 CRM users and administrators.

Caution: Validity sells CRM data-quality software.

897

applications is the average enterprise’s count, and only 29% of them are connected.

Salesforce, State of Data and Analytics, 2025

Estimate

Sample and caution

Sample: Cited in Salesforce’s report release.

Caution: The release does not say where this figure comes from, so treat it as Salesforce’s claim.

89%

of data and analytics leaders with AI in production say they have experienced inaccurate or misleading AI outputs.

Salesforce, State of Data and Analytics, 2025

Survey

Sample and caution

Sample: The 3,800 data and analytics leaders.

Caution: Self-reported, and “inaccurate or misleading” is the respondent’s own judgment.

57%

of data leaders call data reliability a key barrier to moving AI projects from pilot to production.

Informatica, CDO Insights 2026

Survey

Sample and caution

Sample: 600 data leaders in the US, UK/EU and APAC.

Caution: Informatica sells data management software. A regional release reports other, higher figures that are not in the global release used here.

53%

of data engineering time goes to pipeline maintenance, with about 35 full-time engineers keeping an average of 328 pipelines running.

Fivetran, Enterprise Data Infrastructure Benchmark Report 2026

Survey

Sample and caution

Sample: 500 senior data and technology leaders, fielded Q4 2025.

Caution: Fivetran sells managed data pipelines.

7%

of organizations have 70% or more of their unstructured data cleaned, prepared and classified for AI. 57% have half or less ready.

Komprise, Unstructured Data for AI & Lakehouses Survey, 2026

Survey

Sample and caution

Sample: 500 technical decision makers (IT managers, data engineers, AI directors, CIOs and CTOs), fielded September 2026.

Caution: Komprise sells unstructured data management. A different measure from the 7% in the second section.

71%

of executives say they struggle with data accuracy, access and management, the top barrier to AI adoption in ServiceNow’s index. Only 16% have replaced fragmented legacy systems with an integrated platform.

ServiceNow, Enterprise AI Maturity Index 2026

Survey

Sample and caution

Sample: 4,500 executives across 19 countries and 12 industries.

Caution: The landing page doesn’t give fielding dates or define “struggle,” and ServiceNow sells an integrated platform.

Andy Boettcher, Chief Innovation Officer at DoubleTrack

Most companies are drowning in unhelpful data, and that friction is silently killing your effectiveness at every level.

Andy BoettcherChief Innovation Officer, DoubleTrackThe four Rs: relevant, reliable, revealing, reusable. See the approach →

Nobody’s Measuring It

Few organizations can say how good their data is, or what it’s worth.

29%

of data leaders have clear measures of the value of their data-driven business outcomes.

IBM Institute for Business Value, 2025 CDO Study

Survey

Sample and caution

Sample: 1,700 senior data and analytics leaders.

Caution: IBM sells data and AI products.

49%

of business leaders say they can reliably generate timely insights.

Salesforce, State of Data and Analytics, 2025

Survey

Sample and caution

Sample: 3,852 line-of-business leaders.

Caution: Salesforce sells analytics products.

28%

of organizations on average have quantified ROI from AI, though 68% describe themselves as maturing or mature with AI.

Komprise, Unstructured Data for AI & Lakehouses Survey, 2026

Survey

Sample and caution

Sample: 500 technical decision makers, fielded September 2026.

Caution: Komprise sells unstructured data management.

Governance Builds Trust

Organizations with data governance trust their data more, and most haven’t yet extended governance to AI.

43%

of data and analytics leaders have established formal data governance frameworks and policies, and 88% agree AI demands entirely new approaches to governance and security.

Salesforce, State of Data and Analytics, 2025

Survey

Sample and caution

Sample: The 3,800 data and analytics leaders.

Caution: Salesforce sells governance and data products.

76%

say their AI governance does not completely keep pace with employees’ use of AI.

Informatica, CDO Insights 2026

Survey

Sample and caution

Sample: 600 data leaders.

Caution: Informatica sells data management software.

50% by 2028

of organizations will adopt a zero-trust posture for data governance because of the spread of unverified AI-generated data, according to Gartner.

Gartner press release, January 2026

Forecast

Sample and caution

Sample: A Gartner prediction.

Caution: A prediction, not a measurement.

People and Priorities

The hard part is rarely the technology. It’s skills, culture and what gets built first.

93.2%

of executives name culture and change management, not technology, as the greatest impediment to data and AI adoption. 92.7% say interest in AI has led to a greater focus on data.

Data & AI Leadership Exchange, 2026 AI & Data Leadership Executive Benchmark Survey

Survey

Sample and caution

Sample: About 110 Fortune 1000 and leading global organizations, 15th annual, invitation-only.

Caution: Executives’ perceptions, and 42.7% of respondents are in financial services.

61%

of chief data and analytics officers say improving data quality and access is key to AI and agentic AI succeeding.

Deloitte, 2026 Chief Data and Analytics Officer Survey

Survey

Sample and caution

Sample: 100 C-suite executives at companies with $1B+ in revenue, fielded August to September 2025.

Caution: A small sample.

46%

more AI roles are open than the data infrastructure roles needed to support them: 111,296 AI and machine learning postings against 76,271 data infrastructure postings.

DoubleTrack, Hiring Robots Before Mechanics, 2026

MeasuredDoubleTrack research

Sample and caution

Sample: 187,567 US job postings via Adzuna, November 2025, across 20 AI/ML and 20 data infrastructure roles.

Caution: Postings, not hires.

Who is hiring AI before data foundations?How far one type of role outnumbers the other in open job postings, by sector. Regulated sectors lean toward data roles.

More data roles than AI roles

  • Hospitality295%
  • Manufacturing273%
  • Finance240%
  • Retail188%
  • Healthcare164%

More AI roles than data roles

  • Sales232%
  • Legal181%
  • Engineering168%
  • Marketing54%
  • Technology31%

Source: DoubleTrack, Hiring Robots Before Mechanics, 2026 Measured DoubleTrack research

About These Statistics

Last updated November 2026. This page collects research from 2025 and 2026 on the cost, quality and trustworthiness of enterprise data and how ready it is for AI.

Where the numbers come from. Each statistic links to the publisher’s own report, announcement or page. Statistics are paraphrased rather than quoted, and each one shows its source, year, sample and any caution about how to read it.

Evidence types. Survey statistics reflect what respondents reported. Measured statistics come from observed data, such as job postings. Forecasts are predictions, not measurements. Estimates are modeled or analyst estimates.

Why readiness numbers differ. Readiness figures on this page range from 7% to nearly nine in ten, depending on who was asked, how “ready” was defined and how the sample was recruited. Treat any single figure as one reading, not the answer.

Who published what. Most publishers here sell products related to their research, including Salesforce, IBM, Informatica, Fivetran, Validity, ServiceNow, Komprise, Cloudera and Precisely. Where that matters, the caution on the statistic says so.

Predictions. Gartner’s figure is a forecast and is labeled that way.

DoubleTrack research. Figures marked DoubleTrack research come from our published studies: The Hidden Cost of Dirty Data and Hiring Robots Before Mechanics. The dirty data total is a modeled estimate.

Spot something out of date? Tell us and we will check it.

Cite this page. DoubleTrack. (2026). Data statistics. https://www.doubletrack.com/data-statistics

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