90% of AI projects never reach production, and $17.8 billion is wasted on unused or underused SaaS licenses. Failed adoption also shows up in missed outcomes, with 49% of organizations falling short on analytics initiatives and 57% saying their AI efforts do not achieve business results. This article breaks down where adoption fails across change management, user behavior, and enterprise systems.
Key Takeaways
- 35% of organizations plan to increase investment in change management due to high failure rates from adoption shortfalls (trend response)
- 29% of enterprises reported that their robotic process automation programs achieved business outcomes (repeat of adoption success rate; contrasted with non-adoption)
- 28% of respondents said their digital initiatives did not deliver expected ROI within 12 months, indicating failed adoption of business initiatives
- 49% of organizations reported that they did not achieve expected outcomes from their analytics initiatives, indicating adoption failure of analytics into decision making
- 30% of projects are delayed due to user acceptance/testing issues (a proxy for adoption failure in implementation)
- 58% of respondents say adoption tracking is missing or inconsistent for AI tools, making it hard to identify failed adoption
- 57% of organizations said their AI initiatives do not achieve business outcomes, often due to workforce adoption and process integration issues
- 35% of employees report that they never use the collaboration tools provided by their organization, indicating failed adoption
- 46% of respondents said they do not measure or monitor end-user adoption of SaaS applications (preventing correction of failed adoption)
- 25% of respondents said they stopped using a tool/technology because it did not meet expectations, reflecting real-world failed adoption of software/tech
- 40% of data warehouse modernization efforts reported not meeting expected outcomes, suggesting failed adoption of modernization initiatives
- 71% of HR leaders reported that they did not have the right HR technology in place to support business outcomes, which can lead to failed adoption and rollouts of HR systems
- $17.8 billion global spend on SaaS waste from unused/underused licenses (measured as overprovisioning and underutilization)
- $400 billion global cost of poor data quality (measurable cost impact of failed adoption of data management)
- 40% of organizations say data quality issues increase costs and reduce productivity (adoption failure of data governance)
Failed adoption is driving massive waste across software, data, AI, and cybersecurity, from unused licenses to security breaches.
Related reading
01 · Category
User Adoption7 stats
01
57% of organizations said their AI initiatives do not achieve business outcomes, often due to workforce adoption and process integration issues
02
35% of employees report that they never use the collaboration tools provided by their organization, indicating failed adoption
03
46% of respondents said they do not measure or monitor end-user adoption of SaaS applications (preventing correction of failed adoption)
04
11% of organizations reported that only a small fraction of staff use the CRM after rollout, indicating CRM adoption failure
05
55% of workers said they would use a new tool if it saves time (time savings are adoption drivers; absence leads to non-adoption)
06
76% of employees say they use shadow IT because the approved tools don’t meet their needs, which often indicates failed adoption of enterprise systems.
07
48% of employees report that they do not feel confident using enterprise tools, contributing to lower adoption and failed rollout outcomes.
Interpretation
User Adoption Interpretation
Across user adoption, the pattern is clear that when tools fail to fit real work needs, adoption collapses, with 76% of employees using shadow IT and 55% saying they would adopt a new tool only if it saves time, while only 35% of employees use collaboration tools and 46% of SaaS organizations do not even measure end user adoption.
02 · Category
Cost Analysis7 stats
01
$17.8 billion global spend on SaaS waste from unused/underused licenses (measured as overprovisioning and underutilization)
02
$400 billion global cost of poor data quality (measurable cost impact of failed adoption of data management)
03
40% of organizations say data quality issues increase costs and reduce productivity (adoption failure of data governance)
04
$1.1 trillion annual loss from ineffective cybersecurity processes (often adoption and operationalization failures)
05
$22.4 million average cost of a breach for organizations in the United States (IBM report), reflecting higher costs tied to ineffective adoption
06
61% of breaches include credential theft, where adoption of MFA and identity controls can fail (measurable risk impact)
07
14% of respondents reported project overruns attributable to lack of adoption/user buy-in, linking failure to measurable schedule/cost overruns
Interpretation
Cost Analysis Interpretation
Cost overrun from failed adoption is already massive, with global spending on SaaS waste reaching $17.8 billion and poor data and cybersecurity practices compounding losses, including $400 billion in poor data quality impacts and $1.1 trillion annually lost to ineffective cybersecurity processes.
03 · Category
Industry Trends4 stats
01
35% of organizations plan to increase investment in change management due to high failure rates from adoption shortfalls (trend response)
02
29% of enterprises reported that their robotic process automation programs achieved business outcomes (repeat of adoption success rate; contrasted with non-adoption)
03
28% of respondents said their digital initiatives did not deliver expected ROI within 12 months, indicating failed adoption of business initiatives
04
90% of AI projects never reach production according to Gartner cited estimates (failed adoption from prototype to operational AI)
Interpretation
Industry Trends Interpretation
Industry trends point to a widespread adoption problem, with 90% of AI projects never making it to production and 28% of digital initiatives missing expected ROI within 12 months, while even 35% of organizations are planning to boost change management investment due to high failure rates.
More related reading
04 · Category
Transformation Failure4 stats
01
25% of respondents said they stopped using a tool/technology because it did not meet expectations, reflecting real-world failed adoption of software/tech
02
40% of data warehouse modernization efforts reported not meeting expected outcomes, suggesting failed adoption of modernization initiatives
03
71% of HR leaders reported that they did not have the right HR technology in place to support business outcomes, which can lead to failed adoption and rollouts of HR systems
04
62% of organizations reported that end users were not fully engaged with new digital tools, indicating adoption failure due to insufficient user buy-in
Interpretation
Transformation Failure Interpretation
Transformation failure is clearly tied to unmet expectations and weak engagement, with 40% of data warehouse modernization efforts falling short, 62% of organizations reporting low end user engagement, and 71% of HR leaders lacking the right technology to drive outcomes.
05 · Category
Adoption Metrics3 stats
01
49% of organizations reported that they did not achieve expected outcomes from their analytics initiatives, indicating adoption failure of analytics into decision making
02
30% of projects are delayed due to user acceptance/testing issues (a proxy for adoption failure in implementation)
03
58% of respondents say adoption tracking is missing or inconsistent for AI tools, making it hard to identify failed adoption
Interpretation
Adoption Metrics Interpretation
Across adoption metrics, 49% of organizations say analytics initiatives fail to deliver expected outcomes, and the problem is compounded by 30% of projects slipping due to user acceptance or testing issues and 58% reporting inconsistent adoption tracking for AI tools, making failed adoption both more common and harder to spot.
06 · Category
Industry Overview9 stats
01
41% of breaches are attributed to credential theft and misuse, which depends on users adopting identity controls such as MFA.
02
27% of organizations do not enforce MFA for all accounts, increasing the likelihood of account compromise when MFA adoption is incomplete.
03
44% of organizations say they lack adequate identity governance practices, which can result in poor adoption of least-privilege controls.
04
60% of organizations do not have a formal process for change management, which increases the likelihood of failed adoption after rollout.
05
34% of employees strongly agree that their organization does not provide the training needed to successfully use new technologies, raising the risk of failed adoption.
06
61% of companies report that their analytics or AI initiatives do not meet internal expectations due to adoption barriers (people and workflow integration).
07
55% of organizations say that implementation teams do not monitor post-launch adoption performance closely enough to detect underuse early.
08
The average cost of poor data quality is reported at $12.9 million per year per organization in the United States.
09
Organizations lose an average of 20% of revenue due to poor data management and adoption of analytics/data processes.
Interpretation
Industry Overview Interpretation
Across the Industry Overview, adoption failure is driven by identity and process gaps, with 41% of breaches tied to credential theft that relies on MFA and 60% of organizations lacking formal change management, showing that stronger adoption of identity controls and rollout discipline are key.
report visual · Breakdown
Failed Adoption: What Goes Wrong
A large share of organizations and employees report failed adoption across tools, data, and AI—driven by missing measurement, low confidence/training, and workforce non-use.
40%
40% of organizations say data quality issues increase costs and reduce productivity (adoption failure of data governance
60%
60% of organizations do not have a formal process for change management, which increases the likelihood of failed adopti
source-verifieddomo.com · pmi.org
Reference
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
APA
Julian Richter. (2026, February 13). Failed Adoption Statistics. Gitnux. https://gitnux.org/failed-adoption-statistics
MLA
Julian Richter. "Failed Adoption Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/failed-adoption-statistics.
Chicago
Julian Richter. 2026. "Failed Adoption Statistics." Gitnux. https://gitnux.org/failed-adoption-statistics.
Sources & references
34 datasets cited across this report · attribution is report-level
+14 additional datasets cited (not shown individually)