- While 84% of data leaders express confidence in AI outputs, a significant trust gap exists. Only 30% fully rely on AI answers, while 54% verify results before making decisions, highlighting a disconnect between confidence and actionable trust.
- Organizations recognize the importance of data quality for AI success, but 86% of data teams spend at least 20 hours monthly on data prep, creating unsustainable resource demands and diverting attention from strategic work.
- Simba helps builders embed trusted intelligence into every product, providing access to the right data at the right time so organizations can spend less time debating and more time making decisions.
RALEIGH, N.C., Sept. 16, 2026 (GLOBE NEWSWIRE) -- Simba, the data and analytics provider built on 30 years of heritage, today launched as a dedicated brand built to solve the AI confidence paradox. Also launched today, Navigating Uncertainty: The State of Data and Analytics in 2027 report reveals a striking contradiction: while 84% of organizations report confidence in their AI-generated insights, 85% have experience with or are concerned about unreliable outputs. Simba, the embedded intelligence leader built for a world running on AI, closes this trust gap by delivering consistent, governed intelligence directly from source data.
The report shows that organizations are investing heavily in analytics and AI, spending 20 to 40+ hours monthly on data preparation alone, but they don’t trust the outputs. Governance requirements are now the primary driver of analytics and AI deployment decisions, and 98% of organizations view data quality as critical to AI success.
"Most companies are concerned about hallucinations, but they don’t know how to solve the issue," said Alison Huselid, Chief Product Officer at Simba. “Organizations are investing in tuning their models when the root issue lies beneath the surface: the quality and consistency of their data foundation. Untrustworthy AI outputs cannot be built on top of inconsistent or not auditable data. Simba applies governance at the data layer to ensure that every question draws from the same governed, consistent data.”
The Confidence Gap
AI deployments are revealing a painful reality: most companies don’t trust its outputs, undercutting potential gains or time savings, which get spent addressing leading barriers including data quality concerns (22%), security and governance concerns (20%), inability to verify AI outputs against source data (18%), and AI hallucinations/fabricated information (18%).
For product teams building data products and serving customers through embedded analytics, this directly impacts deployment velocity and outcomes.
Organizations must have a foundation of governance, transparency, and compliance to build trust in AI. Respondents say the top drivers of AI trust are source traceability (38%), business context understanding (28%), and comprehensive audit trails (26%).
Simba helps builders embed trusted intelligence into every product and powers the most demanding data platforms. Organizations get access to the right data at the right time without needing to move, copy, or reorganize it. Outputs are consistent, verifiable, and defensible, with context provided where decisions are made. Data visualization capabilities give every user the right view of the right data in a format they can act on, helping organizations spend less time debating and more time making decisions.
The Operational Burden of AI
Beyond confidence gaps, the operational burden is unsustainable. Most respondents (86%) spend at least 20 hours monthly preparing data for AI consumption, and 83% receive more than 10 analytics enhancement requests monthly. Teams that should be innovating are overcome by integrating, maintaining, and governing fragmented analytics platforms.
Still, the research reveals a clear market shift. Organizations are making deployment and architectural decisions based on governance, compliance, and control requirements:
- 95% of survey respondents are subject to General Data Protection Regulation (GDPR);
- 75% prioritize regulatory compliance as a primary decision factor in AI governance; and
- 62% prefer hybrid deployment models that keep data on-premises or in private cloud.
Organizations operating in regulated industries face an impossible choice with most solutions: adopt modern AI and analytics or maintain data governance and compliance. Most cloud-first platforms force this tradeoff. That choice is no longer acceptable.
Certainty Isn’t Optional
"The competitive advantage goes to platforms that refuse the false choice between modern AI and data control," Huselid said. "Organizations are demanding on-premises and hybrid execution with full governance transparency. That's reshaping the entire category."
The shift toward governed, production-grade AI is under way, and companies will prioritize governed AI. But there are questions. How quickly can they build it? Which platforms ensure consistency? Which solutions keep sensitive data in place? Which vendors give us control at scale? Balancing AI innovation with trusted intelligence is no longer optional. It’s required.
Visit simba.com to find out how Simba helps builders embed trusted intelligence into every product.
About the Research
Navigating Uncertainty: The State of Data and Analytics in 2027 is based on a survey of 325 data decision-makers in Canada, France, Germany, Ireland, South Africa, Switzerland, United Arab Emirates, United Kingdom, and the United States and included independent software vendors (ISVs) and enterprise organizations.
About Simba
Built on insightsoftware's decades of finance software expertise, Simba is a data and analytics provider for a world running on AI. We help builders embed trusted intelligence into every product. Powering the most demanding data platforms on the planet, Simba gives access to the right data at the right time without needing to move, copy, or reorganize it. Backed by a thirty-year heritage, outputs are consistent, verifiable, and defensible, with context provided where decisions are made. Data visualization capabilities give every user the right view of the right data in a format they can act on, helping organizations spend less time debating and more time making decisions. Learn more at simba.com.
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