Alteryx has released new research highlighting a persistent gap between surging enterprise investments in AI and automation and their actual business impact. Despite increased spending, low trust in AI outputs, poor data quality, and legacy infrastructure continue to limit adoption, with fewer than one in four AI pilots advancing to full production.
Quick Intel
The study reveals a clear disconnect: while organizations ramp up AI ambitions, real-world deployment stalls as generative AI applied directly to raw data sources often produces hallucinations, inconsistent outputs, and variable responses that erode confidence, especially in strategic applications.
Trust barriers are pronounced for high-stakes use cases. Nearly half of respondents trust AI for automating routine tasks, drafting content, or monitoring systems, but far fewer extend that confidence to supporting decisions, forecasting, or planning—areas where explainability and reliability are essential.
Data quality and governance emerge as foundational requirements for agentic AI to deliver meaningful impact. Leaders overwhelmingly identify accessible, high-quality, and well-governed data as the primary enabler, underscoring the need to address these basics before scaling advanced capabilities.
Ownership dynamics are evolving, with expectations that responsibility for AI workflows will decentralize to lines of business. This shift—from 22% today to 33% by 2028—reflects growing departmental adoption and the push for AI to integrate more deeply into daily operations.
Adoption momentum remains strong, with 89% of leaders planning to maintain or increase AI budgets in 2026 and nearly half targeting higher investments in infrastructure and tools. AI platforms are gaining prominence within broader data stacks, signaling a strategic pivot toward more integrated, AI-centric environments.
The research emphasizes that trust falters without proper business context, defined metrics, and deterministic rules layered with generative AI's creativity. Organizations must strengthen foundations through governed data, adaptable workflows, and rapid governance enhancements to move from experimentation to scalable impact.
"AI adoption is accelerating fast," said Andy MacMillan, CEO of Alteryx. "Our research shows that compared to a year ago, two-thirds of business and IT leaders are using AI more in their roles. We're also seeing AI move closer to individual departments. Over the next three years, leaders expect responsibility for AI workflows to shift to specific lines of business, rising from 22% today to 33% by 2028. The most advanced organizations are doubling down on improving data quality and integrating AI across their operations."
By focusing on trustworthy data foundations and explainable AI integration, enterprises can bridge the ambition-to-impact gap and realize sustainable value from their AI initiatives.
About Alteryx
Alteryx is a leading AI-ready data and analytics company that powers actionable insights to help organizations drive smarter, faster decisions with AI-ready data. More than 8,000 customers around the world rely on Alteryx to automate analytics, improve revenue performance, manage costs, and mitigate risk across their businesses.
TechIntelPro empowers B2B technology decision-makers with the latest industry trends, deep insights, leadership perspectives and actionable intelligence to drive both organizational and professional milestones—and thrive on the tech pulse.