Alteryx CEO: Building Trust in AI for Enterprise Value

April 3, 2026

TL;DR

Fewer than one in four AI pilots make it into production, hindered by trust, legacy systems, data silos, and data stack gaps.
AI deployment often fails when using raw data without proper business context, leading to inaccuracies and eroding trust.
Building trust in AI requires transparency, knowing what data and rules were used, and the ability to adjust them.
Embedded governance, clear definitions, shared metrics, and clear ownership are crucial for data governance.
No-code, drag-and-drop tools empower business users to build AI workflows with their existing business logic, improving accessibility.
Decentralizing AI workflows to lines of business offers advantages but requires governance to prevent duplicated logic and conflicting models.
Generative AI becomes more reliable when grounded in structured, trustworthy data and combined with deterministic workflows.
AI investments deliver value when tied to clear business outcomes and embedded into day-to-day operations.
Companies achieving the greatest AI returns embed it into operations, use high-quality data, and involve both IT and business teams.

Continue reading the original article