What 500 Business Users Told Us About AI-Powered Analytics

We surveyed 500 business users across roles (executives, managers, analysts, engineers) about their experience with AI analytics tools. The results reveal what users want, what frustrates them, and where the industry is heading.

Methodology

The survey was conducted in Q1 2026 with 500 respondents from companies with 10-5,000 employees. Respondents were sourced from our user base and partner networks. Roles included: C-suite (12%), VP/Director (23%), Manager (31%), Individual Contributor (34%).

Key Findings

Finding 1: 73% cannot get answers from their current BI tools without help

The most striking finding: nearly three-quarters of business users cannot independently use their company's analytics tools. They rely on analysts, data teams, or IT to answer data questions.

The primary barriers cited were:

• SQL knowledge required (68%)
• Complex query builder interfaces (54%)
• Data scattered across multiple tools (47%)
• Lack of documentation on metrics and definitions (39%)

Finding 2: Natural language is the most requested feature

When asked "What feature would make you use analytics tools more?", the top answer was "Ask questions in plain English" (62%). This was 2x more popular than "better dashboards" (31%) and 3x more popular than "more integrations" (21%).

Finding 3: Trust is the #1 barrier to AI analytics adoption

Among users who had tried AI analytics tools, 67% cited trust as their primary concern:

• "I don't trust the AI's numbers without seeing the underlying query" (45%)
• "I'm worried about data privacy" (38%)
• "The AI sometimes makes confident but wrong statements" (34%)

Finding 4: Speed of answer matters more than depth

When asked to choose between "a detailed 10-page report in 2 hours" and "a 3-sentence answer in 10 seconds," 78% chose the fast answer. Users want quick directional signals, not comprehensive analyses, for most questions.

Finding 5: Integration breadth drives adoption

The tools that achieved the highest adoption (daily use by >50% of team) were those that connected to 5+ data sources. Tools that only connected to databases had 3x lower adoption than those that also connected to Slack, email, and project management tools.

What This Means for Skopx

These findings directly informed our product decisions:

1. Natural language first: Every interaction in Skopx starts with plain English, not a query builder.
2. Trust through transparency: Tool call expansion, SQL visibility, and citation on every answer.
3. Speed over depth: Default to concise answers with the option to drill deeper.
4. Integration breadth: 47+ connected tools, not just databases.
5. Self-service for everyone: No SQL knowledge required for any feature.

The Full Report

The complete survey results, including methodology, demographic breakdowns, and cross-tabulations, are available in our full report. Contact research@skopx.com to request access.