AIDB AI Pulse Survey Results · Jan - March ’26

AI value is shifting from efficiency to opportunity.

Aggregated insights from the AI Daily Brief audience - the number 1 podcast on enterprise AI.

Take the April Survey
This Month's Findings

After adoption comes delegation:

In a cohort where regular AI use is already assumed, the useful signal is not adoption but maturation: value rotates toward new capabilities, delegated workflows rise, and AI takes up more of the workweek.

Indicator
Jan
Feb
Mar
Change
Opportunity AI·Rising Signal

Making new work possible. Workflows, analyses, and outputs that did not exist before.

Name new capabilities as their primary AI benefit21.9%26.0%29.0%+7.1
Use AI in an automated or agentic mode55.8%62.4%68.5%+12.7
Work 10+ hours per week through AI43.6%47.4%51.6%+8.0
Efficiency AI·Losing Ground

Doing known work faster. A baseline condition for this cohort, no longer a primary benefit.

Name time saving as their primary AI benefit19.7%14.2%12.7%-7.0
Use AI in an assisted-only mode (no automation, no agents)44.2%37.6%31.5%-12.7
Monthly Detail

Three months, one direction.

Switch between months to compare the response cohort, value mix, and field notes from the AI Daily Brief audience.

March 2026

Opportunity AI becomes more visible.

March shows the clearest shift in work patterns: more delegated workflows, more work time routed through AI, and more value framed as new capabilities rather than simple time savings.

Responses
473
New capabilities
29.0%
Automated / agentic
68.5%
10+ hours / week
51.6%
Primary AI Benefit

Share of respondents who named each as their primary AI benefit. Single choice per respondent.

Increased output / throughput37.6%
New capabilities29.0%
Time saving12.7%
Quality improvement10.1%
Improved decision making9.1%
Increased revenue0.6%
How They Used AI

Share who used AI in each mode this month. Multi-select - the same respondent can appear in more than one row.

Assisted83.9%
Automated56.4%
Agentic46.9%
Automated or agentic68.5%
Assisted only31.5%
Use Case Gap Analysis: What People Do vs What Delivers Value

Each AI task, side by side: how often it is done vs. how often it tops the value list. A positive gap means it is valued more than done; a negative gap means it is done more than valued. Sorted by gap size.

Most Common AI UseHighest Value AI Use
Brainstorming & ideation-4.0 gap
9.9%
5.9%
Strategic planning+2.3 gap
9.3%
11.6%
Learning & skill development+1.5 gap
5.3%
6.8%
Data analysis+0.9 gap
4.2%
5.1%
Coding-0.8 gap
35.3%
34.5%
Writing & editing+0.8 gap
8.7%
9.5%
Research & analysis-0.6 gap
18.4%
17.8%
Creative & design+0.4 gap
3.4%
3.8%
Biggest Limiter on AI Use

Share who cited each as the single biggest thing limiting their AI use this month.

Nothing - I'm using it as much as I want30.0%
Time to learn20.3%
Policy or approval barriers15.2%
Skill gap - not sure how to use it effectively14.4%
Tool access - don't have the tools I need12.5%
Use case gap - not sure what to use it for7.2%
Don't see enough value0.4%
What People Built

Share of optional free-text responses mentioning each theme.

Coding / app building45.8%
Other / unclear23.1%
Writing / content / comms18.1%
Agents / automation / workflows18.1%
Strategy / product / business13.4%
Learning / coaching11.1%
Field Notes

A handful of optional free-text responses from this month's cohort.

Coding / app building“I built a multi-module PR assistant that can help with a lot of writing our team does.”
Coding / app building“Claude Code helped me take API documentation and turn it into a live GitHub MCP server.”
Coding / app building“Realized a completely new way to manage websites rather than conventional hosting → WordPress.”
Coding / app building“Used Claude Code to develop individual client websites based on a previously created Skill. The website was beautiful and more functional than I even asked for.”
3.55
Avg models selected
80.5%
3+ models selected
73.2%
Vibe coding this month
60.0%
Built with agent tools
Appendix
Same respondents, all three months
Repeat n = 149
JAN
Auto / agentic
63.9%
10+ hrs
47.2%
New capability
23.6%
FEB
Auto / agentic
61.1%
10+ hrs
50.0%
New capability
33.3%
MAR
Auto / agentic
80.6%
10+ hrs
62.5%
New capability
37.5%
Feb → Mar movement
Repeat respondents only
Repeat n
149
Moved up hours tier
28.2%
Newly automated
28.9%
Newly agentic
19.5%

Directional support - the broad monthly trend and the repeat-respondent trend point in the same direction.

Methodology
Source & caveats
  • AIDB Pulse surveys an AI-forward audience of daily AI-podcast listeners - read results as a post-adoption signal, not a general-market benchmark.
  • Survey exports dated May 6, 2026. Response counts: Jan 590 · Feb 508 · Mar 473.
  • February and March agent-tool questions are not directly comparable; wording changed.
  • Open-text themes are directional keyword classifications, not audited population estimates.
  • Provider / model data is supporting context; analysis centers value and work-mode changes.
April Survey · Open Now

Add your signal to the April 2026 Pulse.

Contribute to the signal and get results before anybody else.
Five minutes is all it takes.

Take the April Survey