Behaviture shows why AI value is not spreading—across tool fit, workflows, policy, training, trust, and role needs—then helps you decide what to change.
One campaign · Up to 25 responses · No credit card required
Ready to fix a specific adoption problem? Plan an improvement pilot →Licenses are active. Workflow value is uneven.
Priority action Clarify approved data use, expand spreadsheet-analysis coverage, and publish two finance-specific workflow examples.
What success looks like In the next pulse, Finance reports clearer safe-use rules and stronger approved-tool fit.
AI access can create an “enablement illusion” when leaders mistake licenses and activity for workforce capability.
Gartner predicts that by 2027, half of enterprises without a comprehensive AI people strategy will lose top AI talent to competitors that prioritize workforce enablement. Its research points to tool experience, targeted support, psychological safety, and diverse real-world use as important parts of workforce AI performance.
Vendor analytics are useful for seats and activity. Behaviture adds the cross-tool workforce context: whether approved tools fit the task, whether employees know how to work safely, and what will unlock more value.
Employees may have AI access but still lack relevant examples, confidence, manager support, workflow integration, or practical training. Behaviture separates activity from useful adoption.
Adoption · Value · Confidence · Training readinessEmployees may need capabilities that approved tools do not provide, are not licensed for their role, or cannot safely use with required data. Behaviture treats that pressure as a signal to investigate—not an automatic rule violation.
Capability demand · Approved coverage · Tool fitA score does not improve adoption. Behaviture helps turn the strongest tool, workflow, policy, and training findings into a short list of owned actions with a follow-up measure.
Finding · Owner · Target date · Outcome measureThe first pulse is a baseline, not the finish line. Behaviture converts evidence into a small set of owned changes and gives the next pulse a job: show what moved.
Add departments, role groups, approved tools, capability coverage, and the privacy settings that apply to the campaign. Enable optional modules only when they fit the organization’s goals.
A pulse grounded in the customer’s real tool and role environment.Employees complete a short mobile-friendly survey with privacy explained before the first question. Each participant receives a private, non-punitive coaching report.
Useful participation—not data extraction.Connect the strongest privacy-qualified findings to practical tool, workflow, policy, or training changes, each with an owner, target date, and success measure.
A focused plan the organization can actually deliver.Run a follow-up pulse after the improvements to see which adoption conditions moved, what still blocks value, and which action should come next.
Evidence of progress—not a one-time maturity grade.Each respondent receives a private interpretation of strengths, blockers, responsible-use habits, approved options, and practical next steps. Individual reports are not available to company administrators.
Leaders see privacy-qualified patterns across the organization, departments, or role groups—never individual employee scores or answers.
The survey and private employee report are available in all eight supported languages, with deterministic scores preserved across every translation.
The free snapshot provides a focused organization-level result and private employee mini-reports. Paid pulses provide richer, more detailed reporting for decisions that need more evidence.
Paid reporting can addWhy this matters Employees answer honestly when the assessment gives them something back. That is what makes the aggregate pattern worth acting on.
Whether teams use Copilot, ChatGPT, Gemini, Claude, or specialized tools, Behaviture connects reported value and workflow demand with approved capability, policy, confidence, and trust—then shows the specific gap a leader can act on.
Does AI improve speed, quality, or the range of work employees can perform?
Do approved tools work well enough for real employee tasks and permitted data?
Can employees translate policy into a safe decision in a real workflow?
Can people ask questions, disclose mistakes, and raise unmet needs early?
Which roles appear to have more AI-suitable work than current adoption conditions support?
Which high-demand capabilities lack a safe, usable, approved path?
Where might unmet workflow demand, tool limitations, or unclear rules push employees toward personal tools?
Employees in Finance report strong AI value and high demand for spreadsheet analysis and sourced research. Approved coverage is weaker for those capabilities, while policy clarity is low. The pattern suggests an enablement and tool-coverage problem—not a lack of interest.
Recommended actionIllustrative sample data. Role opportunity and capability gaps are decision-support estimates, not employee evaluations.
Optional modules extend the same deterministic scoring and privacy rules as the core pulse. Nothing you add changes who can see an individual answer: no one.
Understand AI value, adoption, confidence, responsible use, policy clarity, psychological safety, approved-tool fit, capability demand, and external-tool pressure.
Add deeper role, task, and capability context to identify estimated Job-Based AI Adoption Gaps and approved capability mismatches.
Decision support—not a job evaluation or employee ranking tool.Support role-aware AI literacy planning, internal evidence collection, approved-tool documentation, and governance review.
Readiness and documentation support—not legal advice or certification.Identify candidate workflows, desired autonomy, oversight gaps, and practical boundaries for controlled agentic pilots.
Assessment and planning—not live agent monitoring or control enforcement.Employees will not provide useful signals if they believe the assessment is a hidden performance review. Behaviture separates campaign administration from diagnostic reporting and limits organization views to qualifying groups.
Founder Tim Van Prooyen spent more than fifteen years building and supporting complex enterprise software, data, forecasting, and operational systems—including software used in real-time electric-grid operations and wholesale energy markets. During his MBA at the Prague University of Economics and Business, he studied the behavioral side of workplace AI adoption.
His defended master’s thesis, Shadow AI in the Workplace: Balancing Productivity Gains and Organizational Risk, examined how usefulness, tool disparity, policy awareness, risk perception, and employee confidence shape the use of unofficial AI tools. AI Adoption Pulse turns that research question into a privacy-first product focused on enablement rather than punishment.
About Behaviture and the founder →Use the free snapshot to surface an organization-level signal. Employees receive private mini-reports, and the organization receives a focused aggregate result. No credit card is required.
For a larger rollout, a structured paid pilot adds richer reporting, a findings workshop, one to three owned interventions, and follow-up measurement—plus role and department comparisons when privacy thresholds are met.
Simple guided setup · No employee accounts · Privacy-first by design