Key Takeaways
- Paylocity's AI Assistant has answered over 1.2 million questions for organizations that properly enabled it, but most implementations skip the configuration and training needed for adoption
- AI features are often configured but never explained to users, leaving powerful capabilities like predictive workforce insights, sentiment analysis, and personalized recommendations unused
- The gap between having AI capabilities and using them creates operational problems: HR teams handle routine questions manually, managers make decisions without data, and retention risks go unnoticed
- Organizations that actively introduce and reinforce AI capabilities see measurably higher adoption and lower HR support volume than those assuming users will discover features independently
- Align's optimization service connects AI capabilities to actual daily workflows through role-specific training and sustainable adoption processes
Most organizations implementing Paylocity get excited about its AI capabilities including the intelligent recommendations, predictive workforce insights, sentiment analysis. The demos are impressive. The promise is clear. But here's what we see across hundreds of implementations: months after go-live, those AI features sit largely unused. Not because they don't work, but because nobody showed users they existed, how to access them, or why they matter to their actual daily work. According to Paylocity's 2025 data, their AI Assistant has answered over 1.2 million questions for organizations that have properly enabled it, but getting to that level of adoption requires intentional configuration and training that most implementations skip.
What We See
After working with many organizations through HCM implementations, we see consistent patterns when it comes to AI adoption in Paylocity:
AI features are configured but never explained. The system is technically "on," but HR teams don't understand what the AI can actually do for them. Paylocity's AI capabilities include personalized recommendations, sentiment analysis, and predictive workforce insights, but if users don't know to look for schedule optimization suggestions or retention risk alerts, those capabilities deliver zero value.
Employees don't know they can ask questions. The AI Assistant provides contextual, personalized support directly within the platform, but if employees aren't taught that they can simply ask "How many vacation days do I have left?" instead of navigating through menus, they'll keep calling HR with basic questions.
Managers miss the predictive insights. The system can surface at-risk employees and recommend staffing levels based on historical data, but managers who were never trained on where to find these insights continue making decisions based on gut feeling rather than data.
The perception becomes "our system doesn't have that." When AI features aren't actively used, teams assume Paylocity lacks those capabilities not realizing they've been available the entire time, just never properly introduced.
Why This Matters Right Now
The gap between having AI capabilities and actually using them creates several operational problems:
HR teams continue handling routine questions that the AI Assistant could answer instantly, preventing them from focusing on strategic work. Managers make scheduling and staffing decisions without the predictive insights that could prevent coverage gaps or overtime expenses. Organizations miss early signals about employee retention risks because nobody's looking at the sentiment analysis data.
The business impact shows up in productivity, employee experience, and system ROI. When users don't leverage self-service AI capabilities, HR workload stays unnecessarily high. When predictive insights go unused, organizations react to problems instead of preventing them. When the AI remains invisible to end users, adoption stalls and employees continue working around the system rather than with it.
Five Questions to Assess Your AI Utilization
Ask yourself these questions about your current Paylocity implementation:
- Can your employees name one AI feature they use regularly? If most users can't point to a specific AI capability they interact with, the features are effectively invisible.
- Do your managers know where to find predictive workforce insights? If the answer is "I think we have that somewhere," those insights aren't influencing decisions.
- Is your HR team's support ticket volume dropping or staying flat? The AI Assistant handles employee questions, but only if employees know to use it instead of emailing HR.
- Are you seeing sentiment analysis data regularly? If leadership reviews aren't including AI-generated engagement insights, that capability isn't integrated into your operations.
- Do new hires get introduced to AI features during onboarding? If AI capabilities aren't part of your standard training, each new employee starts from zero adoption.
How Align's Paylocity Optimization Service Addresses This Gap
Align's optimization work exists specifically to close the gap between what Paylocity can do and what organizations are actually doing with it. This isn't about adding features, it's about activating the capabilities already sitting in your system.
Our approach focuses on practical adoption rather than technical configuration. We start by assessing which AI capabilities are most relevant to your workflows, then create role-specific training that shows users exactly when and why to use them. For HR teams, that might mean demonstrating how the AI Assistant handles common employee questions. For managers, it's showing where predictive scheduling recommendations appear and how to act on them.
What makes Align's approach different is that we're not teaching Paylocity features in isolation, we're connecting AI capabilities to the actual problems your teams face daily. When managers see that the system can predict their staffing needs, they start checking those recommendations. When employees learn they can ask the AI Assistant questions in natural language, they stop submitting tickets for basic information.
We also build sustainable adoption by embedding AI awareness into your ongoing processes. New hire onboarding includes AI capability introductions. Manager training includes where to find predictive insights. Monthly check-ins include reviewing which AI features are being used and which need more exposure.
The work is grounded in patterns we've seen across hundreds of implementations: organizations that actively introduce and reinforce AI capabilities see measurably higher adoption and lower HR support volume than those that assume users will discover features on their own.
The Value of Getting This Right
When AI capabilities move from "technically available" to "actively used," several things improve:
Employees get instant answers to routine questions instead of waiting for HR responses. Managers make better scheduling and staffing decisions because they're working with predictive data, not guesswork. HR teams spend less time on repetitive inquiries and more time on work that requires human judgment. Retention improves because sentiment analysis surfaces problems before they become resignations.
The system you've already paid for delivers the value it was designed to provide. Users trust the platform more because it's genuinely helping them work more efficiently. Adoption grows organically because people see their colleagues getting value from AI features.
Want to see which Paylocity AI capabilities your team is actually using versus which ones are sitting dormant?
We'll walk through your current configuration and show you exactly where adoption gaps exist and how to close them.
