From Pilot to Practice: 10 Keys to AI Adoption in Behavioral Health

Artificial intelligence is no longer a novelty, mystery or curiosity in behavioral health and human services—it’s rapidly become a necessity. And with good reason. With rising documentation demands, workforce burnout and complex client needs, organizations are exploring AI tools to ease the load on hard working staff. But merely subscribing to an AI tool is not the same as adopting a meaningful AI strategy.

The difference lies in execution, mindset and trust. Today we’ll be exploring one such example. 

At Netsmart, we’ve supported providers from Catholic Charities of Baltimore to the North Dakota Department of Health and Human Services (ND DHHS) as they moved from pilot programs to enterprise adoption. Here’s what we’ve learned about what separates successful adopters from those who stall out. 

 

1. Start with Why: What Problem Are You Trying to Solve? 

Before selecting an automation tool or bothering to schedule AI demos, clarify your purpose. AI is most effective when it’s tied directly to specific pain points like staff burnout, inefficient documentation or high turnover. In the case of Catholic Charities, their AI journey began with a simple question: “Where are we hurting?”  

For ND DHHS, documentation burden and workforce retention were key, clear motivators with end goals in mind. 

 

2. Get Staff Involved Early and Often 

Successful adoption depends on more than a thumbs up from a CTO. It requires frontline participation. Catholic Charities brought staff into the conversation from Day One. This simple but significant act of inclusion helped build organization-wide trust and ownership. ND DHHS trained internal “cheerleaders” to share wins and reduce skepticism—essential in rural areas where resistance to change can be high. 

 

3. Choose Practical Use Cases Over Shiny Features 

Behavioral health teams need real-world applications that save time and improve care. Anything less is little more than a toy. Leading use cases include mobile documentation, task automation and clinical notetaking ND DHHS focused on mobile tools that worked offline—a critical feature for field staff in remote regions. 

 

4. Educate Teams and Replace Fear with Facts 

A common misconception is that AI will replace jobs. Far from it. The truth is: it replaces tasks.  
 
Catholic Charities spent time upfront helping staff understand how AI would support, not supplant, their work. Quick-text features and faster access to notes made an immediate impact. According to the National Council for Mental Wellbeing, 60% of behavioral health organizations report staff burnout as a top concern—education is essential to address those fears head-on. (source) 

 

5. Choose a Partner, Not Just a Product 

Generic AI tools often fall short in behavioral health. The best vendors offer tailored support, mobile-first design and offline capabilities. Bells, for example, includes embedded coaching tools that save time even during implementation—a differentiator for organizations with limited admin capacity. 

 

6. Empower Super Users to Champion Change 

Internal advocates can make or break AI adoption. Catholic Charities leaned on early adopters to help onboard others. ND DHHS spotlighted user stories to normalize new workflows. These champions help turn AI from a tech initiative into a team win. 

 

7. Make Integration Seamless, Not Siloed 

It’s important for AI to be as deeply integrated with your existing EHR and workflows as possible.  It improves data accuracy, allows for the free flow of information, preserves context and ensures teams actually use the tool long term. If it’s clunky, it won’t stick. 

 

8. Train By Role and Follow Through with Support 

One-size-fits-all training doesn’t work. Catholic Charities used role-based onboarding so every user could see personal benefits. ND DHHS stressed the need for ongoing support, especially in geographically dispersed teams. Training should be persistent, not just an event. 

 

9. Track Meaningful Metrics, Not Just Usage Stats 

To sustain momentum, it’s important to demonstrate measurable value. Keep tabs on your total time saved on documentation, reduced no-show rates, faster intakes and improved staff satisfaction. Metrics like these help teams see progress and justify continued investment. 

 

10. Listen, Adapt and Iterate 

Even the best AI tools need refinement. Catholic Charities and ND DHHS both emphasized the value of feedback loops. When teams see their input being used to improve the system, trust grows and adoption follows. 

 

Technology Alone Doesn’t Deliver Transformation 

AI isn’t a silver bullet but with the right strategy, it can be a powerful ally. As Catholic Charities and ND DHHS have shown, the most successful adopters lead with people, purpose and partnership. Behavioral health is deeply human work. When AI respects that and fits the way people actually work, it doesn’t just get adopted, it makes a lasting impact.