For small independent healthcare practices, the main barriers to using new AI tech are time pressure, limited infrastructure and lack of clear guidance, not a lack of interest. Studies of private occupational therapists show that insufficient knowledge, time limitations and funding are among the top obstacles to integrating new AI technologies into practice.

Healthcare more broadly also struggles with poor usability of AI tools, patchy integration with existing records, and a lack of standardised guidelines, which makes every adoption decision feel risky. This combination means most owners are stuck between “I know I should be doing something with AI” and “I don’t have a spare day to even work out where to start.”  Sounds familiar?

Mindset shifts that make AI manageable

A helpful shift is to treat AI as a set of targeted workflow aids, not a revolution you must master in one go. Evidence from healthcare AI implementations shows that organisations get the best results when they embed AI into existing processes (documentation, scheduling, billing) instead of adding standalone “extra” systems. It is also realistic for smaller providers to adopt AI in a modular, subscription-based way, focusing on a few specific use cases that can show measurable time savings within months. Thinking in terms of “small, safe experiments” rather than permanent platform choices lowers the emotional pressure and decision fatigue.

From chatting with Qunote, one of the main industry standard patient record management systems for OTs and Case Managers, they are working on their version of integrating AI into their system.

A simple framework: clarify, choose, contain

Owners can use a three-step framework to cut through the noise:

  1. Clarify your top 2–3 pain points Common high-impact areas in OT practices include documentation/admin load, scheduling and communication, and generating therapy/education materials in accessible formats. Before looking at products, write one sentence per problem, e.g. “I spend at least an hour each evening writing up notes”.
  2. Choose narrow use cases, not platforms Healthcare organisations that see strong ROI from AI typically pick specific, measurable use cases (e.g. automating new enquiry forms, summarising clinical notes, or invoice generation) rather than buying broad “AI platforms” first. For a small OT practice, that might mean: AI-assisted report drafting from bullet-point notes; AI-powered scheduling suggestions inside your existing practice management system; or AI support for creating client-friendly information sheets.
  3. Contain the experiment Start with a 6–8 week pilot with one tool and one workflow, with clear success criteria such as “reduce average report-writing time by 30% without reducing quality.” Use simple governance: document what data you will and won’t put into the tool (no personal information), how you will check outputs, and who is responsible for oversight, in line with emerging recommendations for AI governance in healthcare.

Finding time: practical tactics for time-poor owners

Instead of “finding a spare day,” owners can carve out small, recurring slots and delegate parts of the learning process.

  • Create a protected “innovation hour” once a week Short, regular blocks are more realistic than rare full days; even larger health systems are advised to build ongoing, iterative AI programs rather than one-off projects. Use that hour only for: watching one tutorial, testing one feature on dummy data, or reviewing pilot metrics—not for email or routine admin.
  • Delegate research and first drafts Literature on OT technology adoption highlights that lack of structured guidance and training is a major barrier; having someone in-house act as an “AI Champion” can improve preparedness and confidence. Shortlist 2–3 tools per use case, gather basic comparisons (cost, data protection, integration) and bring you a one-page summary to decide from.
  • Integrate learning into existing meetings Use a portion of monthly team meetings for a quick “AI in practice” slot where someone demos a small workflow improvement (e.g. an AI-assisted template for SOAP notes). This shared learning builds team competence which reduces the sense that owners must carry all the knowledge themselves.

If you’re interested, we have an AI Guide for Occupational Therapy Owners to read, come along to Tracey’s AI Webinars for Healthcare Businesses to get your Free copy.