Why AI for Allied Health Needs a Different Approach

Artificial intelligence (AI) has the potential to transform healthcare, but most of the investment and development in AI solutions has focused on hospitals, general practice, and specialist care. Allied health is often treated as a peripheral market, with AI tools designed primarily for medical settings and then adapted as an afterthought.

This approach does not reflect the reality of allied health practice. Clinics in physiotherapy, podiatry, osteopathy, exercise physiology and speech pathology operate under different financial, operational, and patient engagement models. If AI is going to provide real value to allied health, it must be designed with these unique challenges in mind.

AI in Allied Health Is Often an Afterthought

Most AI solutions in healthcare are developed with large medical institutions and primary care in mind. The focus is often on automating clinical documentation, supporting diagnosis, or improving hospital workflows, which does little to address the business and operational challenges faced by allied health clinics.

Allied health does not function in the same way as GP or specialist services. While medical professionals typically work within structured referral pathways and stable funding models, allied health clinics must attract and retain their own patients while managing complex funding arrangements.

Many AI tools fail to address these realities. They are often limited to basic administrative automation, without offering meaningful solutions for patient retention, financial management, or business growth. This leaves allied health professionals underserved and reliant on technology that was never truly designed for their needs.

The Importance of Patient Engagement in Allied Health

Unlike single-visit consultations, allied health treatments are often delivered over multiple sessions, making patient engagement a critical factor in both clinical outcomes and financial sustainability.

Patients frequently disengage from treatment due to perceived recovery, life commitments, or financial concerns, which can lead to suboptimal results and reduced clinic revenue. AI has the potential to bridge this gap, but only if it is used for more than just administrative support.

How AI Can Help

• Intelligent appointment follow-ups that predict when a patient may disengage and intervene accordingly.
• Progress tracking tools that provide clear, data-driven insights into a patient’s improvements, reinforcing the need to complete treatment.
• Personalised patient engagement strategies, using AI to tailor communication and reminders based on individual behaviours and treatment plans.

If AI is only used to streamline paperwork, it is missing the larger opportunity to enhance patient care and retention.

The Financial Realities of Allied Health

Financial sustainability in allied health differs significantly from many other areas of healthcare. Clinics operate under a mix of private fees, insurance claims, and government funding schemes, such as Medicare’s Chronic Disease Management (CDM) plans, the National Disability Insurance Scheme (NDIS), and WorkCover.

This creates greater complexity in revenue management compared to clinics that rely solely on direct billing or government rebates. Unlike bulk-billed GP services, allied health clinics often face fluctuating income due to cancellations, no-shows, and inconsistent patient attendance.

How AI Can Help

• Automated invoicing and claims management that simplifies compliance with funding bodies and reduces administrative burdens.
• AI-driven analytics to help clinics forecast revenue trends, adjust pricing models, and optimise scheduling for maximum efficiency.
• Intelligent payment systems that reduce late payments and automate follow-ups, ensuring better financial stability.

Many AI solutions for healthcare do not address these financial realities, which means allied health professionals are left using generic administrative tools rather than AI-driven solutions that actively improve financial performance.

Business Growth in Allied Health Requires a Different Strategy

Growth in allied health is not as straightforward as in some other areas of healthcare. Many GP and specialist clinics expand by adding more practitioners, often benefiting from existing referral networks that keep patient numbers stable.

Allied health clinics, however, must take a more proactive approach to attracting new patients. Even a well-established clinic cannot rely on referrals alone—strong local visibility, patient retention, and marketing all play a role in long-term success.

How AI Can Help

• AI-powered digital marketing tools that analyse local demand and help clinics improve their online presence.
• Referral optimisation systems that track and enhance relationships with GPs, specialists, and other healthcare providers.
• Predictive analytics to help clinics identify high-demand services and adjust their offerings accordingly.

Most AI tools in healthcare do not prioritise growth strategies, yet for allied health clinics, growth is essential. AI must evolve beyond administrative automation and provide solutions that support long-term business success.

AI Must Be Designed for Allied Health - Not Adapted from Other Models

The slow adoption of AI in allied health is not due to a lack of interest or potential. Rather, it is because most AI solutions were never designed for this sector in the first place.

Too often, allied health is treated as a niche market, where AI features are merely extensions of broader healthcare solutions. This underestimates the size and complexity of allied health and limits the value AI can provide.

For AI to be truly effective in allied health, it must:

• Extend beyond administrative automation to include patient engagement, business growth, and financial optimisation.
• Recognise the unique funding and billing models in allied health and provide solutions to simplify compliance.
• Support clinics in attracting and retaining patients, rather than assuming they will always have a steady stream of referrals.

Clinics that take a strategic approach to AI adoption - focusing on patient retention, operational efficiency, and business development - will be best positioned to thrive in an increasingly digital healthcare environment.

What Are Your Thoughts?

Have you implemented AI in your clinic? Do you feel that the available solutions are designed for allied health, or do they feel like adapted versions of tools built for other healthcare sectors?

Share your experiences in the comments - I would love to hear your perspective.