AI has become one of the most discussed topics in fertility. Every conference has sessions dedicated to AI. Many software vendors are launching AI features. Every clinic leadership team is beginning to ask the same question: What should our AI strategy be?
We see that many clinics are immediately jumping to the second half of the conversation. They start by evaluating tools. Should we implement an AI scribe? Can AI support patient communication? Should we automate parts of administration?
This is the first problem. These are reasonable questions, but they are just not strategic questions. An AI strategy is not a list of AI tools.
It is a view on how AI is likely to change your organisation over the next five years and how you intend to respond to it. Most fertility clinics have not yet had that discussion.
The fertility industry is facing a combination of challenges that make AI particularly relevant. Patient demand continues to increase in many markets. Staffing remains difficult across clinical, nursing and operational functions. Administrative workloads continue to grow. At the same time, many clinics are under increasing pressure to improve efficiency without compromising patient experience or clinical outcomes. AI will inevitably become part of the answer.
The question is where. When leadership teams discuss AI, I believe there are four areas they should be thinking about.
The first is productivity
This is where most conversations start today. How can AI help clinicians spend less time documenting? How can it reduce repetitive administrative work? How can it support communication with patients? How can it help staff spend more time on activities that create value and less time on activities that do not?
These opportunities are real, and many fertility clinics will see meaningful benefits from them. However, productivity is only the first layer.
The second is operational intelligence.
Most fertility clinics generate enormous amounts of information every day. Patient enquiries, consultations, diagnostics, treatment cycles, laboratory activities, financial transactions and operational workflows all produce data. Historically, much of this information has been used for reporting. Increasingly, AI will allow organisations to use it to support decision-making.
Why are conversion rates different between locations? Why are treatment cancellations increasing? Which operational bottlenecks are affecting patient flow? Which staffing models are performing best? These are not questions that leadership teams want answered once a quarter. Increasingly, they will want answers continuously.
The third is patient experience
The expectations patients bring into fertility care are changing rapidly. Patients increasingly expect the same level of accessibility, communication and responsiveness that they experience in other parts of their lives. AI has the potential to support clinics in meeting those expectations while maintaining high-quality care. Not by replacing clinical judgement or human interaction, but by making both more accessible and efficient.
The fourth is clinical intelligence
Fertility clinics generate an extraordinary amount of clinical data, yet much of that information remains underutilised outside individual patient care. As AI capabilities continue to develop, clinics will increasingly have opportunities to analyse treatment pathways, patient cohorts and outcomes at a scale that has historically been difficult to achieve. Which protocols are producing the strongest outcomes for specific patient groups? Where are patients dropping out of treatment pathways? Which interventions appear to correlate with improved outcomes? How do results differ across clinicians, locations or demographics?
These are not questions that AI should answer independently. In our opinion they remain clinical questions that require clinical judgement. However, AI has the potential to help organisations identify patterns, surface insights and support more informed decision-making. Over time, this may become one of the most significant opportunities for fertility clinics. Not because AI replaces clinical expertise, but because it allows organisations to learn more effectively from the thousands of treatment journeys that already exist within their own data.
The fifth is perhaps the most important. Competitive positioning.
Every fertility clinic should be asking itself a simple question. If AI continues to improve at its current pace, what will our clinic look like in three years? What will our staffing model look like? What will patients expect? What will our competitors be able to offer? What parts of our operation could be fundamentally different?
These are leadership questions, not technology questions. The mistake many organisations make is treating AI as a software discussion. In reality, AI is increasingly becoming a strategic discussion.
The clinics that benefit most from AI are unlikely to be those that implement the largest number of tools. They will be the organisations that understand where AI can create meaningful leverage across their business and that make deliberate decisions about how they want to use it. The fertility industry has spent the past decade focused on growth, expansion and consolidation. The next phase may be defined by something different.
AI will not determine which clinics or networks succeed. But the clinics that develop a clear strategy for how they use it are likely to have a significant advantage over those that simply react to it.
The conversation is no longer whether AI will become part of fertility care. The conversation is whether clinics are actively shaping how that future will look for their organisation.
