What AI Already Does in Orthodontic Planning, and What It Still Needs From You

What the treatment planning process looks like from the inside.

Today, we’re not discussing the use of artificial intelligence in orthodontic software. AI is already there and has been for a long time. But which parts of the planning process has technology actually taken over, and which parts still depend on the orthodontist’s judgment? Debates about whether the profession is under threat are unnecessary, so we’ll try to explore how it will evolve.

Let’s start by saying that most skeptics' expectations regarding AI have not been met - the technology is already performing quite well. Take, for example, the segmentation of teeth and soft tissues, the assessment of roots and surrounding bone, and the identification of landmarks - these tasks used to take the first few hours of work on each case, but now they’re mostly automated. It now takes about 2 minutes to complete a task that used to require 4 to 5 hours of work from a technician - outlining what they believed to be a crown, a root, or the gum line. The result is consistent and does not depend on which technician was assigned to the case that day.

In clinics that use artificial intelligence-based software, this single change has transformed the approach to staffing, planning, pricing, and turnaround times. Tools that visualize the forces and movement of teeth give the dentist a clearer understanding of the mechanics underlying the proposed treatment plan than a static setup could ever provide.

Everything I’ve described above is far from the most complex part of orthodontics, which is precisely why these processes can be automated first. After all, the repetitive, mechanical work of reconstructing anatomy based on scans has never been a measure of expertise in this specialty. I would say that these are overhead costs, and eliminating them is beneficial - just as the automation of model trimming or manual measurements has proven beneficial. Such automation frees up the orthodontist, allowing them to focus on complex decisions that require professional training and specialized knowledge.

Artificial intelligence is very good at calculating a final position that looks correct in 3D. Unfortunately, however, the model cannot determine whether that position is clinically achievable for the specific patient sitting in front of you. There are a number of factors standing between an idealized scheme and a feasible plan: the proximity of the roots to one another, the boundaries of the cortical bone layer, the condition of the periodontal support, and the load that the surrounding bone can withstand. If the treatment plan does not take these limitations into account, it remains merely a visualization.

The same applies to the sequence of movements. An AI program can suggest a route from start to finish, but it cannot decide how to load the teeth, when to move on to the next stage, or what compromises to make in a specific case.

Basically, most discussions about AI are driven by anxiety that automated planning will turn orthodontic work into a mass-market commodity and will not deliver the expected quality. This concern is understandable, but it’s misdirected. Automation does indeed turn the technical aspects of the work - not the decisions themselves - into a routine process. This work was never truly clinical to begin with.

Actually, I believe that doctors should embrace the use of AI and influence the future of the profession. AI systems learn from clinical cases and from the experience of the specialists who train them. If the people training the models focus primarily on volume and speed, the system will learn to generate treatment plans that are essentially mediocre - and most likely, it is precisely these plans that will eventually become the standard. A model trained on average-quality work will confidently reproduce that average-quality work.

This is why it is so important to be involved in the algorithm training process right now. Orthodontists who fine-tune these systems - by providing them with well-documented clinical cases and insisting that treatment plans prioritize biological principles over geometric ones - are the ones who determine what the next generation of planning tools will consider the norm.

Specialists who stay on the sidelines of this process do not slow it down. They simply leave the training to those who are actively involved, and the tools that each practice ultimately adopts will reflect the priorities of that smaller group. The same instinct that compels an experienced doctor to invest in teaching their residents should compel them to be cautious about how they train AI: if left to learn on its own, it will absorb whatever information is provided and make up the rest.

In conclusion, I’d like to highlight that the work that truly safeguards the value of the specialty is already available today, and it’s more routine than groundbreaking. AI-based tools are already good enough to use, but they’re still far from ideal. They require fine-tuning based on real-world cases. In my view, what treatment planning software will look like in five years - and how the specialty will interact with it - depends on how orthodontists perceive working with AI: as part of their professional skills, or as something that someone else should do for them.

This materials was published in Dentaltown: https://www.dentaltown.com/channel/post/26193/what-ai-already-does-in-orthodontic-planning-and-what-it-still-needs-from-you