Transforming the Level of Care
New Technologies in Dental Practice
By Kristen Mickelwait
Today, the field of dentistry stands at a remarkable inflection point. From AI-powered diagnostic imaging to 3D printing that enables same-day treatments, novel technologies are fundamentally reshaping what is possible in oral health care and paving the way for graduates of the Arthur A. Dugoni School of Dentistry to perform at even higher levels in their practices.
Dr. Daniel Hammer ’11 is a leading expert—a board-certified oral and maxillofacial surgeon and fellow of the American College of Dentists—who speaks and publishes nationally and internationally on the integration of dentistry and reconstructive surgery with advanced technologies and techniques. He currently serves as program director of the Maxillofacial Restoration Program at the U.S. Naval Medical Center in San Diego, California, as well as vice chair of its Department of Oral and Maxillofacial Surgery.
Hammer says that in-house 3D printing and virtual surgical planning (VSP) have transformed his clinical workflow—making complex reconstruction faster, less expensive and often better for patients. “This ‘good, fast, cheap’ triad is increasingly achievable in modern biomedical and dental practices,” he says. “Improving upon the engineering credo that ‘you can only pick two,’ recent evidence and digital workflows show that you can increasingly get all three. This mirrors value in the healthcare field: better outcomes plus a faster pace while at a lower cost.”
Since 2011 and the birth of commercial 3D printing, there has been an enormous leap in technologies applicable to the dental field, Hammer says. Compare the early bulky, slow consumer printers to today’s reality, when you might find a 3D printing lab in someone’s home—that’s how accessible the technology has become.
The time and cost benefits of such new devices are dramatic. Traditional labs and outsourced workflows used to take three to six weeks, while current protocols can deliver 3D-printed teeth or guides within a day (often two to three hours after seeing the patient), with any remaining delays mostly from third-party hardware logistics. For example, a vendor model for a full-arch prosthesis might be 25% of the cost from a lab, while in-house printing could make the item for 1-2% of the lab fee.
“This shift toward new tech is due to several drivers,” he says. “Consumerism, economics and profit margins, public policy, even social media activities. But the ideal drivers continue to be patient outcomes and the high quality of novel products. This is linked to the concept of near-zero marginal cost— after fixed costs, each additional printed part is extremely inexpensive relative to hospital-scale expenses.” A legitimate, entry-level lab can be built for under $4,000, he notes, making adoption feasible in private practice, schools and hospitals.
Hammer simplifies the digital workflow framework into four basic steps:
Capture: CT/CBCT (DICOM) and dental surfaces (STL) via intraoral scans, scanned stone models or impressions (Hammer now prefers intraoral scanning for speed, accuracy and tolerance).
Design: Virtual surgical planning with engineers or on personal licensed software.
Print: Using different printing modalities such as liquid crystal display, fused deposition modeling, digital light processing and stereolithography, plus metPal printing like powder-bed fusion for titanium.
Process: Cleaning, curing and finishing with an alcohol bath, cure box, gingiva characterization and sealing to reduce porosity and colonization.
“The challenge is scaling these technologies and techniques as medical and dental healthcare deliveries continue to run adjacent to each other rather than integrated in most healthcare settings,” Hammer says. “We understand the predictable technology available and improved outcomes, but the healthcare delivery and economic engine are still being designed.”
The Human Must Always Be in Command
A good example of innovation in dental education can be found within the Arthur A. Dugoni School of Dentistry’s Graduate Orthodontic Program. Emerging technologies and artificial intelligence (AI) are incorporated into lectures, case discussions and clinical training throughout the curriculum.
Orthodontic residents are encouraged to think critically about where innovations originate, how different technologies compare and what roles researchers, clinicians and industry play in bringing innovative solutions to patient care. They learn to evaluate new tools through an evidence-based lens, considering their scientific support, limitations and potential clinical impact. Through this approach, residents develop the ability not only to use modern technologies, but also to thoughtfully assess and integrate them into orthodontic practice as the field continues to evolve.
Dr. Jonas Bianchi, associate professor and director of research in the Department of Orthodontics, agrees that the dental school’s graduates must become technologically proficient clinicians in an era of rapidly advancing digital dentistry and AI. But while AI plays an important role, he says, the school’s broader focus is on digital workflow integration, innovation, ethical responsibility and preparing future practitioners to critically evaluate—not blindly adopt—new technologies. Its curriculum includes many of the technologies and skillsets mentioned earlier by Hammer, including intraoral scanning, digital radiography and 3D imaging (CBCT), facial scanning and “digital twins”—a comprehensive digital version of the patient that enables advanced planning visualization.
“Technology should support clinicians,” he says, “but the human must always remain in command. This ‘human-in-the-loop’ framework is central to our philosophy—AI should never replace clinical judgment.” Bianchi is clear that artificial intelligence can be helpful in diagnosis or treatment planning, may flag issues such as caries or periodontal disease and might generate summaries or predictions. But the final decision must always be made by the clinician, an approach known as human in command (HIC).
Here are a few specific examples of technologies currently used in the orthodontic program:
Technology should support clinicians, but the human must always remain in command. This ‘human-in-the-loop’ framework is central to our philosophy—AI should never replace clinical judgment.
How the dental school trains students and residents to be technology proficient
- Digital workflow integration
- Data literacy
- Critical appraisal skills
- Evidence-based technology adoption
- Understanding limitations
(not black-box thinking) - Clinical relevance over novelty
- Responsible AI implementation
- AI as decision support,
not decision maker - Lifelong adaptive learning mindset
- Translational thinking
(bench to chairside)
The process for evaluating new technologies at the dental school
- Evidence-based validation (peer-reviewed data)
- Reliability and reproducibility
- Clinical relevance
- Outcome improvement
- Educational value
- Ethical oversight
- Data security/HIPAA compliance
- Bias assessment (AI tools)
- Cost-benefit analysis
- Pilot testing before full adoption
- Faculty consensus
Core themes that define the school’s approach
- Innovation with responsibility
- Digital integration across all disciplines
- AI literacy—not blind adoption
- Human in Command
- Validation before implementation
- Ethical and secure data usage
- Preparing students for
a competitive future
Examples of novel technologies used by the program:
- Fully digital orthodontic workflow
- 3D imaging integration
- AI-driven craniofacial analysis
- Automated American Board of Orthodontics Discrepancy Index and Objective Grading System tools
- Machine learning for asymmetry assessment
- NIH-supported AI research
- Clinical decision-support systems
- Predictive modeling
- Learning platforms with integrated AI
Innovation must always be patient-centered and grounded in humanism.
Training in Digital Orthodontic Workflows
Orthodontic residents gain hands-on experience with intraoral scanning and cone-beam computed tomography (CBCT) as core components of contemporary clinical practice. Through this training, they develop the ability to synthesize imaging data
to assess tooth alignment, jaw relationships and upper airway anatomy, ultimately applying these findings to diagnosis, treatment planning and custom appliance fabrication. These same digital models support downstream applications such as 3D printing of study casts and the in-house production of retainers and clear aligners.
Craniofacial Analysis Supported by Artificial Intelligence
Residents are introduced to emerging AI-driven technologies capable of evaluating craniofacial images to detect asymmetries and structural patterns that are challenging to quantify through conventional manual methods—a particularly valuable capability when working with orthognathic surgery patients. Because the manual identification of three-dimensional craniofacial landmarks is inherently time-intensive, AI-assisted localization enables residents to complete this process more efficiently while remaining under direct clinical supervision, freeing them to devote more attention to interpretive and planning responsibilities.
Automated Tools for Orthodontic Evaluation
Within research and academic settings, residents are also familiarized with automated orthodontic evaluation systems, including those designed to perform image segmentation for enhanced visualization of anatomical structures. Exposure to these technologies helps residents understand how AI and automation can contribute to clinical documentation, outcome assessment and quality review. Ongoing research in this area encompasses automated extraction of clinical notes, predictive modeling using 3-D datasets and tools aimed at visualizing treatment progression, evaluating skeletal maturation and enriching the overall treatment planning process.
Another tech advancement—particularly helpful in orthodontics—is remote monitoring, in which patients can scan their teeth at home using a smartphone app and scanning device. AI is then used to analyze movement, hygiene and risk of white spots or caries. Such innovation allows clinicians to monitor their patients between visits.
For professional clinicians wondering about how and when to incorporate these new tools into their practices, Bianchi says there are three types of technology adopters: early adopters, mid-adopters and late adopters. His advice: “Don’t be the very first, and don’t be the very last. Try to get the technology while it’s still new but wait a bit to see how well it works. Because if the tool is validated and it saves clinical time, you don’t want to be lagging behind.”
Bianchi’s view is, “AI will never replace dentists or orthodontists. But dentists who understand and responsibly use digital technology will replace those who do not.”
A Rigorous Assessment Process
To assess upcoming technologies and their applications, the dental school has a Center for Innovation and Translation (CIT) and an Educational and Information Technology Advisory Committee.CIT engages in partnerships with new companies seeking product validation. In addition, in January 2026, the school held the first-ever AI in Oral Health Care Symposium, which brought together industry partners, clinicians, researchers and educators to discuss the responsible, evidence-based use of AI in oral health and integrated medical–dental care. The program focused on what it takes to move promising technologies into real-world practice, including clinical workflow integration, validation, guidelines for ethical use, implementation challenges and workforce readiness.
In order to train its students and faculty in responsible AI use and policy development, the dental school has developed a Generative AI Responsible Usage Guide. This guide outlines appropriate and ethical uses of AI in education, provides recommendations for course directors, allows individual instructors to establish course-specific AI policies and aligns with broader institutional guidelines being developed by the university. The goal is not just exposure to AI tools, but literacy—helping students understand what AI is, how it works and where its limitations lie.
According to Dr. Sinky Zheng, director of educational innovation and assessment and professor of learning science, the dental school integrates several contemporary platforms to support in-person and online education, including Nearpod, SoftChalk and ThingLink. “Now, with AI becoming more integrated into higher education, these learning platforms are also adding AI features to further support teaching and learning at our school,” she says.
For the educational technology she oversees, Zheng conducts initial research to explore the tool’s capabilities and does a literature review to see if there is any reported evidence of the effectiveness of the technology. “The next step is to pilot the tool with faculty leaders,” Zheng says. “The outcomes from these pilots guide our decision making on whether this is a valuable tool for our program. We look at how it can enhance teaching and learning, how it can help address educational challenges and how easy it will be for faculty and students to learn. We also work with IT to ensure that data privacy and security protection are sound.”
In the context of dental education, Hammer says, “A central question for educators is what students should be taught now—terminology, exposure, workflows and resources—so they can lead the next 10 years of patient-care advancement. As new tools and frontiers emerge—think face transplants or bio-printed bone with stem cells—innovation must always be patient-centered and grounded in humanism.”
Such ideas and advances are not distant promises—they’re tools already in the hands of forward-thinking clinicians and educators today. As dentistry looks ahead, the integration of robotics, teledentistry and machine learning into everyday practice signals not just an evolution, but a revolution in the way that dentists and specialists teach, learn and deliver quality dental care.