Next Gen Dental Technology - Part 1

We were delighted with the positive response to our first issue - thank you very much for your feedback. Once again, we are staying true to our promise: direct, honest and without marketing blah-blah.

We are focussing on a hot topic: artificial intelligence (AI) in dental technology. Specialist journalist Annett Kieschnick is once again supporting us as a guest author with her expert view of the industry. There is often a world of difference between hype and concrete benefits - we take a look at what is really possible today and what the future may bring. The topic is so multifaceted that we are covering it in two parts.

In this issue, we look at the current status and the challenges. In the next LabMag, integration strategies and a look at the generative AI of the future.

Enjoy reading and discovering!

Quick Takes | What's moving the industry?

Chatting until the doctor comes

Secure communication in the healthcare sector: Eight TI messengers approved by gematik now enable secure communication between practices and laboratories. From Q3/2025, patients will also be included - much more secure than WhatsApp & Co.

Countdown to the e-bill

Dental laboratories have been required to receive electronic invoices since January 2025. The active issuing obligation will be staggered: 2027 for larger laboratories (> €800,000 turnover), 2028 for all others.

Material offensive for dental 3D printing

The range of dental 3D printing resins is growing rapidly: at IDS 2025, several resins for new interesting areas of application were presented - e.g. for interim prostheses and sports mouthguards.

Deep Dive | Background and perspectives

Last week, I was scrolling through my Instagram feed and was amazed: Suddenly, many of my contacts looked like they were in an action figure box - all using the same prompt. With two clicks, the algorithm transforms every face into a cartoon character. Impressive? Yes. Creative? Rather not.

Because if we're honest: The supposed democratisation of creativity through AI does not suddenly turn us into artists. What characterises human creativity? The personal story, the will to be unique, the intention to touch others ...

Beyond art, AI offers us great opportunities. In dental technology, it could go far beyond simply increasing efficiency and open up new opportunities for precision, personalisation and process optimisation. However, there is often a world of difference between hype and reality - or crucial years of development. What is often touted as a revolutionary vision has to prove itself in everyday dental technology. Time for a reality check between hype cycle and game changer; time for a sober look at a technology that could actually fundamentally change our industry - if it delivers what it promises.

From hype to reality: a billion-dollar market with real applications

In February 2025, the FDA granted VideaHealth the largest approval to date in the field of dental AI - a clear signal that the regulatory landscape is changing. Market research institutes are also forecasting significant growth in the AI market in the healthcare sector.

But honestly: what counts for users is not forecasts, but the benefits in everyday life. And more is happening here than many people want to realise. AI is developing from a mere assistance system into an independent player. The first generation automated processes - the new generation will transform them. Practical examples:

• Overjet analyses X-ray images within seconds and highlights caries lesions, bone density and anomalies that often escape the human eye
• Yomi, the first FDA-approved robotic system for implantology, provides haptic guidance during implant placement.

What makes these applications different from previous solutions? They change not only how we work, but what we do. And this is the crucial difference between the first and second AI waves - the transition from pure process optimisation to genuine transformation.

AI 2.0: beyond mere automation

The first generation of AI applications automated processes, e.g. CAD suggestions in model (e.g. didex) or design software (e.g. Maestro 3D Ortho Studio, exocad AI), optimised manufacturing through intelligent CAM software (e.g. MillBox) or workflow optimisation in CAM machines. This is all great - but it seems to be just the beginning. The really exciting developments go far beyond that.

Four key trends in AI 2.0

1. Multimodal AI analysis: Instead of isolated data sources, advanced systems combine text, image and 3D data. This enables a context-sensitive interpretation of clinical cases. The analysis takes into account anatomical structures, patient history, functional parameters, aesthetic preferences and medication interactions, among other things.
2. LLM-based assistance systems: Large Language Models (LLMs) - the technological basis behind language AI such as ChatGPT - are finding their way into the dental industry. Specialised LLMs process patient records, scientific literature and clinical experience.
3. Immersive collaboration: VR-supported platforms are revolutionising collaboration between laboratories and practices. In the virtual world, it is possible to work together in real time, regardless of location.
4. Generative design systems: AI systems can independently generate new restoration designs based on functional and aesthetic parameters.
   

Between euphoria and reality

Despite all the enthusiasm, it is necessary to take stock. Three central aspects characterise the discussion:

Sensible integration vs. technological overkill

New systems offer fascinating possibilities - but the challenge lies in meaningful integration into existing workflows. Identifying the "sweet spot" between innovation and established processes is crucial. Laboratories that see AI as an extension of their expertise and not as a replacement will achieve the most convincing results.

Man and machine: who is in charge?

The reliability of modern AI systems has improved enormously, but dental expertise and clinical experience remain irreplaceable. The future lies in hybrid models in which AI takes over repetitive tasks. It is important to consider the potential risks of "black box" results where the AI's decision is not transparent.

Data economy vs. data protection

Multimodal AI analysis requires comprehensive data integration. The advanced systems require a critical mass of training data for optimal results. A data pool of many patient cases can help to optimise training data. At the same time, the protection of sensitive data must be guaranteed.

Conclusion - Part 1

So much for the current opportunities and challenges of AI in dental technology. But how can the technology be meaningfully integrated into everyday laboratory work? Which specific strategies have proven successful? And what role will generative AI play in dental technology? Specialist journalist Annett Kieschnick answers these questions in the second part of our AI series in the next issue of LabMag.