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automated operations, leading to improved patient outcomes and enhanced efficiency in surgical practice.

Limitations of automated surgery
The integration of automation and AI into surgical practice holds immense promise for enhancing patient
outcomes and optimizing healthcare delivery in spine surgery. However, several limitations and challenges
must be addressed to ensure safe and effective implementation in clinical settings.

One significant limitation of automation in surgery lies in its ability to handle complex scenarios with
potential unexpected intraoperative complications. While AI algorithms excel in analyzing structured data
and predicting outcomes based on predefined parameters, they may struggle to adapt to unanticipated
events or variations in patient anatomy . In such cases, human intervention and expertise remain
[45]
indispensable for navigating unforeseen challenges and ensuring patient safety.

The high cost associated with robotic surgery, including equipment acquisition, maintenance, and training,
[46]
presents a significant barrier for many healthcare institutions . As the level of autonomy in autonomous
devices increases, the regulatory challenges also escalate. The FDA reviews and clears robotic-assisted
[17]
devices via the 510(K) premarket notification process . However, higher-risk devices, such as those
classified as stage 3 or higher, may face more stringent regulatory scrutiny, leading to significantly increased
costs of bringing the device to market . The difference in costs for higher autonomy could be reflected in
[47]
the cost to the patient. Thus, increases in levels of autonomy could further exacerbate healthcare
disparities .
[48]
The legal and ethical ramifications of autonomous surgery further compound the challenges surrounding its
complete implementation. Analogous to the legal debates surrounding self-driving cars, questions regarding
liability and accountability arise when patients are harmed, or complications occur during autonomous
[43]
surgical procedures . The FDA approves devices but not the practice of medicine itself. Higher levels of
automated devices, such as stage 4 or 5, will be making clinical decisions intraoperatively to the same level
[49]
as a human physician . New regulatory bodies will likely need to be created to oversee the practice of
highly autonomous devices to ensure that the safety of the patients is upheld.

CONCLUSION
The advancements in surgical automation and robotics in spine surgery signify a transformative shift in
medical practice. From the initial introduction of robot-assisted systems to the development of semi-
autonomous platforms, the field has witnessed significant technological progress. These systems enhance
[37]
surgical precision and reduce operative time, offering potential benefits over traditional methods . The
integration of AI, ML, and DL algorithms into these robotic systems may further optimize surgical planning
and execution, allowing for real-time adjustments and improved outcomes.

Despite these advancements, the journey toward fully autonomous surgery is still in its early stages. With
the increasing integration of real-time imaging with robotic platforms, surgical systems will become
increasingly autonomous as computer vision improves unsupervised decision making. Better visualization
will enable robotic systems to process more data and thus execute better movements in real time, from
micro-corrections to serious changes of course when a complication may arise during surgery. Further, the
autonomous spine surgery systems currently in the pipeline far exceed the scope of pedicle screw insertion
alone: from neuro-registration to autonomous exoscopic guidance, groups have proposed innovative
robotic approaches to many procedures and standing problems. These technologies promise to enhance the
precision and safety of spinal surgeries, reducing the cognitive and physical load on surgeons.