Vision-based robotic control (also known as visual servoing) is promising for surgical tool tip tracking and automated visualization of photoacoustic targets during interventional procedures. However, reliable segmenta-tion in photoacoustic-based visual servoing was previously achieved with a light source that exceeds laser safety limits, due to the limited availability of laser safety limits for only skin or eyes and the associated difficulty with visualizing signals at the low laser energies within these safety limits for millimeter-sized light sources. Short-lag spatial coherence (SLSC) imaging is an advanced beamforming method that has shown offline promise toward enhancing the visualization of signals acquired with low laser energies. This paper summarizes the first known GPU-based, real-time implementation of SLSC for photoacoustic imaging and displays example images showing the application of this real-time algorithm to improve signal visualization and segmentation for visual servoing tasks. Results with ex vivo bovine tissue demonstrate that real-time SLSC imaging recovers signals obtained with low laser energies (i.e., ≤ 268 μJ) with mean ± standard deviation signal-to-noise ratios (SNRs) of 11.2 ± 2.4 (compared to 3.5 ± 0.8 with conventional delay-and-sum beamforming). Therefore, real-time SLSC imaging enables low laser energies for visual servoing within existing safety limits, which is promising for multiple surgical interventions.