Classical force field and finite field methods adopt a different approach to constant potential simulations and describe the applied electrode potential in terms of the inner potential (ϕ) difference between two electrodes without any electronic structure information. This attractive feature, however, comes with a cost, as two electrode interfaces need to be simulated to build an electrode potential difference in a cell and to keep the simulation cell neutral. As one is typically interested in the properties of just a single electrode, i.e. the working electrode, the second electrode acts as a passive counter electrode. While the treatment of a passive electrode is justifiable for low-cost analytic force field potentials, this does not hold for electronic structure methods or even machine learning potentials as their computational cost is two or three orders-of-magnitude larger than that of analytic classical potentials. Therefore, future studies of electrochemical interfaces with machine learning potentials need new approaches to enable constant potential calculations of single electrodes without explicit electronic structure information So far, both GCE-DFT and classical force field methods have overlooked the question which of the electrochemical potentials, μbath e or μM e , is the relevant constant quantity in GCE-DFT simulations. While this has not been considered in the context of computational electrochemistry, recent work by Islas-Vargas et al. addressed this issue in detail for semiconductor-water interfaces. They emphasized that the relevant thermodynamically independent parameter defining the semiconductor electrode potential is the bath chemical potential (μ bath e ) rather than the system chemical potential (μ M e ). In semiconductor simulations, the inequality between μM e and μbath e results from the neglect of metal connections at the backside of the working electrode (see Supporting Information Section S5 for more discussion). This means that all the recent constant Fermi level GCE-DFT simulations fix the electrochemical potential of the simulation cell (μ M e ), not that of the connections i.e. the electron reservoir (μ bath e ) controlled experimentally Furthermore, the discontinuity in semiconductor electronic structure, due to the presence of band gap, does not permit the use of constant Fermi level DFT. Our results in the next sections demonstrate the limitations of present constant Fermi level simulations, which calls for more general GCE-DFT methods, where μbath e rather than E DF T f is explicitly controlled. To achieve this, we introduce a new constant inner potential (CIP) DFT method, and demonstrate that it is a general and theoretically rigorous approach to carry out constant potential ab initio simulations. Importantly, the CIP method directly controls μbath e and enables GCE-DFT simulations for systems for which the constant Fermi level methods do not correctly mimic the experimentally applied potential. CIP-DFT emerges as a universal approach for simulating a wide variety of electrochemical systems and expands the scope of the GCE-DFT simulations from metallic electrode and inner-sphere reactions to semiconductor electrodes, outer-sphere reactions and biased two-electrode cells.