AIMS/HYPOTHESIS: The continuous glucose monitoring (CGM)-derived glucose management indicator (GMI) is valuable to people with diabetes, and healthcare professionals and organisations for assessing overall glucose levels, optimising management plans. However, the current GMI can both over- and underestimate HbA(1c), which can create clinical difficulties. Our aim was to improve the agreement between these two markers across clinically relevant ranges of glucose. METHODS: An updated GMI (uGMI) model based on physiological processes was evaluated using clinical trial and real-world data. The empirical relationship between average glucose (AG) and HbA(1c) was evaluated over 100 equal-sized data bins ordered by the sum of their rank positions. Alignments were assessed using biases in various ranges. RESULTS: In 18,860 individuals with 26,647 AG-HbA(1c) pairs, the uGMI significantly improved alignment with HbA(1c) and reduced the proportion of pairs with clinically significant discordance. Specifically, the regression slope of HbA(1c) vs GMI decreased from 1.4 to 1.0 when using uGMI, effectively eliminating proportional bias by reducing the deviation from unity (p<0.0001). Furthermore, absolute bias at HbA(1c) below 31 mmol/mol (5.5% in National Glycohemoglobin Standardization Program [NGSP]) and above 75 mmol/mol (9.0% NGSP) was reduced from >4.4 mmol/mol (0.4% NGSP) to ≤ 1.1 mmol/mol (0.1% NGSP). Consistent performance across both Abbott Freestyle Libre and Dexcom CGM devices confirmed that the uGMI is robust and device-independent, supporting its clinical utility and incorporation into standardised CGM clinical summary reports. CONCLUSIONS/INTERPRETATION: Compared with the CGM-derived GMI, the uGMI provides more accurate and consistent agreement with HbA(1c), particularly at lower (<42mmol/mol or 6% NGSP) and higher (>58 mmol/mol or 7.5% NGSP) HbA(1c) levels.