AF development is determined by clinical risk factors and genetic predisposition. Few studies have explored whether incorporating polygenic risk scores (PRS) improves clinical risk prediction beyond existing models. We evaluated the interaction between AF-PRS and the HARMS₂-AF and CHARGE-AF clinical risk scores on incident AF risk among the UK Biobank. AF-PRS was examined in those with and without incident AF based on ICD-10 coding and divided into tertiles defined as low, intermediate and high risk categories. Regression analysis examined the impact of AF PRS combined with the HARMS₂-AF and CHARGE-AF risk scores and AF risk. Among 285,734 participants with available whole genome sequencing data (52% female, age 57 years [50-63], 84.6% caucasian), AF incidence was 6.6% with a median time to AF 8.5 [5.0-11.2] over median 12.9 years follow up. High AF-PRS tertile was independently associated with incident AF risk, after adjustment for clinical risk factors (HR 2.75, 95% CI 2.62-2.89, p<0.001). AF-PRS enhanced AF risk prediction when combined with the HARMS₂-AF risk model (AUC 0.828 improved to 0.839 with the addition of AF-PRS (DeLong p<0.001) with overall NRI 13.5% [12.8%-14.1%] and the CHARGE-AF risk model (AUC 0.808 improved to 0.828 with the addition of AF-PRS (DeLong p<0.001) with overall NRI 7.3% [6.7%-7.9%]). Combining genetic and clinical risk using the HARMS₂-AF and CHARGE-AF risk scores significantly improved AF risk prediction. Incorporating polygenic to clinical risk scores may enhance population screening and promote targeted interventions to reduce the incidence of AF.