Background: Nearly 1.6 million Americans are diagnosed with Rheumatoid Arthritis (RA). 90% of patients with a diagnosis of RA have been prescribed a Tumor Necrosis Factor-ɑ Inhibitor (TNFi) or Targeted Synthetic Disease-Modifying Antirheumatic Drug (b/tsDMARD) as their first biologic, despite up to 70% ineffectiveness. Artificial intelligence tools can be used in the field of Rheumatology to predict inadequate response to TNFi therapies. Methods: This literature review analyzed the usefulness of Artificial Intelligence (AI) tools for patients with an RA diagnosis to determine if patients can benefit from an AI predictive tool to predict non-response to RA therapies. A total of 21 articles were thoroughly examined and included in this review. Results: AI tools can confirm which patients are non-responders to certain treatments. Results from this literature review support targeted therapy treatment selection in treatto-target management strategies. Conclusion: An AI tool can correctly predict which RA patients would likely fail to achieve a response to TNFi therapies and other therapies for RA post-treatment initiation. An AI tool halts the progression of RA in patients and helps inform doctors of the best treatment routes.