The use of AI-based applications to deliver HR processes has exponentially increased in the last few years. Among all the processes, Talent Acquisition (TA), also known as recruitment and selection, has seen the most surge in the number of AI solutions available. The AI assimilation has however been far from smooth, as several well-known failures of deploying AI in TA have been reported, and a reliable mechanism for deploying AI in TA is therefore essential. We conducted a mixed-method qualitative study to address this gap. First, 171 HR software products were analyzed for their features and key offerings. Then, we interviewed a total of nineteen leaders across two categories – TA leaders who deliver recruitment operations, and technologists who develop and deploy AI-based recruitment solutions. Analysis of the interviews revealed key concerns and negative perceptions that TA leaders identified, and corrective measures to mitigate these perceptions that the technologists proposed. Adapting a phenomenon-based theorizing approach to our findings, we present an AI-TA maturity model by correlating the main categories of the software solutions we analyzed with the themes emerging from the interviews.