In an interview-style profile, Alexander Vasylenko—a Ukrainian-born New York-based financial analyst who also trains AI models in his spare time—explains how AI training intersects with his day job and career security in a landscape of growing automation.

Vasylenko trains AI models after work to perform core analyst tasks like market analysis, opportunity evaluation, and report drafting, aiming to future-proof his career as automation expands in finance.

Looking ahead, he envisions AI augmenting professionals across industries, with success hinging on deep subject-matter knowledge paired with proficiency in AI tools and a willingness to supervise AI outputs.

The piece notes a shift from pilot programs to full-scale AI implementations in investment management, emphasizing areas such as due diligence and operational efficiency.

Payment for AI tasks varies by role, ranging from $50–$70 per hour for prompts, $90–$120 for reviewers, and up to $160 in some cases, underscoring human-guided prompt creation as a key driver of AI performance and monetization.

Industry commentary stresses a skills-and-reskilling imperative, with resources to build AI literacy and the potential for high pay in specialized AI roles in finance.

Forecasts warn that AI could threaten or transform millions of jobs globally, including finance, but analysts who can supervise and govern AI systems may find new opportunities.

Vasylenko highlights rapid progress in AI over the past couple of years, with substantial efficiency gains and the ability to generate complex analyses with fewer inputs, raising questions about the staying power of traditional analyst work.

Security and ethics are central to his training, incorporating regulatory guidelines and adversarial testing to mitigate biases and protect data, as demand for AI security professionals grows.

He argues that mastering AI training will make him an indispensable bridge between human expertise and machine efficiency, turning disruption into a personal advantage.

The article places his approach within a broader trend of AI adoption in finance, where banks and firms use AI for predictive analytics, risk assessment, and portfolio management, and where analysts are urged to upskill in AI literacy.

His routine blends a full-time finance role from 9:00 to 17:00 with AI training sessions from 17:00 to 21:00 on weekdays, plus weekend work, driven by the belief that AI will eventually handle many routine tasks in finance.