BRAI is a systematic, active equity investment companytargeting US value stocks with the dual aim of delivering consistent returns and a 6% annual dividend yield. The trust applies four decades of BlackRock’s systematic investing expertise, combining advanced data science, AI, and portfolio construction discipline to outperform the Russell 1000 Value Index. Its structure allows for long-term capital deployment, with stringent shareholder protections including a 100% tender offer if it fails to beat its benchmark by 50bps annually over three years. Holding 150–250 stocks diversified across sectors, the trust seeks to capture inefficiencies in one of the world’s most competitive markets while managing risk and maintaining reliable income.

In the interview, co-manager Muzo Kayacan explains how AI – including transformer-based large language models – is reshaping the trust's investment process, from digesting 6,500 broker notes a day in 47 languages to back testing millions of ideas in seconds. He describes the balance between automation and human insight, where machines handle data-heavy analysis while portfolio managers focus on creative and complex decision-making. The conversation explores portfolio construction, risk controls, dividend sustainability, and how systematic signals such as valuation, management quality and sentiment combine to identify underappreciated US value opportunities. Kayacan also reflects on the “second golden age for quant,” outlining how scale, innovation, and continuous discovery of new signals give BlackRock an edge in staying ahead in systematic investing.