Choosing the Right Implementation Strategy When J.P. Morgan and Goldman Sachs announced major GenAI initiatives last year, they took notably different approaches—one prioritized vendor partnerships, the other emphasized building proprietary models in-house. For investment banks evaluating their own GenAI strategies, this divergence highlights a critical question: what deployment approach best fits your organization's capabilities, risk tolerance, and strategic priorities? An Enterprise GenAI Blueprint isn't just about what you build—it's fundamentally about how you build it. The right approach depends on your firm's technical resources, regulatory constraints, and the specific workflows you're targeting. Let's examine four common deployment strategies with their respective trade-offs. Approach 1: Custom In-House Development Some firms, particularly those with established quantitative trading operations and deep ML expertise, opt to build proprietary GenAI capabilities from the ground up.…