Writer says AI is shifting investment banking’s bottleneck to sourcing

AI is changing the staffing model

Investment banking has traditionally relied on a staffing pyramid, with analysts handling much of the production work while senior bankers manage client relationships and judgment. Writer says that model is being challenged as AI agents become capable of handling parts of junior bankers’ workloads.

Goldman Sachs CEO David Solomon said a team of about half a dozen people once spent two weeks preparing an S-1, a regulatory prospectus describing a company, its financials and risk factors. Solomon said AI can now produce a document that is 95% complete in a few minutes. The remaining 5%, he argued, is where a firm can distinguish itself.

Writer says AI increasingly automates analytical and production tasks that consume 60% to 70% of a junior banker’s time. It also says AI can produce a structured first draft of a confidential information memorandum in hours, reducing first-draft production time by 60% to 70%.

The capacity shift puts sourcing in focus

According to Writer, a traditionally staffed boutique advisory firm supports one deal per junior banker each year. With AI handling the analytical layer, the same banker can support two to three deals simultaneously. Deloitte estimated that generative AI could increase front-office productivity at the world’s largest investment banks by 27% to 35% by 2026, adding roughly $3.5 million in additional revenue per front-office employee.

Writer points to Evercore’s internal AI tool, launched in February 2026, which automates the creation of a precedent-transactions deck. VP-level associates can now run their own deal teams without analyst support on the research side, the company says.

The result, Writer argues, is that the main constraint moves upstream. McKinsey found roughly 20% lower costs on deal processes and a 10% to 30% shorter timeline. Meanwhile, 80% of corporate and private equity organizations use generative AI for target identification, and 79% use it for target screening.

Writer says firms are using AI to score a 500-company universe in 24 hours, compared with the two weeks previously needed to build a 30-company target list. Finding more targets, however, is only the beginning. The company says the advantage comes from how bankers engage with those targets.

Human judgment remains central to winning mandates

Writer says AI can find and score targets and draft an initial outreach email, but cannot assess a management team’s conviction, interpret tension in a boardroom or determine whether a founder is ready to sell. Those capabilities depend on personal relationships, trust and judgment.

A 2026 benchmark involving 502 current and former investment bankers from firms including Goldman Sachs, JPMorgan and Evercore tested nine frontier AI models on 100 junior-banker workflow tasks. Writer says even the best-performing model failed close to half of the grading criteria, and bankers rated none of its outputs as ready to send to a client.

In the accompanying survey, only 10% of bankers said current AI tools meet their needs, while 78% identified excessive errors as the primary limitation. Writer attributes the problems to issues including fabricated data, inconsistent figures and hard-coded values instead of formulas.

Writer advocates redeploying analysts

Writer argues that firms should redirect analysts toward sourcing, personalized outreach and other work that develops judgment and relationships. It says this would help analysts build skills needed for progression toward senior banking roles, rather than removing the positions that provide that development path.

The company also promotes governed AI systems that use firm data, compliance guardrails and an individual banker’s writing style. Writer says its voice feature learns a banker’s phrasing, habits and idiom, while its guardrails govern every generated piece of content.

For users, the message is that AI can create more capacity for deal teams, but the value of that capacity depends on how firms deploy it. Writer’s argument is that investment banks will gain the most when automated analysis gives bankers more time for sourcing, conversations and the relationship work that can turn potential targets into mandates.