Financial services firms are finding that one of the most immediate pay-offs from artificial intelligence may not lie in flashy customer-facing tools, but in the painstaking work of answering requests for proposals and due diligence questionnaires.
According to Responsive’s 2026 Financial Services State of Strategic Response Management Report, the most advanced firms are more than 1.4 times as likely to report revenue growth from RFP activity as organisations with less mature...
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approaches. The finding suggests that the benefits of AI in this sector are arriving first in the commercial machinery that supports sales, procurement and client onboarding, rather than in the more visible parts of the business.
The lesson, according to the company, is not simply to bolt AI on to existing workflows. Instead, leading firms are building a dependable knowledge base, applying automation across the whole response process, governing what is produced and tracking whether the work is actually improving commercial outcomes. Responsive argues that firms taking this approach are turning institutional knowledge into an asset that can be reused, rather than allowing it to remain scattered across inboxes, documents and individual employees.
That emphasis on foundations reflects a broader pattern across enterprise AI adoption. In F5’s 2026 State of Application Strategy Report for banking and financial services, global leaders were said to be running an average of five AI models and embedding inference into applications, operations and customer-facing experiences. The report frames AI less as a single project than as a portfolio-management challenge, with firms needing to decide where automation adds value, how models are coordinated and how risk is controlled.
For response management, that means accuracy and governance matter as much as speed. Platforms focused on RFPs, DDQs and security questionnaires increasingly promise to draft answers from approved past responses and trusted source material, while routing uncertain questions to subject experts. The aim is to reduce the time spent assembling submissions without loosening control over what is sent to clients, consultants or counterparties.
The strategic case is strengthened by signs that the payoff extends beyond efficiency. Responsive’s report says the most mature organisations are seeing shorter sales cycles, stronger revenue and happier employees, suggesting that better response management can help both frontline deal-making and internal morale. In practice, that may matter as much as any time saved, particularly in businesses where a single missed deadline or inconsistent answer can undermine an opportunity.
The wider financial services backdrop may also be encouraging greater experimentation. HubSpot’s 2026 State of Industry Report on financial services says regulatory change and compliance are no longer the sector’s dominant obstacles, with other pressures now taking precedence. That shift suggests firms are becoming more focused on growth, productivity and competitive differentiation, even as compliance remains a constant consideration.
Taken together, the reports point to a more mature phase of AI adoption in financial services. The early advantage is no longer just about testing new tools, but about applying them to tedious, high-volume work where better process discipline can translate into tangible commercial gains. In that environment, RFP and DDQ management may prove to be one of the clearest examples of AI moving from promise to measurable business impact.
Source: Noah Wire Services
