Choosing the right partner defines the success of generative AI in banking: BCG reports that 66% of executives are dissatisfied with their AI progress. This guide covers 5 selection criteria from BCG, McKinsey and Gartner, plus the 5 actions taken by banks that achieve productivity gains above 10%.
Generative AI in banking: from opportunity to real impact Generative AI is no longer something on the horizon, it is a real, concrete driver of efficiency, growth and differentiation in financial services. Today, the banks that manage to scale real use cases, from customer service and fraud prevention to internal productivity, collections, marketing and sales, are the ones combining strategy, technology and execution. We can see how generative AI adoption is already growing today in the following charts from McKinsey's study, Banking's Gen AI Opportunity : But there is a critical point that defines whether these initiatives succeed or fail: the choice of technology partner. It is not just about who implements a model, but about who supports the bank in transforming processes, teams and results with generative AI. In this article we share which criteria you should consider to select the best company to implement generative AI at your bank, drawing on studies and reports from BCG, McKinsey and Gartner, and we explain why Delto is that partner for financial institutions in LATAM. According to the data in From Potential to Profit with GenAI , from BCG AI Radar, 66% of executives are ambivalent or dissatisfied with their organization's progress on AI or generative AI. This stems from a lack of talent and skills, little clarity on investment priorities and planning, and the absence of a strategy to implement responsible AI or generative AI. That is why in this blog post we explain how you should implement AI the right way to achieve productivity gains, one of AI's biggest promises (as shown in the second image), and succeed. Step 1: understand the business value before the technology One of the most common mistakes in generative AI initiatives is starting with the tool instead of the problem. Leading organizations first define the business impact they are after: cutting costs, improving customer experience, accelerating time-to-market or mitigating risk. Generative AI in banking creates the most value when it is aligned with clear, measurable goals, and when use cases are prioritized by impact and feasibility. Step 2: check for proven experience in banking and financial services Generative AI is not implemented the same way across every sector. In banking, important factors come into play such as regulation, security, data privacy, compliance and legacy systems. Consulting reports agree that the most successful projects rely on partners with industry-specific expertise, who understand the flows, risks and constraints of the financial sector. Step 3: assess the focus on scalability and secure architecture Running a generative AI pilot is relatively easy. Scaling it in a secure, governed and sustainable way is the real challenge. According to Gartner, many initiatives fail when moving from proof of concept to production because they did not properly define the architecture, data governance and operating models. What to evaluate in a partner: Design of scalable and secure architectures Model and data governance Focus on MLOps / LLMOps Compliance with security and privacy standards Step 4: ability to work with internal teams and drive adoption Generative AI does not transform organizations on its own, people transform organizations. The banks that create value invest in change management, training and co-creation with their internal teams. A good partner does not replace the bank's teams, it empowers them. Step 5: long-term vision and continuous improvement Generative AI evolves very fast. Models, tools and best practices change in ever-shorter cycles. That is why, more than a one-off vendor, banks need a long-term partner with a continuous-improvement mindset. As a summary, these are the 5 actions taken by those who are implementing AI successfully in their organizations according to BCG: 1. They invest in productivity and revenue growth. They target productivity gains above 10% and reinvest to drive revenue growth. 2. They build skills systematically. They scale their learning capacity, including across executive teams. 3. They watch the cost of usage. They understand that usage cost has long-term implications and needs immediate attention. 4. They build strategic relationships. They develop a partner ecosystem to manage complex, dynamic challenges that evolve quickly. 5. They implement responsible AI (RAI) principles. They bring responsible AI to the CEO's agenda and plan proactively for emerging policies and regulations. Why is Delto the ideal partner to implement generative AI at your bank? At Delto we work as strategic transformation partners, not just technology implementers. We combine technical expertise, methodology and a business mindset so that generative AI delivers real, measurable impact. What sets us apart: In the MIT report, The Gen AI Divide , it is explained that generic AI chatbots work because they are simple to test and flexible, but they fail in critical workflows due to a lack of memory and personalization. At Delto we have experience in complex, regulated environments : we understand the specific challenges of banking and financial institutions in LATAM. Our AI agents also have omnichannel memory, they remember the conversations they had with users on one channel and can continue them on another, and they enable the customization each bank needs. The GenAI Divide, STATE OF AI IN BUSINESS 2025, MIT. In addition, our approach is end-to-end , we cover everything from defining use cases to implementation, scaling and adoption. We work with secure, scalable architectures, designed to grow without compromising compliance or security. We believe in collaborative work, we co-create with the bank's teams, strengthening internal capabilities. Our world-class mindset means we build on global-level standards, practices and technology, adapted to the local context. We do not believe in generic solutions or empty promises. We believe in doing, measuring, learning and scaling. Always giving our best so that generative AI stops being a trend and turns into concrete results. Choosing the right company to implement generative AI at your bank is a strategic decision. It is not only about technology, but about truly being able to trust the partner you choose, one with proven experience and a vision shared with your bank's. At Delto we are ready to support you on that journey, with a team that is prepared, committed and focused on generating real impact.
What criteria define the best partner to implement generative AI at a bank? Five: start with business value rather than the tool, proven experience in banking and financial services, scalable and secure architecture with data governance, the ability to drive adoption with internal teams, and a long-term vision with continuous improvement. These are the criteria BCG, McKinsey and Gartner agree on.
Why do so many generative AI initiatives in banking fail? According to BCG, 66% of executives are ambivalent or dissatisfied with their AI progress due to a lack of talent, unclear investment priorities and the absence of a responsible AI strategy. Gartner adds that many projects fail when moving from pilot to production because they do not properly define architecture, data governance and operating models.
What makes Delto an ideal partner for LATAM banks? Delto works as an end-to-end strategic partner, not just an implementer: experience in regulated LATAM banking environments, agents with omnichannel memory that resume the conversation across channels, secure and scalable architectures, and co-creation with the bank's internal teams.