• Winning now means showing up in AI-generated recommendations, which are influenced by third-party sources, reviews, and how models frame the brand.
  • Trust remains a constraint, however, and customers are more likely to make a purchase with AI if they feel a brand and a transaction process are secure and credible.

Middle East: For two decades, banks competed for visibility through branches, brokers, marketing scale, and online search rankings. In the span of a year, the sales funnel has moved into the AI era. Bain & Company finds that generative artificial intelligence has completely disrupted the existing model, changing not just how customers search and discover but how they decide and purchase.

Brand discovery shifts from search to answer

AI has become a key tool for customers discovering brands and products, as search shifts from link-based results to AI-generated answers. During the discovery stage, AI is embedded in search engines such as Google’s Gemini and in standalone assistants such as ChatGPT and Claude. AI assistants provide synthesized responses to customer questions, especially when the question requires explanation, guidance, or an analysis of trade-offs. As a result, a growing number of customers form a view and short list before or without ever visiting a brand’s website.

New research by Profound for Bain & Company, analyzing prompts and queries from opt-in consumer panels in Australia, paints a detailed profile of how consumers use AI assistants.

Within banking, customers are using AI assistants to discover brands, interpret options, and even draft communications. Roughly one-third of queries involved home loans, with customers looking to find banks that match their selection criteria. Credit card customers often pasted in a page of fees and asked the AI assistant to convert the fine print into understandable text.

In these cases, the AI assistant becomes the port of entry rather than the bank’s channels. Across all types of queries, social media and content sites dominated as the sources used by AI assistants. For banking queries, AI assistants generally relied not only on the banks’ own websites but also on trusted sources, including comparison websites. Brands can no longer gain awareness simply by driving customer traffic to site; they must position themselves for inclusion in AI-generated short lists and win in the answer.

AI assistants have also developed perspectives on each bank that inform share of voice. In transaction banking, the major banks led in share of voice, but that metric does not reflect overall market share, highlighting an opportunity for smaller banks in AI brand discovery.

Being included in the list is not enough. How the LLM behind an AI assistant frames a bank’s brand will influence customer consideration. Bain & Company’s analysis shows that positive framing correlated with repeated signals, such as clear anchor facts, structured and comparable product language, and credible third-party validation. Negative framing tended to stem from regulatory scrutiny; articles and commentary about scams, fraud, and customer harms; and persistent complaints about fees, disputes, or service delays.

Moving to the purchase stage

Consumers are already graduating from using AI assistants for brand discovery and comparison to purchasing with the help of AI assistants. In banking, this could take the form of a prompt like “Compare three mortgage offers I qualify for and prepare my application information for the lowest-rate lender.”

Pioneers are experimenting with tools for consumers to make purchases within AI assistants. In banking and personal finance, Intuit has embedded apps, including Credit Karma, directly into ChatGPT. Users can ask ChatGPT to surface credit card, personal loan, or mortgage options tailored to their actual credit profile and approval odds, without leaving the AI assistant.

Today the purchasing capability is nascent. Scaling adoption in consumer financial services will depend on implementing the technology with appropriate safeguards and building consumer trust so that AI purchasing feels as secure as traditional digital banking.

The trust factor

While consumers are beginning to use AI assistants, trust remains a constraint. Caution and skepticism surface when the consumer advances from advice to money movement or commitment. Bain’s research shows that only one-quarter of US consumers are comfortable using AI to complete a purchase. Customers cite data security and encryption, privacy, and AI misunderstanding their needs as the primary concerns. Brand also matters, with 36% of respondents saying they’d feel comfortable making purchases using an AI assistant from a brand they already trust for digital shopping.

Bain & Company identifies five practical steps for banking executives committed to winning in this new era.

  • Manage the narrative to control brand framing; don’t just solve for visibility. Move beyond aiming to be mentioned. Track how you are framed in AI answers, then fix the underlying issues and reinforce the right signals with third-party proof.
  • Build segmented value propositions that make the short list. LLMs flatten generic offers into average answers. Sharpen propositions by segment and job to be done, and express them as quotable, comparable facts.
  • Understand your role in the AI-enabled sales funnel before the profit pools move. Decide whether you will be the customer’s assistant, the trusted rails partner, or the product provider, and redesign distribution and economics to avoid disintermediation.
  • Rewrite and technically structure content for the answer layer, not the click. Turn marketing pages into natural-language modules that address trade-offs, scenarios, fine print, and next steps. Use structured formats, verified first-party facts, and a strong third-party presence so AI assistants can cite you accurately.
  • Put in safeguards to protect customers. Make primacy explicit through permissioned delegation, transparent controls, human escalation for high-stakes moments, and clear recourse when something goes wrong.

Banks no longer compete only for customer attention but also for how machines interpret their offerings and act on customers’ behalf. Banks determined to thrive in acquiring and retaining customers will need to shape that layer instead of being shaped by it.

For any questions or further information, please contact:
Christine Abi Assi – christine@daydreamer.agency

About Bain & Company

Bain & Company is a global consultancy that helps the world’s most ambitious change makers define the future.

Across 65 cities in 40 countries, we work alongside our clients as one team with a shared ambition to achieve extraordinary results, outperform the competition, and redefine industries. We complement our tailored, integrated expertise with a vibrant ecosystem of digital innovators to deliver better, faster, and more enduring outcomes. Our 10-year commitment to invest more than $1 billion in pro bono services brings our talent, expertise, and insight to organizations tackling today’s urgent challenges in education, racial equity, social justice, economic development, and the environment. We earned a platinum rating from EcoVadis, the leading platform for environmental, social, and ethical performance ratings for global supply chains, putting us in the top 1% of all companies. Since our founding in 1973, we have measured our success by the success of our clients, and we proudly maintain the highest level of client advocacy in the industry.