McKinsey Desperate to Unlock AI Value in Banking
Unlocking AI value in banking is easy if you "revamp the entire tech stack."
McKinsey is becoming increasingly desperate to show banks how to uncover its predicted $200-350bn in global AI value, but most banks can’t comply with broad diktats such as: “revamp the entire tech stack.”
McKinsey's advice for banks isn’t all bad. It is often practical with suggestions such as focusing on “high business impact and high technical feasibility” areas for AI transformation, which are perfectly reasonable. In another era without billable hours, that would be called “go for the low-hanging fruit.”
If you enjoy this article, subscribe for more!
Still, if you read between the lines, it seems McKinsey is becoming impatient with its banking clients, who are way behind in unlocking the massive AI value they predicted.
Banks, which were never known for speed in technology adoption, seem to be working against McKinsey’s high-speed transformation. From the bank’s perspective, McKinsey’s sprint to unlock AI value may be too much and too fast, given their justifiable fear of AI risks and challenges with their tech stack.
So when McKinsey comes out with statements like this, many bankers just cringe:
“To create sustainable value, banks need to put AI first and revamp the entire technology stack. The rise of innovative technologies such as gen AI has prompted an update to the technology stack from a previous version published in 2020.”
At the start of 2025, most banks' tech stacks date to 2015, not 2020! So, McKinsey's push for banks to transform themselves and “revamp their tech stack” will be met with a shrug from most bankers.
AI will transform banking, there is no doubt. How fast that transformation will come is another story, and McKinsey’s urgency appears increasingly out of touch with most banker’s reality.
👉AI-First Bank Essentials
🔹 Reimagining the customer experience by providing personalized offers and streamlined, frictionless use across various devices for bank-owned platforms as well as partner ecosystems.
🔹 Using AI to help with decision-making, significantly enhancing productivity by building the architecture required to generate real-time analytical insights and translating them into messages addressing precise customer needs.
🔹 Modernizing core technology required for the backbone of the AI capability stack, including automated cloud provisioning, an application programming interface, and streamlined architecture to enable continuous, secure data exchange among various parts of the bank.
🔹 Setting up a platform operating model that brings together the right talent, culture, and organizational design.
If you know someone who would like this newsletter, please share it with them and help grow our Asia, CBDC, and AI aficionados community!
Readers like you make my work possible! Please buy me a coffee or consider a paid subscription to support my work.
Sponsor Cashless and reach a targeted audience of over 55,000 fintech and CBDC aficionados who would love to know more about what you do!
