Make AI Boring Again
Our Guest- David Hardoon
David Hardoon is the Global Head of AI Enablement at Standard Chartered Bank, focused on making AI work inside a large, regulated financial institution.
His work centers on embedding AI into everyday banking decisions across risk, compliance, operations, and customer experience in ways that are responsible, explainable, and scalable.
Rather than flashy pilots, he focuses on practical AI that quietly reduces paperwork and helps people spend less time on repetitive tasks.
“We wanna put AI in the hands of everyone, just like you have email, just like you have Word.”
-David Hardoon
Imagine you walk into work on Monday and your bank has just rolled out an AI assistant to 70,000 employees.
Half the office is excited. The other half is quietly thinking: Is this the start of layoffs?
And somewhere in the middle is David Hardoon …
a man who helped write the rules for responsible AI as Chief Data Officer at the Monetary Authority of Singapore, then left the regulator’s office to build AI inside banks from the inside out.
His most controversial idea? He wants to make AI boring again. Not because it’s weak but because when AI is done right, it becomes like email or Excel: invisible, expected, and essential.
As David puts it, “banking’s quite boring” and he means that as a compliment. Because at the core, banking is about trust, safety, and risk management.
The Man Who Left the Rulebook to Enter the Trenches
David’s career reads like a rare “both sides of the battlefield” story.
First he worked at the Monetary Authority of Singapore, shaping how AI should be governed. Then he jumped into industry, helping digitize UnionBank in the Philippines, and now leading global AI enablement at Standard Chartered, a bank operating across 54 markets.
When asked what Standard Chartered actually does, he breaks it down plainly: “If I oversimplify it, cross border… how do we make sure money moves safely from one place to another?”
He adds two more pillars: wealth and sustainability, noting the bank was early in sustainable finance.
Then he describes his own role with the kind of blunt clarity that makes you trust him:
“I’m the global head of AI enablement… my goal and my objective is exactly that.”
In other words: less “AI theatre,” more making it usable for real people.
His job is to take AI from “this ethereal construct of AI, you know, jazz hands” and turn it into something practical: What does it mean? What does it mean to the business? How do we implement it, from infrastructure to talent to policy?
What Happens When You Give Everyone AI
Standard Chartered’s first big move was SC GPT, an enterprise productivity tool rolled out across the bank.
David explains the philosophy simply: “We wanna put it in the hands of everyone, just like you have email, just like you have Word.”
And he makes a prediction that lands because it’s obvious: one day we’ll find it strange that people ever debated whether AI assistants should exist at work, just like we’d find it strange to debate whether employees should have Excel.
But the real story isn’t the rollout. It’s what normal employees did once the tool was in their hands.
David shares one example from a team doing onboarding work:
They had to review huge piles of documentation, “it’s really mundane and boring stuff”—but necessary because “you have fiduciary responsibility.”
The process used to take about eight hours. The team used SC GPT to create a workflow that cut it to one hour.
And then he asks the question everyone jumps to: what happens to the other seven hours?
His answer: capacity.
“They have seven hours to onboard more companies.”
That’s why he says this isn’t just about productivity. It’s about growth.
Why “AI for Cost Cutting” Is a Trap
David has a surprisingly direct response when executives say they want AI to reduce costs or replace employees.
“I tell ‘em, point blank, don’t bother.”
If you want cost reduction, he says, use Six Sigma. AI can support that work but using AI primarily as a headcount-reduction tool misses the point.
Because to him, AI is fundamentally about knowledge:
“AI is about knowledge… knowledge discovery… knowledge management.”
And that’s why he calls it “an oxymoron” to say: we’re building a knowledge capability to reduce people.
Then comes the quote that hits hardest for employees:
“AI will not take your job in the bank. What will take your job from the bank is someone who has AI, understands AI.”
He compares it to a pilot trained in the 1970s trying to get hired today: the job still exists, but the skillset has moved on.
AI Doesn’t Fix Broken Work. It Exposes It.
David also calls out a quieter risk: people using AI to do the same messy work faster.
“If you say… ‘this is how we do things’… and I just want you to put AI here—the likelihood of failure is significant.”
He gives a mortgage example where teams needed to cross-reference up to 60 or 100 documents for a credit memo.
But trying to automate it revealed something absurd:
“People embed… scanned documents inside Word documents.”
That tiny “how” breaks everything. AI can’t extract or process information cleanly until the process is redesigned.
His point is simple: AI projects aren’t tool projects, they’re process projects.
How to Stand Out When AI Arrives
If your bank rolls out an AI assistant, what makes you the person who gets noticed?
David says it starts even before the tool launches. He hopes AI leaders don’t just roll it out with “jazz hands, AI.” They should talk to employees early.
And if you’re an employee? Be the one who says:
“Talk to me.”
“I want to be part of that process.”
Once it’s launched, the standout employees aren’t the ones pretending they already know. They’re the ones asking:
“I’m not quite sure yet how to use it… how do I use it?”
Then he shares what he looks for when hiring—something far more important than knowing how to code:
“What I look for is that critical thinking… the respectful challenging.”
He even warns people up front: “I’m sorry, I’m gonna ask a lot of annoying questions.”
The most important one?
“Why?”
Because in a 170-year-old bank, many processes exist purely because they’re institutional heritage. AI doesn’t fix that. Humans do.
Will AI Make You Dumber?
David doesn’t dodge this question. He says it depends on what you do with the time AI gives back.
“It’s about creation of capacity… but then there’s the question of what you do with that capacity.”
He jokes about spending it all on TikTok—but shares something personal: he’s dyslexic, and AI helps him write the ideas that have been stuck in his head for years.
“Now, suddenly I have this ability to write all the things that I wanted to write… because I’m using a tool that’s helping me articulate things.”
In his view, there’s responsibility at three levels:
individual accountability
organizational nudging
and societal education, because we still train people to memorize and pass exams rather than think.
The Future of Banking Isn’t More AI. It’s Less Visible AI.
David’s “boring AI” idea isn’t anti-innovation. It’s the opposite: it’s how real innovation scales.
He says we’ve “romanticized AI” too much, treating it like something magical we need to announce. His take is blunt:
“It’s like, no, just get on with it.”
He compares it to your phone:
“When do you wake up in the morning and look at your phone with this loving expression?… No, it’s just there.”
That’s what AI should become, something you don’t think about, but rely on.
And it leads to his best line of the episode:
“Get the brilliant basics right with AI first.”
Because once AI becomes normal, trusted, and boring, it creates proof points and the confidence to tackle bigger, world-changing work.
