AI REGS & RISK: Riding the AI Wave – Out of the Lab And Into Mainstream


By Greg Woolf, AI RegRisk Think Tank

Remember when your iPhone was just for calls and texts? Fast forward to today, and it’s your pocket-sized portal to the world. Now, imagine a shift just as groundbreaking, but in the world of finance, thanks to AI. That’s right, AI has officially hit the mainstream. And once the genie’s out of the bottle, there’s no cramming it back in.

So, here we are, at a juncture like the iPhone App Store launch in 2008 – but this time, it’s AI transforming how we interact with the world and manage our finances and wealth. The promise is huge: personalized financial advice at our fingertips, investment strategies that adapt in real-time, and customer service that knows what we need before we do. But, let’s be honest, integrating AI into the risk-averse, regulated world of finance comes with its share of heavy lifting.


First up, the complex regulations. Navigating the labyrinth of financial compliance with AI? It’s like threading a needle while wearing boxing gloves. Privacy, data security, accuracy – the list of must-haves goes on. Then there’s the challenge of making AI’s decisions as clear as day, especially when it’s used to guide investments or manage risk. Transparency isn’t just nice to have; it’s a must. Plus, we need to ensure our AI doesn’t inadvertently pick up biases along the way, treating fairness as an afterthought.


AI can also expose you to new and undiscovered cybersecurity vulnerabilities. Ensuring AI systems are resilient against cyber threats is crucial for safeguarding customer data and financial assets, maintaining trust, and meeting regulatory demands. And integrating cutting-edge AI into existing financial systems is no small feat—it’s like to trying to run the latest apps on a first-gen smartphone. This challenge involves not just technical upgrades but also aligning new AI capabilities with the old guard of legacy systems, a task that demands strategic insight, investment, and careful execution.

However, with AI transitioning from experimental labs to mainstream applications, the potential for significant returns has arrived. In less than eight years, 79% of U.S. enterprises that adopted mobile apps reported substantial ROI benefits, according to a 2016 survey by Red Hat software. The unprecedented rate of user subscription for ChatGPT and other Generative AI platforms shows that the rate of adoption for AI is even faster. This isn’t merely about keeping up; it’s about utilizing AI to substantially increase market share, profitability, and shareholder value.

Since 2017, our AI Think Tank has advised financial institutions, government regulators, and the U.S. Congress on leveraging AI in the financial services industry. In the coming articles, we will share insights from a collective of expert advisors, including financial executives, regulators, and AI practitioners. Our goal is to help you harness the promise of everyday AI for your customers while carefully navigating potential pitfalls and risks. Helping you find the sweet spot where innovation meets practicality, ensuring you’re well-positioned to capitalize on the AI revolution without getting ensnared by its complexities.

So, as we dive into this exciting era, remember the iPhone’s journey from a simple calling device to becoming your customers’ indispensable digital Swiss Army knife. With AI, we’re looking at a similar trajectory, transforming the financial services landscape. Sure, there are challenges, but the rewards? They’re as vast as the possibilities unleashed by the iPhone App Store!

As we embark on this journey together, we’ll learn, adapt, and innovate as we go.  Because when it comes to AI in financial services, the future isn’t just coming; it’s already here. And it’s time to make the most of it.

Greg Woolf Bio

Greg is an accomplished innovator and AI strategist with over 20 years of experience in founding and leading AI and data analytics companies. Recognized for his visionary leadership, he has been honored as AI Global IT-CEO of the Year, received the FIMA FinTech Innovation Award, and was a winner of an FDIC Tech Sprint. Currently, he leads the AI Reg-Risk™ Think Tank, advising financial institutions, FinTech companies, and government regulators on leveraging AI within the financial services industry.