What businesses need to know for their AI era

Janet George is an AI pioneer. For several decades, she has been serving tech giants — including Oracle, Intel, Apple, Yahoo! and eBay — by building  computer systems that function more like the human brain. And she has done so by implementing artificial intelligence, machine learning, LLMs and deep neural networks.

“My experience with AI traces back to the era when cloud computing, deep learning, vast data sets and advanced GPU capabilities began to converge,” she says.

Since 2025, George has led the AI Center of Excellence at Mastercard, where her focus is harnessing cutting-edge technologies to enhance, protect and personalize payment systems. She’s also guiding Mastercard on its journey to become an AI-first organization — a goal she encourages for businesses of every size.

AI has evolved like wildfire over the past two years, igniting expectations that it will radically transform how companies run operations, develop new products and interact with customers. George believes businesses that are open to change — and make an effort to understand AI’s capabilities and limitations — will be best positioned to thrive.

We asked this tech trailblazer what business leaders need to know to stay ahead of the curve in our increasingly AI-powered world. 

George: First, learn how to tune out the hype and focus on scalable ROI. The goal should be to move beyond experimenting with generative AI and start scaling it throughout the organization. Leaders need to pinpoint high- impact and realistic use cases that genuinely enhance customer value with ROI rather than just pursuing productivity tools, because every day we have a new productivity tool that is emerging.

I also think deploying AI ethically and responsibly is super essential. This means proactively addressing the bias that may already exist in operations or operational data, ensuring there is transparency in how our data is used and maintaining trust with customers.

Technological fluency is really crucial. I don't think leaders need to be writing the code themselves, but they should understand the complexities, the capabilities and the limitations of AI, including how to mitigate risks and look at inaccuracies in data or any kind of security vulnerabilities.

That said, AI should be seen as a tool that augments, not replaces, human intelligence. By encouraging the pursuit of models where AI tackles routine tasks, leaders can enable their people to focus on creativity, empathy and strategic thinking.

Over the past several years, AI has undergone a remarkable transformation, moving away from first- and second-generation machine learning and feature extraction with gradient boost algorithmic modeling to embracing deep learning with neural networks with third and fourth generations of transformer modeling, with attention mechanisms and self-learning. This shift has been marked by the emergence of very large language models, such as generative pre-trained transformers, or GPTs, that have redefined what AI can accomplish.

These innovations, powered by immense data resources and GPU acceleration, have enabled AI to achieve human-level performance. There has been an exponential leap in how the technology retrieves information, understands context and demonstrates intelligence, especially in the natural language processing and reasoning area. So modern autonomous systems and AI agents are now designed to emulate the human brain, incorporating elements like episodic memory and advanced cognitive abilities. I'm constantly amazed at how biologically inspired all of our scientific advances have been.

AI is fundamentally reshaping financial industries and banking. They are evolving from using simple automation to becoming generative AI–first institutions, very decisively acting and deploying modern AI technologies.

And this is all expected to gain them a very significant competitive edge over those relying on legacy systems and manual processes. A 2025 EY survey showed that 71% of banks have implemented or soft-launched gen-AI capabilities, with 61% seeing strong impacts already and 89% seeing strong impacts ahead over the next two years, ranging from cost-savings tools to driving top-line revenue growth.

We’ve been long using AI for risk management and fraud detection. Now AI agents can monitor transactions and patterns across accounts and channels, scoring risks in milliseconds and flagging anomalies in location and spending velocities that older detection methods can easily miss. Generative AI agents can significantly reduce the number of false positives in operational network traffic. Autonomous agents can understand, reason and act on behalf of the bank to manage complex end-to-end tasks, such as handling credit disputes. 

George: Instead of relying primarily on brand websites or traditional search engines, consumers are now using AI-driven Q&A tools to guide their shopping decisions. One recent report showed that 60% of the consumers utilize AI for shopping and 46% of these people trust AI more than friends when they seek advice on outfits — some of the insights that are driving our continued investment in agentic commerce and the development of tools and services like Agent Pay and Agent Suite.

We’re also seeing more AI-powered customer support. Consumers are now engaging with AI agents, versus traditional chatbots, on retail websites to access instant round-the-clock support. But what’s incredible is that these agents are sophisticated enough to understand and manage complex conversations, adapting to various speech patterns, tones and accents.  

Small businesses have adopted generative AI to automate a variety of routine business processes — administrative work, appointment scheduling, inventory control and data entry — allowing these tasks to be completed more efficiently and accurately.

We're also seeing, in the financial management area, the rise of AI-powered virtual CFOs that are enabling small businesses to get real-time data analysis of their cash flows, identify potentially fraudulent activities and enhance cybersecurity by monitoring transactions and network traffic.

Last, I would say one of the benefits for small business is cost reduction. By automating routine and repetitive tasks, they can significantly cut labor costs and find greater efficiency, freeing up time previously spent on manual tasks. Now business owners can focus on driving strategic growth and competitive advantage. Small businesses gain the ability to offer superior and faster services, allowing them to effectively compete with larger organizations.