Ten years ago, digital payments were still considered “alternative. ” Today, they’re the new normal — and by 2030, they’ll account for nearly 80% of global e-commerce. Wallets, account-to-account (A2A) payments, buy now pay later (BNPL), and even crypto are rewriting the rules of how money moves. What started as a convenience is now an expectation. Read the WorldPay report
Implications: Power shifts from older gatekeepers
This seismic shift isn’t just changing checkout flows — it’s reshaping who holds power in the financial system. Traditional banks, once gatekeepers, now compete with fintech giants and digital wallets backed by tech platforms. As digital payments expand, expect tighter regulations, fierce battles over user data, and a reimagining of what “banking” even means.
WiFi is replacing wallets
Real-time payment infrastructure is quietly becoming the backbone of global commerce. Systems like India’s UPI and Brazil’s Pix are enabling money to move instantly — 24/7, 365 days a year — cutting settlement time from days to seconds. This immediacy is a game-changer for merchants, consumers, and economies alike. It reduces fees, improves liquidity, and boosts financial inclusion.
Yet, as real-time rails begin to link across borders, they also threaten traditional card networks and challenge the status quo of global fund transfers. Banks and regulators will need to catch up — or risk being bypassed entirely.
Mobile payments have exploded, with phones now responsible for over half of global e-commerce transactions — and climbing. We no longer need wallets, just Wi-Fi. Whether it’s shopping online, tapping to pay in-store, or ordering dinner through an app, mobile has made payments seamless, personal, and always-on.
What does it mean for career opportunities?
With digital wallets expected to dominate transactions, demand for blockchain developers, cybersecurity experts, and payment infrastructure engineers is skyrocketing. Skills in real-time payments, embedded finance, and fraud detection AI are becoming essential. AI-driven fraud prevention, personalized financial services, and automation are transforming payments. So careers in machine learning, risk modeling, and behavioral analytics will see continued growth.
Midlife Crisis: When you become irrelevant for the first time
Midlife crisis – when you wonder if you have been wrong all along…
When you first question your relevance
It doesn’t hit all at once. At first, it’s subtle—like background static you can almost ignore. But slowly, almost imperceptibly, things begin to shift. You start second-guessing yourself in meetings, especially when younger colleagues speak with quick confidence. You hold back—not because you don’t know the answer, but because you’re no longer sure your answer holds weight. The certainty you once carried starts to flicker. Skills that once set you apart now feel… dated. The conversations move faster, the culture feels different, and you begin to wonder: Am I still relevant?
It’s not just doubt—it’s something deeper. Like a quiet unraveling of the identity you spent years building. The puzzle pieces of your career—your achievements, your reputation, the things you thought defined you—suddenly don’t fit the picture anymore. And in the stillness, a more unsettling question rises:
What you have in abundance does not matter
A lot of people label this moment as a “midlife crisis. ” But let’s be honest—it’s not always about age. You can feel this identity fracture in your late twenties if your career path suddenly disappears. You can feel it at 35 after a layoff. Or at 50 when the promotions stop coming.
What we’re really talking about is a relevance crisis—and it can hit at any time. You realize that the rules have changed. The things that used to signal success—loyalty, titles, experience—don’t carry the same weight.
Here is a chat with Vijayanti Margassery (ACC) who is a PhD scholar and a HR practitioner.
Building a Learning Culture
DataCamp had the Radar Conference. The focus was on skills that are needed for the AI economy. I joined Oliver Patel, AIGP, CIPP/E of AstraZeneca and Colleen Young, Ph. D. of Bayer to brainstorm on how to build a learning culture.
Read what DataCamp wrote about it https://www. datacamp. com/resources/webinars/learning-culture-in-generative-ai
Frame it like a problem to be solved or a habit to be formed
https://www. datacamp. com/resources/webinars/learning-culture-in-generative-ai
For every question, I believe, you must frame it as a problem to be solved. For example when asked about the question, “What are the hallmarks of a great learning culture for generative AI?”, frame it as a problem.
AI is what I call Chaotic Technology.
Solution: A great learning culture treats learning as a habit, not an event. It is:
1. Embedded in work – Learning should be part of daily workflows, not a separate activity. Laing O’Rourke, a construction company in Australia, revamped its training by adopting “bite-sized” learning modules inspired by platforms like Instagram and TikTok, making learning more accessible and engaging for its 5,500 employees.
2. Leverage AI for Personalized Learning: Utilize AI to tailor learning experiences to individual needs. Squirrel AI Learning employs AI to create personalized lesson plans, adapting to each student’s learning pace and style, enhancing engagement and effectiveness. Use AI to learn about AI.
3. Demonstrate Leadership Commitment: Leaders should actively participate in and advocate for continuous learning. Johnson & Johnson implemented mandatory generative AI training for over 56,000 employees, emphasizing leadership’s commitment to AI literacy.
I am deeply critical of mandating ANY kind of learning activity – other than safety training and that too can be made to be interesting and fun. Years of push based training is going to be the biggest reason why employers will struggle to upskill empolyee when they need it most.
