Business and Money Tips

AI can give you answers in seconds. But let me ask you something honest. When was the last time an answer alone gave you clarity? Most leaders today are not short of answers. They are short of clear thinking under pressure. And pressure is exactly where AI doesn’t help as much as we hope. I work with leaders, managers, and professionals across different industries. Almost all tell me the same thing, quietly. “Andy, I have more data than ever. More dashboards. More AI summaries. But decisions feel heavier, riskier, and more exhausting.” They are not confused. They are overloaded. Emotion creeps in. Fear of making the wrong call. Fear of accountability. Fear of speed. That’s not an intelligence problem. That’s a thinking problem. In the AI age, thinking is no longer about getting answers. It is about: framing the right problem reading people and situations accurately knowing when to act — and when not to AI can assist. But judgment still sits on human shoulders. Over the years, I realise...

  Why Love Intelligence Matters in the Age of AI “What’s this got to do with me?” That is often the first reaction when people hear the word love in a business or leadership context. Love, after all, seems far removed from performance, productivity, or profit. Yet this question itself reveals a deeper misunderstanding of how results are actually created. For decades, we have been taught that success comes from intelligence, hard work, strategy, and now technology. In the age of artificial intelligence, that belief has intensified. We are told to upskill, reskill, and optimise faster than ever before. But look more closely at what is happening in organisations today. Why do people with similar skills produce vastly different outcomes? Why do some teams thrive under pressure while others collapse into conflict and burnout? Why do capable professionals stall, while others keep attracting opportunities? The difference is not competence. It is human state . Every outcome begin...

Top 5 AI Concerns for Government Agencies & MNCs 1. Accountability: “Who Is Responsible When AI Is Wrong?” The concern AI outputs look authoritative Decisions are still signed off by humans Blame becomes unclear when things go wrong Why it keeps leaders awake Public sector: reputational and political fallout MNCs: legal liability, shareholder impact “The system recommended it” is not an acceptable defence What they fear most Leaders losing decision ownership without realizing it. 2. Over-Reliance and Erosion of Human Judgment The concern People stop questioning AI outputs Critical thinking weakens over time Junior staff defer to AI instead of learning Why it matters Judgment is a muscle, it atrophies when unused Organizations become fast but fragile Creativity and strategic insight decline Silent risk AI doesn’t just automate work, it can de-skill thinking . 3. Bias, Blind Spots, and Hidden Errors The concern AI reflects the data it is trained on Bias is often invisible and uninten...

How to Think Better in the AI Age (Without Becoming Dependent on AI) In the AI age, thinking better is not about becoming smarter. It is about becoming less lazy with your mind . AI will happily think for you. Your job is to ensure it doesn’t replace you. Here are easy but effective ways any ordinary person can improve thinking—no jargon, no PhD required. 1. Delay the Answer (Don’t Ask AI First) The biggest damage AI causes is answer addiction . Before asking AI anything, pause for 60 seconds and ask yourself: What do I already know? What don’t I know? What assumptions am I making? This short delay activates your own thinking muscles. Rule: If you ask AI immediately, you outsource thinking. If you think first, you use AI properly. 2. Turn Answers into Questions When AI gives you an answer, don’t accept it. Instead, ask: What is missing? What would make this wrong? In what situation would this fail? Who would disagree with this? Good think...

AI can now do almost everything. So what actually matters? Not the tools. Not the features. Not learning the “next” AI platform. What matters is: – asking the right questions – thinking clearly – having direction – knowing what to solve and why That’s why the real advantage today is thinking. AI is brilliant at execution. Humans must be brilliant at sense-making. The mistake many people make is this: They keep chasing new AI tools, hoping tools will give them an edge. But tools don’t create advantage. Thinking does. The correct approach in the AI era is: – improve your thinking – frame better problems – imagine new possibilities – design solutions – then use AI to execute at scale AI should be used as an amplifier, not a crutch. Instead of asking: “What new AI tool should I learn?” The better question is: “How do I think better, so any AI tool becomes powerful in my hands?” That is the shift. And those who make it will not be replaced by AI — they will lead with it.

In the Age of AI, Trust Becomes the Real Currency As Sam Altman pointed out, AI creates so much information that everyone suddenly looks like an expert. With one prompt, anyone can generate answers, strategies, and even insights that once took years to acquire. This creates a deeper problem. It is no longer about whether information is available. It is about whether we can trust the information, and more importantly, the person behind it. If we look at human evolution, we started from almost no information. Knowledge was scarce. Trust was simple. Whoever provided information was usually an expert. Over time, we moved into the information age, and now we are in the over-information age. Today, information is cheap. Expertise is diluted. AI makes everyone sound right. So what can we still trust? The answer is no longer information. The answer is people. Can this person do what they say? Have they done it before? Do their actions match their words? This is where older people gain a natura...

The great inversion of the AI era In past eras: Skills were scarce Knowledge was power Technical mastery created advantage In the AI era: Technology accumulates Capabilities become cheap Execution is automated Answers are abundant This is why Altman’s view feels counter-intuitive but accurate: the most valuable things are no longer technical abilities. What AI makes cheap (and therefore replaceable) AI ill outperform humans at: Pattern recognition at scale Generating text, code, images, plans Optimizing known processes Reproducing best practices Imitating expertise So who gets eliminated? People who wait to be told what to do People whose value is “I know how to do X” People who follow playbooks without questioning them People who outsource judgment to systems These roles don’t disappear overnight—but they quietly lose leverage. What AI cannot fully replace Altman keeps circling back to three human capacities. Not because AI lacks intelligence—but because these sit above intelligence. ...

Most people spend their lives training to win at standardised work. Clear rules. Known answers. Measurable benchmarks. That is exactly the kind of work AI devalues first. What remains valuable now is work that is: – messy – human – ambiguous – dependent on trust – shaped by judgment, intuition, and meaning Grades matter less. IQ matters less. Pure intelligence is becoming cheap. AI is the engine. Humans must provide the direction. The winners won’t be the smartest. They will be the ones who can: • define the right problem • ask better questions • architect systems • lead humans and machines together When intelligence becomes cheap, thinking is no longer the advantage. Meaning is the advantage. Direction is the advantage. Leadership is the advantage. That’s why Love Intelligence (LQ) matters. LQ gives us meaning when answers multiply. Direction when options explode. Leadership when expertise alone is no longer enough. With LQ, you don’t compete with AI — you lead it. And that’s why, in ...

This fear is real — and it is rational. But it is also incomplete. AI is not replacing humans. AI is replacing tasks, roles, and behaviours that have already lost their human edge. This is exactly where Love Intelligence (LQ) becomes the stabilising force. Let me explain clearly and calmly, without hype. Why the Fear Exists (and Why It Feels So Strong) The billboard says: “Stop Hiring Humans.” That triggers fear because many people unconsciously built their identity on: being efficient being accurate being knowledgeable being fast being compliant AI now does all of that better. So the fear is not really: “AI will replace humans.” The deeper fear is: “If what I do can be automated, what value do I still have?” How Love Intelligence (LQ) Directly Addresses This Fear LQ does not fight AI. LQ moves the human to a level AI cannot reach. 1. LQ Redefines Human Value Beyond Productivity AI is good at output. Humans are irreplaceable at: trust-building moral judgement emotional courage meaning-...

AI has accelerated decision-making, automation, and performance measurement. What it has not improved is trust, alignment, or human judgment. As a result, many organizations are facing: Technically capable leaders who cannot mobilize people Faster execution with higher internal friction Smart strategies that fail due to emotional blind spots This is not a skills gap. It is a human intelligence gap. The Insight When pressure increases, leadership weaknesses surface. AI does not replace leaders. AI exposes weak leadership. The next competitive advantage is not IQ or digital capability. It is Love Intelligence (LQ) — the ability to lead with Care, Courage, and Connection. The Framework: Love Intelligence (LQ) Care Builds trust, psychological safety, and clarity of intention. Courage Enables decisive action under uncertainty and moral pressure. Connection Aligns people, systems, and purpose for sustained execution. LQ is not “being nice.” It is precision leadership in complex environments.

People say nowadays everyone writes using AI, and everyone sounds so perfect, and no one is real and authentic. Some people now resort to writing with grammar mistakes and Singlish to avoid being labelled as AI written. The truth is, AI is just reflecting the user's patterns and data. When the user uses AI regularly and instructs AI to write in their human and 'imperfect' tone and language, no one can tell that AI is writing for the person. Authenticity isn’t about avoiding AI or adding intentional errors.  It’s about showing up as yourself. AI is just a tool: like a camera, a brush, or a pen. What matters is who’s holding it and how it’s used. When you: Use your own stories Share personal experiences Inject your quirks, tone, and even pauses Guide AI with clear intent and emotion …the result feels unmistakably you. Not AI. People can tell when something is written with heart, just as they can sense when it’s empty or polished to the point of being fake.  So instead of worr...

A few years ago, there was a project manager I coached. Brilliant guy, technically perfect. He used every tool: AI, data, dashboards, automation, yet his team was falling apart. Deadlines slipped, people avoided him, tension filled the room. One day he said to me, “Andy, I don’t understand. I have all the skills. Why is nothing working?” I asked him one question: “When was the last time you showed someone you cared?” He went quiet. The next week, he tried something simple. He asked a stressed teammate, “Are you alright? How can I support you?” He apologised to another for being harsh. He thanked a third person for staying late. Within a month, the team performed better than ever. The same tools. The same AI. The same systems. The only difference was love: the courage to care, the courage to connect. And I told the young engineers that day: “You can let AI think for you. But only you can make people feel safe, valued, and inspired.” That is Love Intelligence. Not soft. Not romantic. It ...

What you see in the image are human meta-skills, not technical features. AI can support every one of them, sometimes brilliantly, but it cannot replace the human essence behind them. Here’s the honest view: 1. Creative thinking & experimental thinking Gemini 3 and ChatGPT 5.2 can generate ideas, remix concepts, propose experiments, and spark creativity. But the original spark, the taste, the intuition, the emotional truth — that still comes from you. 2. Analytical thinking & engineering thinking Both models are extremely strong at breaking down problems, building logical chains, troubleshooting, and simulating engineering scenarios. Still, without human judgement and real-world context, AI can make “confident mistakes”. 3. AI/Data literacy They can teach AI and data literacy, explain concepts instantly, and help you practise. But true literacy means you can question, interpret, and challenge AI outputs — that part is human. 4. Ethics & governance in AI/Tech AI can explain f...

Before AI, humans spend so much time on tasks that now seems silly, because AI can do them in just a split of a second.  What we consider valuable are now worthless, especially tasks like: - analysing - projections, budgeting, scenario planning - linking ideas, sorting our ideas, generating ideas - designing, creating videos - writing articles like this Now with the time spared, humans can do real human work, including: - doing nothing, for this will inspire creative ideas - connecting hearts - dancing, singing, to our hearts' contents - strategy discussions with all kinds of people I am happy with this change, what about You? 

In the AI Era, What Can We Still Trust? Today, everything can be created easily — reports, proposals, strategies, even “expert opinions.” We have reached a point where top consulting firms like McKinsey and Deloitte have been caught using AI tools to generate client deliverables… and still charging millions. Numbers give comfort, but not truth. every promise contains both yin and yang. A bright projection hides a shadow. A strong guarantee hides uncertainty. A perfect plan hides unseen forces. If projections cannot be fully trusted… If AI-generated reports cannot be fully trusted… Trust Does Not Come From Intelligence. not once, not twice, but consistently demonstrated over a long period of time. History doesn’t lie.  Your behaviour over the years reveals who you really are. older people have a major advantage. AI Makes Knowledge Cheap, And the older you are, the more of these assets you carry. AI helps them work faster, but it does not replace what makes them valuable...