Kirill Eremenko

Most international grads don’t realise this, but Australia rewards the outspoken, not the qualified. You can be the smartest person in the room. You can have the highest GPA, the toughest degree, the most technical mind. None of it matters if you speak softly and wait your turn. Because in Australia, confidence is competence. Social presence is leadership. And the person who speaks first is almost always seen as the one who knows what they’re doing. This is why so many international grads feel “invisible”. It’s not a skills problem. It’s not a visa problem. It’s not a hiring problem. It’s a behaviour mismatch. You grew up in a culture where you respect the hierarchy, wait to be invited in, and try not to step on toes. Then you arrive in a country where the loudest person gets listened to, the most likeable person gets promoted, and the one who participates without being asked becomes the default leader in the room. If you stay quiet, Aussies don’t see humility. They see absence. And it holds people back more than any technical gap ever will. If you want to compete here, you need to adapt. Not your accent, not your identity. Your presence. Speak earlier. Speak louder. Speak with certainty even when you’re still figuring things out. Australia doesn’t reward the person who knows the most. It rewards the person who acts like they belong. And that is the shift that changes everything.

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If you’re an international grad in Australia, you’re sitting on a goldmine, and most of you don’t even see it. Australia is years behind in AI adoption. While the U.S. and Europe are building AI-first economies, most Australian companies are still stuck in pilot mode. Meetings. Committees. “Ethical frameworks.” But here’s the upside: when a market lags, individuals who move fast can dominate. You don’t need to compete with Stanford engineers here; you just need to outpace local inertia. Here’s how: 1. Exploit the skills gap. Learn practical automation now. OpenAI APIs, LangChain, Python scripting, Ollama, and bring it into your workplace or internship. You’ll look like the future while everyone else is catching up. 2. Stop waiting for an “AI role.” In most Australian firms, the job title doesn’t exist yet. So create it. Build an internal chatbot, automate reporting, or generate client insights using AI. Once you show ROI, the role forms around you. 3. Bridge two worlds. You understand both global innovation and local hesitation. That’s your edge. Translate cutting-edge tools into safe, compliant, usable solutions that Australian execs trust. 4. Be louder. Most people underestimate how fast credibility compounds when you share projects publicly. Document what you build. Post demos. Write about lessons learned. Visibility builds gravity. You came to Australia for opportunity. AI is the biggest one you’ll ever get. The only question is whether you’ll wait for permission or use the lag to lead.

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We’re entering the most asymmetric job market in decades. AI won’t just take jobs. It will split the market in two. Those who move up the value chain, and those who get left behind. Australia could lose over $100 billion if we get this transition wrong. A new government report from Jobs and Skills Australia makes it clear. Routine roles are collapsing first. Data entry. Admin processing. Anything predictable. But here’s what nobody is talking about. Workers who understand and apply AI are not being replaced. They are being rewarded. According to PwC’s 2025 AI Jobs Barometer, AI-exposed roles already earn a 56% wage premium. The people who lean into AI, who use it to multiply outcomes, are winning. Full report here: https://lnkd.in/gyDFBbB2

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New blog post: Using deep learning in PyTorch on rainfall data to predict Australian area remoteness Who would have thought I'd be back with another post so soon! Not me, that's for sure. Anyway, in this episode, I continue my exploration of rainfall data for each ABS SA2 in Australia by computing a set of time-series features and then using them to train deep neural networks in PyTorch to classify whether an unseen rainfall time series is from a major city, inner/outer regional Australia, or remote/very remote Australia. What's more, I switch between R and Python within the one document, highlighting the power of multilingual integration in modern markdown! I found that time-series features which capture temporal dynamics in rainfall can meaningfully classify the remoteness of ABS SA2s, which suggests that there are differences in temporal patterns of rainfall unique to the five different remoteness classifications. This is interesting, because it highlights that looking beyond simple/intuitive hypotheses such as 'cities probably get more rain than the outback' can reveal potentially novel insights about the differential patterns. This could lead to further inquiry about whether these dynamics shift over time (i.e., due to climate change) or other important scientific questions. In any case, if nothing else, deep learning is awesome and I had fun! Please check out the post via the link below if you are interested. https://lnkd.in/giQ-UHKR #statistics #deeplearning #machinelearning #climate #timeseries

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I just read this article in the The Australian Financial Review: “CBA U-turns on AI job cuts, calls back humans” LINK-> https://lnkd.in/gWNiTEtj It’s a timely reminder that while AI can improve efficiency, it should never come at the expense of humanity!!! Commonwealth Bank discovered that chatbots and voice-bots can handle routine enquiries, but when things get complex or emotional, people want people. They’ve now brought staff back to meet those needs. The lesson? AI should empower, not eclipse. Human-centred approaches build trust, resilience, and better outcomes!!! This is a lesson for all industries but in education it is acutely important because the development of our youth requires more than curriculum efficiency. A human/ai balance is what is needed moving forward. Thanks CBA for the lesson!

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🤖 How can AI help Australia’s weak productivity? The results are in and they don’t look great. The latest estimates of Australia’s productivity for 2024/25 are still dismal. On the ABS latest figures, market sector multi-factor productivity fell by 0.5% in 2024/25. The RBA’s recent rate hike should put this issue front-and-centre. The recent surge in inflation, is not because growth is strong – it’s not. It is because of Australia’s low economic growth ‘speed limit’, which is due to persistent weak productivity. Pro-growth reforms are needed, as a more competitive and efficient economy would encourage businesses to invest and innovate, which is where productivity gains typically come from. One way this could happen is through businesses adopting AI tech solutions. A deeper look shows that Australia’s AI adoption is positive, but it has been slow and will likely to take time to substantively boost productivity. A faster pace of adoption could help. For more ready my latest Australian Economic Comment, available to all 👉 http://grp.hsbc/6043hU4lV #HSBCResearch #Australia

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AI Ethics Index 2025: https://lnkd.in/gWHrNFxH What jumped out - AI is now a top-tier ethical concern for Australians—right alongside cost-of-living and cybersecurity. - Corporate AI is under scrutiny. People want evidence: clear purpose, data lineage, pre-release risk tests, and post-deploy monitoring. - Healthcare is the relative bright spot—accepted when it augments clinicians, not when it replaces judgment. - Financial services: Trending down ethically—which is a clear signal that more work to do to turn policies into auditable evidence across the industry. - Culture watch: “promoting a respectful and diverse work culture” slipped in priority—a warning sign. Ethics without culture is cosmetic; leaders at all levels need real introspection My take: If it isn’t defined, versioned, tested, and explainable, it isn’t “go-live” ready. #AIethics #ResponsibleAI #AIinFinance #Superannuation #DataGovernance #RiskManagement #TrustByDesign #Leadership

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Data: not valuable in its raw form; get the foundations right - let it speak your language. Great to join this panel at Digitalisation & AI in Mining Australia with Patrick Wicki, David Cavanagh, Peter Walker FAusIMM, FIEAust, and Rob Johnston - a group who’ve all had to turn digital theory into something that actually works on a mine site. A few themes kept surfacing: 🔹 Standardisation isn’t rigid: it’s semantics. The biggest failures in AI and digital projects aren’t dirty data; they’re ambiguous data. Standardisation today means aligning ontologies - shared definitions of events, assets, units, and processes - so every team speaks the same operational language (and the AI does too!). 🔹 Knowledge graphs are the new backbone for mining. Once those ontologies are connected, you get a knowledge graph: a systems-thinking model of your operation. It shows dependencies, context, causal links, and where value (or risk) actually sits. It’s the difference between data stored and data understood. 🔹 Change management is the real moat. You can have a perfect architecture and still fail if frontline teams don’t trust it. The biggest wins often come from co-designing workflows, simplifying decisions, and showing crews how this removes friction - not adds it. 🔹 Safety wins are the quickest wins. A people first approach makes it easier to surface leading indicators, connect weak signals, and spot patterns you’d normally miss. Many of the fastest adoption stories start with safety, because the value is immediate and the trust is high. 🔹 Operational value beats strategy every time. People don’t rally behind roadmaps; they rally behind getting their job done better. A reduced delay code set, a cleaner shift report, or a predictive alert that actually matters can move a team faster than any “digital transformation program”. Huge thanks to the organisers (Mining Innovation Network - Giulia Jalmerot - Timarco) and fellow panellists for a grounded conversation. Mining doesn’t need more data: it needs systems that deliver value in the field. #MiningInnovation #DigitalMining #AIinMining #OperationalExcellence #Safety #Ontologies #KnowledgeGraphs #ChangeManagement #SystemsThinking #DataStrategy Unearthed Bentley Systems CITIC Pacific Mining Integrated Energy Pty Ltd

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