Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
AI AND humans. Not AI OR humans.
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When the AI wave first hit, it was all about chatbots, and tech CEOs promised a future where humans and AI would work together to deliver better outcomes than humans could manage alone. Then, as AI progressively became better, businesses started to question whether they needed human workers at all, and the first wave of AI-driven redundancies hit. The tech CEOs suddenly started changing their tune and began warning of the impending white-collar job-pocalypse, especially following the advent of AI agents. But something interesting happened on the way to the future. It turned out that AI agents aren’t cheap and that experienced humans are capable of insights AI can’t manage alone. Businesses that had previously fired human staff in favour of AI quietly started hiring the humans back, and the tech CEOs’ tune changed once again. So now we’re back where we started, with AI and humans working together once again, but with technology vastly superior to what it was when the cycle first began. Victor Coimbra has seen this future up close. As Partner and CTO at Artefact, the world’s largest pure-play AI consulting firm, he has helped global enterprises build what he calls hybrid agentic organisations - where humans provide the judgment, creativity, and context while AI agents provide the speed, memory, and execution power. In the latest episode of Value Driven Data Science, Victor joins me to share what hybrid agentic organisations actually look like in practice, and what data scientists need to do to position themselves at the centre of them. You’ll discover:
The future of work isn’t AI OR humans. It’s AI AND humans. Listen now on Apple Podcasts or Spotify, or click the link below: Episode 121: What Hybrid Agentic AI Organisations Mean for Data Science Talk again soon, Dr Genevieve Hayes |
Data Science Impact Algorithm
Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
Data science is obsessed with scalability. Can your model handle bigger data received at a higher velocity than ever before? So, it's ironic that some of the best things you can do for your data science career don't actually scale. Genuinely understanding the problems of a single stakeholder - doesn't scale. Building a reputation as an expert in your domain - doesn't scale. Delivering recommendations that actually get acted on - doesn't scale. AI has made it easier than ever to produce...
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