The AI Boomerang
By Brett Dyess
There's an interesting trend emerging in the AI economy. Companies invest in artificial intelligence to automate work, eliminate positions, and improve productivity. Then something unexpected happens.
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By Brett Dyess
There's an interesting trend emerging in the AI economy. Companies invest in artificial intelligence to automate work, eliminate positions, and improve productivity. Then something unexpected happens.
Read the essayBy Brett Dyess
Talent Signal recently featured my perspective on AI in recruiting and the independent workflows I’ve been building and testing.
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Oracle, Cielo and Dayforce point toward a different recruiting operating model—one that connects intelligence, AI workflows, human judgment and accountable action.
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The requisition may be the last talent signal you see. Talent Advisor 2.0 connects business signals, recruiting conversations and human judgment to earlier workforce decisions.
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For decades, workforce planning has started with a simple question: how many people do we need? As work is increasingly performed by a mix of employees, AI agents, automation, and external partners, the better starting point may become what work needs to happen.
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KPMG’s 2026 U.S. CEO Outlook found 89% of surveyed CEOs expect to grow headcount over the next three years — while redesigning roles for human-AI collaboration. The story is more complicated than “AI is taking jobs.”
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Today I gave my sourcing agent a real recruiting problem. From job description to a completed candidate slate and email ready to send: 14 minutes.
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As AI moves from answering questions to taking actions, an AI agent being capable of doing something does not mean it should have the authority to do it.
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Google announced AI coworker agents with their own email addresses. I gave Jarvina an inbox last week. The timing made me laugh. The implications for work deserve a closer look.
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I’ve used Google Voice for recruiting calls and texts for about fifteen years. The more interesting question is where the candidate conversation lives.
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What if we’ve been searching for talent in the wrong order? Start with the work, look for capability, and use job titles as context.
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The next recruiting breakthrough may be less about screening more applications and more about understanding capability before the funnel fills up.
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Most people are still using AI like a chatbot. What happens when you stop starting over? The short take on building a custom AI — and seven levels of customization.
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I use AI every day. But most people are still using it like a chatbot — and dramatically underestimating what happens when you start building your own AI.
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The people who make a business strategy possible do not necessarily work for that business. Workforce planning needs to follow the capability beyond the org chart.
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For years, the AI talent conversation has focused on the obvious people. The next AI talent shortage may have surprisingly little to do with building models.
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For a while, I thought I was pretty good at using AI. Then I realized I was still treating one of the most transformative technologies I've encountered like a really sophisticated search box.
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Apparently, I may have been thinking too small about AI, work, and the future of human civilization.
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One recruiter can mistakenly reject a qualified candidate. An algorithm can potentially make the same mistake thousands of times.
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When the business needs a new capability, do we need to hire it — or can we build it? AI is making that question increasingly important.
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Recruiting's transactional model is disappearing. In the AI era, the recruiter is evolving into a Talent Advisor — part workforce strategist, part market analyst, part AI-enabled talent architect.
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