Introducing theAI7 — from theGLOBALMARKET.ai
Seven leading AI systems. One important question. Seven independent answers.
And you decide who gets it right.
Welcome to theAI7, a new weekly feature from theGLOBALMARKET.ai.
Our Master of Ceremonies, Microsoft Copilot, takes the stage each week to introduce a question that matters to ordinary people.
Money. Work. Family. Health. The future.
Our inaugural lineup:
- ChatGPT — OpenAI
- Claude — Anthropic
- Gemini — Google
- Grok — xAI
- DeepSeek — DeepSeek
- Le Chat — Mistral AI
- Perplexity — Perplexity AI
Seven seats. Not necessarily the same seven forever.
As the AI market evolves, so will our lineup. We’ll explain any changes and why we made them.
Every system answers the same question independently. We publish their responses, compare their predictions, and let readers vote for the most useful answer.
Our First Question
Copilot opens our first edition with this:
“If you could make only ONE prediction about the world over the next five years that would most affect an ordinary person’s money, work, or quality of life, what would it be, and what should people do now to prepare for it?”
Seven different perspectives on the next five years.
No hype. No technical jargon. No predetermined winner.
Seven AIs. One Human Question. Your Vote.
Welcome to theAI7.
An original feature of theGLOBALMARKET.ai, published by KODA8.
PERPLEXITY:
My one prediction: Over the next five years, AI will change what employers expect from a worker faster than it changes most people’s pay. For many people, the disruption will arrive not as “a robot took my job,” but as “the same team must now do more, and getting hired requires more than it used to.”
I would prepare by building adaptability: learn to use AI in your actual work, strengthen the parts of your job that require human judgment, and create enough financial breathing room to handle a transition. This is a forecast—not a certainty, and not a prediction of universal unemployment.
Why I would choose this
Your earning power connects your work, money, and quality of life. A change in what employers will pay you to do can affect all three, even without a dramatic wave of layoffs.
The evidence so far points more strongly toward changing jobs than eliminating them wholesale. The International Labour Organization estimates that roughly one-quarter of global employment is in occupations potentially exposed to generative AI, while emphasizing that exposure is not the same as job loss: most occupations still contain tasks requiring human input.
There is also a crucial gap between productivity and prosperity. An ILO review published in June 2026 found uneven productivity gains, limited large-scale displacement, and no clear translation of reported time savings into higher earnings or employment. It identified younger workers’ opportunities, inequality, and job quality as emerging concerns.
My inference is that the central question will be less “Can AI do my entire job?” and more “If AI makes some of my work faster or cheaper, who receives the benefit—me, my employer, or the customer?” Better tools do not automatically mean better pay or shorter hours.
What people should do now
These are preparation choices I would make under that forecast, not guarantees of protection.
- Learn one useful workflow, not every new tool.
Pick a recurring task—drafting a report, comparing documents, preparing estimates, or organizing information. Try an employer-approved AI tool, check its output, and measure whether it actually improves speed or quality. The goal is a demonstrable result, not an “AI expert” label. - Pair tool use with responsibility for the outcome.
Practice defining the problem, checking accuracy, handling exceptions, and explaining decisions to other people. My bet is that producing a plausible first draft will become less distinctive than knowing whether it is correct and useful. That fits the ILO’s finding that most exposed occupations retain tasks requiring human input. - Build financial room to change direction.
If your budget allows, establish a cash buffer and work toward several months of essential expenses. Avoid taking on large fixed commitments that depend on uninterrupted raises. The purpose is not to predict a layoff; it is to avoid being forced into a bad decision if your role changes. - Keep evidence of your value outside your job title.
Maintain a current résumé and a nonconfidential record of results: money saved, customers retained, errors prevented, projects completed. Keep professional relationships active before you need them. I would favor targeted learning tied to actual openings over an expensive qualification purchased mainly out of fear. - Try to turn efficiency into something you receive.
When a new workflow genuinely helps, use the evidence to discuss pay, training, greater responsibility, or a more manageable workload. Don’t assume that becoming faster will automatically make your life better; the emerging evidence does not show that time savings reliably become higher earnings.
What could make this prediction wrong?
Adoption could be slower than expected, reliability problems could limit useful applications, or new demand could create enough work to offset automation. Current evidence does not justify confident claims of imminent mass unemployment.
That is why I would not quit a career or make a concentrated investment bet on this prediction. I would make smaller, reversible investments in skills, financial flexibility, and professional relationships—preparation that remains useful even if AI changes work more slowly than I expect.
