The C-Suite Moves Shaking Up TV in 2026, From VideoAmp’s CEO to Paramount Exits
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What a New AI Disruption Index Can Tell You About Your Brand’s Future
This post was created in partnership with Moloco Are Google AI overviews wreaking havoc on your brand’s discovery strategy? How likely is it that AI might make your brand’s offers […]Read More
Not trying very hard
This is not the same as not working very hard. In fact, they’re very different.
We’ve been indoctrinated to avoid trying hard (too risky and emotionally fraught) and to resign ourselves to working hard (held up as a virtue).
People who work in productivity-focused jobs where they follow the manual work very hard. If you buy a Subway franchise, you’re buying years of hard work–the more hours you put in, the better your profits. If you work on an assembly line–making chocolate or writing code–the boss pushes you to work harder and harder.
On the other hand, there are projects where the outcomes are less certain and where the manual isn’t as complete. In these sorts of projects, we need to use our judgment and insight. We do things that might not work. There are few prizes for longer work, but plenty of upside for better work.
We’re surrounded by businesses staffed by hard-working people who have been trained to not try very hard. So they stick with the policy and avoid innovation, customer delight and connection.
Ironically, when it’s our turn to be the customer, we often seek out precisely the opposite. Humans are drawn to folks who care enough to try a bit harder.
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Make and take
In a world of automation, AI and outsourcing, what exactly do we do for a living?
Perhaps we make decisions.
And what’s in short supply?
A willingness to take responsibility.
If you choose to sign up to make and take, there have never been more tools or more leverage available to you.
AI is old news. Generative AI is the future.
The term Artificial Intelligence (AI) is well known, often evoking futuristic movies like Robocop, Terminator and The Matrix. Yet what many don’t realize is that AI has been part of our lives for decades. When you finish watching a movie on a streaming platform and instantly see recommendations for similar content, that’s AI. When you’re shopping online and an entire page of suggested products appears, that’s AI. Even the digital ads you see are powered by machine-learning algorithms designed to optimize engagement, clicks, and conversions. Companies have relied on AI rule-based automation, routines, and machine-learning algorithms for years to power their systems and business processes. So when…
This story continues at The Next WebRead More