Why Using AI to Do Other People's Jobs Is Bad Strategy
With Great Power Comes Great Responsibility: Why AI Should Amplify Collaboration, Not Replace It
Uncle Ben got it right. With great power comes great responsibility—and AI gives us more power than we've ever had in the workplace.
Give someone access to generative AI and suddenly they're convinced they can write marketing copy, design user interfaces, build product roadmaps, and maybe run financial projections while they're at it. The tool is powerful enough to make it all feel possible.
But here's the critical question every product leader, manager, and team member needs to ask: just because we can do something with AI, should we?
AI as an Amplifier, Not a Replacement
AI excels at one thing: accelerating expertise. When used correctly, it's a force multiplier for what you already do well.
A designer using AI to iterate faster on concepts? That's strategic leverage.
An engineer using it to debug code or generate boilerplate? That's pure efficiency.
A product manager using it to synthesize research or draft requirements? That's working smarter.
These are examples of AI amplifying core competencies. You're still bringing the expertise, judgment, and context. AI is just helping you do it faster.
The Collaboration Trap
The problem starts when we use AI to bypass collaboration entirely. When we prompt our way around the expertise of designers, engineers, researchers, or operations teams, we're not being innovative—we're being short-sighted.
The best product work happens at the intersections. It requires healthy tension, constructive debate, and the humility to recognize what we don't know. These moments of friction aren't inefficiencies to eliminate. They're where the real value gets created.
When we use AI to smooth over these intersections—to avoid the hard conversations with specialists who actually own their disciplines—we end up with work that looks complete but fundamentally lacks depth. It's productivity theater, not real progress.
The Real Cost of AI Overreach
Using AI to approximate what a specialist would bring has two hidden costs:
First, the output suffers. You get work that's technically complete but missing the nuance, context, and craft that comes from genuine expertise.
Second, and more importantly, you're no longer doing your job well either. You're spreading yourself thin across multiple domains, delivering mediocre versions of several jobs instead of excellence in your own.
The question isn't whether AI can help you do more things. It's whether using it that way actually serves the outcome you're trying to achieve.
If you're spending your time prompting AI to replicate what a specialist would bring to the table, you've made a strategic error. You've confused capability with wisdom.
My Thoughts on Using AI Responsibly at Work
Amplify your strengths. Use AI to get exponentially better at what you're already good at. Double down on your expertise.
Respect boundaries. When you need design thinking, talk to a designer. When you need technical architecture, loop in engineering. AI can help you ask better questions, but it shouldn't replace the conversation.
Stay humble. The most powerful use of AI might be helping you articulate what you don't know so you can bring in the right people faster.
The Bottom Line
With great power comes great responsibility. AI gives us unprecedented ability to move fast and generate output. But using it responsibly means knowing when to amplify our own expertise and when to step back and collaborate.
Use AI to become exceptional at what you do best. Use people for everything else.
That's not old-school thinking. That's just good strategy.
#AI #ProductLeadership #Collaboration #ArtificialIntelligence #TeamWork #ProductManagement #Leadership
