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A common mistake is applying new technology to solve old, already-automated problems. True value comes from using new tech, like AI, to tackle entirely new challenges. Incumbent systems that work well, even if based on older technology like mainframes, are rarely swapped out, creating opportunities when the market overestimates their demise.

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A common mistake leaders make is buying powerful AI tools and forcing them into outdated processes, leading to failed pilots and wasted money. True transformation requires reimagining how people think, collaborate, and work *before* inserting revolutionary technology, not after.

Faced with an "AI mandate," many companies try to force-fit AI onto their current offerings, leading to failure. The correct first step is a fundamental assessment: is this problem even a good candidate for AI, or does the entire product need to be reimagined from the ground up?

The biggest gains from AI come not from automating steps in an existing process, but from starting with the desired outcome and co-creating a new workflow with AI. This "first principles" approach leverages AI's capabilities far more effectively than piecemeal automation.

AI isn't a technology to be applied to existing processes. It's a foundational layer, like an operating system, that fundamentally reshapes how businesses create value, make decisions, and operate. This perspective forces a complete rethink of strategy, not just an upgrade.

Companies can either augment existing processes with AI for incremental efficiency (e.g., co-pilots) or completely redesign workflows. While augmentation is common, the most transformative value and disruptive business models will emerge from a clean-sheet redesign of how work is done.

Drawing a parallel to the slow adoption of PCs in the 90s, Boris Churney argues companies won't see AI productivity boosts by simply layering it onto old workflows. The biggest benefits come from placing AI at the core of the business and redesigning processes around its capabilities, eliminating old bottlenecks entirely.

The market is rejecting 'lame co-pilots' that provide minor workflow improvements for an extra fee. Successful AI products create entirely new, powerful use cases and deliver substantial, tangible value on day one, justifying their place in the budget.

The most common failure in AI implementation is treating it as a technology project to automate existing workflows. True success requires a transformational mindset, using AI as a catalyst to completely redesign how work gets done and how human and AI agents collaborate.

The biggest mistake in AI adoption is simply automating an existing manual workflow, which creates an efficient but still flawed process. True transformation occurs when AI enables a completely new, non-human way of achieving an outcome, changing the process itself rather than just the actor performing it.

The historical adoption of electricity in factories shows that true productivity gains came from redesigning the factory floor, not simply replacing steam engines. Similarly, companies must fundamentally re-engineer processes around AI to unlock its transformative potential.

New Technologies Excel at New Tasks, Not Replacing Working Systems | RiffOn