Merely deploying AI tools like Copilot to employees offers minimal value. The real revolution is using AI to re-engineer core processes from the ground up. For example, AI can reduce a six-week credit file preparation to 14 minutes, forcing a fundamental rethink of roles and requiring massive reskilling efforts.
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Instead of merely 'sprinkling' AI into existing systems for marginal gains, the transformative approach is to build an AI co-pilot that anticipates and automates a user's entire workflow. This turns the individual, not the software, into the platform, fundamentally changing their operational capacity.
AI's primary value isn't replacing employees, but accelerating the speed and quality of their work. To implement it effectively, companies must first analyze and improve their underlying business processes. AI can then be used to sift through data faster and automate refined workflows, acting as a powerful assistant.
Notion's CEO compares current AI adoption to swapping a water wheel for a steam engine but keeping the factory layout the same. The real gains will come from fundamentally rethinking workflows, meetings, and hierarchies to leverage AI that works 24/7, rather than just layering it onto existing processes.
A critical error in AI integration is automating existing, often clunky, processes. Instead, companies should use AI as an opportunity to fundamentally rethink and redesign workflows from the ground up to achieve the desired outcome in a more efficient and customer-centric way.
The Goldman Sachs CEO differentiates between two types of AI adoption. Giving employees AI tools to make them more productive is relatively easy. The much harder, yet more impactful, challenge is fundamentally re-engineering long-standing, complex processes like customer onboarding from the ground up.
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 most significant gains from AI will not come from automating existing human tasks. Instead, value is unlocked by allowing AI agents to develop entirely new, non-human processes to achieve goals. This requires a shift from process mapping to goal-oriented process invention.
Beyond individual productivity gains, AI's strategic enterprise value is its ability to re-engineer core operations. This automation creates significant efficiency savings, unlocking capital that can be reinvested into strategic technology spending without negatively impacting financial returns.
The greatest value of AI isn't just automating tasks within your current process. Leaders should use AI to fundamentally question the workflow itself, asking it to suggest entirely new, more efficient, and innovative ways to achieve business goals.
Just as electricity's impact was muted until factory floors were redesigned, AI's productivity gains will be modest if we only use it to replace old tools (e.g., as a better Google). Significant economic impact will only occur when companies fundamentally restructure their operations and workflows to leverage AI's unique capabilities.
