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 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.

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.

Adding AI tools to current processes yields only incremental efficiency. To achieve significant business impact, leaders must rebuild their entire go-to-market system—roles, workflows, and data flow—with AI at the core, not as an add-on.

The true power of AI is unlocked by adopting an "AI First" approach. This means completely redesigning workflows with AI at the core, rather than simply using AI to accelerate existing processes. This shifts employees' roles from performing tasks to managing the AI agents that do the work.

The greatest leverage from AI comes not from accelerating individual tasks, but from improving information flow between teams. Use AI to create a "common brain"—a central repository of project knowledge and goals—to ensure alignment and drive efficiency at critical handoff points.

To maximize AI's impact, don't just find isolated use cases for content or demand gen teams. Instead, map a core process like a campaign workflow and apply AI to augment each stage, from strategy and creation to localization and measurement. AI is workflow-native, not function-native.

The productivity boom from AI won't materialize from workers simply using new tools. Citing historical parallels with electricity and computers, the real gains are unlocked only when companies fundamentally restructure their operations and business models around the technology.