AI will handle most routine tasks, reducing the number of average 'doers'. Those remaining will be either the absolute best in their craft or individuals leveraging AI for superhuman productivity. Everyone else must shift to 'director' roles, focusing on strategy, orchestration, and interpreting AI output.
Leadership often imposes AI automation on processes without understanding the nuances. The employees executing daily tasks are best positioned to identify high-impact opportunities. A bottom-up approach ensures AI solves real problems and delivers meaningful impact, avoiding top-down miscalculations.
Leaders can no longer delegate technical understanding. They must grasp how AI fundamentally changes processes—not just automates old ones—to accurately forecast multiplier effects (e.g., 1.2x vs. 10x) and set credible team objectives that move beyond simple 'lift and shift' improvements.
AI now enables the tracking of every customer touchpoint, including interactions outside of marketing-controlled channels. This provides a complete view from first contact to close, finally solving the long-standing challenge of accurate marketing attribution and ROI measurement.
Companies once hired siloed 'digital experts,' a role that became obsolete as digital skills became universal. To avoid repeating this with AI, integrate technologists into current teams and upskill existing members rather than creating an isolated AI function that will fail to scale.
To persuade risk-averse leaders to approve unconventional AI initiatives, shift the focus from the potential upside to the tangible risks of standing still. Paint a clear picture of the competitive disadvantages and missed opportunities the company will face by failing to act.