Procter & Gamble's Chief Information Officer revealed a massive AI and data infrastructure that could offset near-term cost pressures—but Wall Street hasn't priced it in yet.

What happened: P&G's CIO Seth Cohen detailed the company's AI operations at a June 10 conference, including a 35-petabyte consumer behavioral database, digital twins that have cut R&D timelines from five-plus years to under six months, in-house generative AI for advertising, and manufacturing automation running unattended operations. The company logs over 2 million consumer touch points per year from connected devices and uses AI to optimize media buying and financial forecasting.

Why it matters: The market has focused on a $1 billion（約1600億円） after-tax oil cost headwind for fiscal 2027, which caused P&G stock to fall 16.15% from its 52-week high as of June 3. However, these AI and automation improvements represent structural cost reductions that could offset commodity pressure on gross margin—a benefit the Street has not yet modeled into P&G's earnings outlook. P&G trades at 15.52x NTM EV/EBITDA, a premium to peers like Reckitt Benckiser at 10.24x and Kimberly-Clark at 10.95x, which the company justifies through technology differentiation.

What to watch: P&G's ability to demonstrate that AI-driven margin gains materially offset the $1 billion（約1600億円） oil headwind in coming quarters. The company also plans to expand AI-based financial forecasting across R&D, selling, and product supply, signaling that cost reduction is still in early stages.