Siemens and P&G Cracked the AI Code

KEY INSIGHTS:

• The DIP-AI framework enhances AI project success by aligning business objectives with technical capabilities, reducing the risk of misalignment and improving project outcomes.
• Implementing the DIP-AI framework can lead to higher stakeholder satisfaction and successful development of AI solutions, as evidenced by a case study that resulted in a viable product.
• Organizations that adopt the DIP-AI framework can gain a competitive edge by fostering collaboration and clarity in AI projects, positioning themselves for future innovation and market leadership.

KEY INSIGHTS:

• Over 80% of firms report no significant earnings impact from Gen AI, highlighting a critical gap between adoption and realized value that CEOs must address.
• Implement structured experimentation, as demonstrated by Siemens and Procter & Gamble, to refine Gen AI adoption strategies and accelerate learning while minimizing risks.
• The slow integration of Gen AI presents a future risk of falling behind competitors; proactive experimentation can unlock its full potential and enhance market positioning.

KEY INSIGHTS:

• Global IT power capacity is projected to grow by 13% to 20% annually through 2030, necessitating strategic infrastructure adaptations to support AI workloads, which will dominate compute tasks.
• Hyperscalers are prioritizing capital efficiency and resource deployment; CEOs should reassess their data center strategies to enhance operational precision and competitive advantage.
• As AI mandates spread globally, companies must capitalize on emerging markets to diversify their data center investments, mitigating risks associated with over-reliance on North American capacity.