Feuji’s Post

AI is dominating my feeds, with notable examples like NVIDIA's market-moving growth and Business Insider's headline, “Insider Today: OpenAI’s Funding Frenzy.” This topic also came up recently at Feuji. My thought share at the event: ✅Most AI revenue from BigTech is still enterprise-focused (B2B), but this will shift as Apple, Alphabet, and others embed AI into consumer products. ✅The rise of OpenSource, exemplified by Meta’s LLaMA, carries significant implications—similar to LINUX’s evolution. Reading the fine print on Meta’s LLaMA OpenSource is crucial, as there are important nuances. AI Adoption Frameworks: ✅Tech Companies: Focus on product embedding (customer usage), internal efficiency (AI for tech productivity), and exploring new business models. ✅Enterprises: Prioritize customer experience (D2C, service, marketing, loyalty), cost management (operations, supply chain, clinical ops), productivity (HR, finance, legal), and new business models (targeting new segments and revenue generation). All efforts must center on value creation. While many enterprises have embraced AI with various use cases and projected ROI, there are critical gaps: ⭕ A shift from conversational AI to embedded and agentic AI is needed. ⭕ Focus on end-to-end processes and customer journeys. ⭕ Rigorous automation of Responsible AI, including continuous testing. ⭕ Clear understanding of costs and risks. Even startups that are pre-GenAI, whether using AI or not, risk obsolescence if they don't embrace the #NewAI. Some CEOs, like Jamie Dimon of JPMC, openly discuss AI adoption with analysts, while others still see it as a shiny object. Key Questions for CEOs and Executive Teams: ✳ What is your level of ambition? Are you aiming to lead, maintain parity, or selectively lag? Ensure your ambition statement has a tangible dollar value and that your investments are pragmatic. ✳ How will you structure your AI focus? Cross-functional teams thriving across industries, geographies, and scales are now the rule. Who will lead this effort? ✳ How are you guiding your organization through this social change? Are you preparing holistically or on a use-case basis? A common question I get is: Who’s leading in New AI (deterministic, probabilistic, and conversational) in the enterprise? The biggest impact stories are still unfolding. Who has reshaped their P&L—altering revenue segments, channels, customer clusters, or reducing costs and creating capacity? Who is managing AI-related risks effectively, including Responsible AI, bias management, and driving results? Ultimately, results will speak for themselves. We’re waiting to see significant impacts on revenue, margins, cash, and costs—beyond the number of AI bots or model tokens. The progression from Chips to Platforms to SaaS/Tech Companies to Enterprises for value creation doesn’t need to be linear. I am confident it will come !! What are you seeing? How are you seeing the AI frenzy temper, taper, evolve? Anandhi Periyanan Manohar Reddy