𝗔𝗜 𝗜𝘀𝗻’𝘁 𝗡𝗲𝘄—𝗕𝘂𝘁 𝗜𝘁𝘀 𝗣𝗼𝘄𝗲𝗿 & 𝗔𝗰𝗰𝗲𝘀𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗛𝗮𝘃𝗲 𝗘𝘅𝗽𝗹𝗼𝗱𝗲𝗱 🚀

𝗠𝗮𝗻𝘆 𝗽𝗲𝗼𝗽𝗹𝗲 𝗯𝗲𝗹𝗶𝗲𝘃𝗲 𝗔𝗜 𝘀𝘁𝗮𝗿𝘁𝗲𝗱 𝘄𝗶𝘁𝗵 𝗖𝗵𝗮𝘁𝗚𝗣𝗧, but the truth is, AI has been around for decades—I’ve been applying it since 1992. What’s changed? Accessibility, scalability, and real business impact.

Back then, I built an 𝗜𝗕𝗠 𝗘𝘅𝗽𝗲𝗿𝘁 𝗦𝘆𝘀𝘁𝗲𝗺 𝘂𝘀𝗶𝗻𝗴 𝗶𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗶𝗻𝗴 for UVA’s Darden Business School. Over the years, I’ve applied AI and ML to optimize job estimating (i.e., CPQ), create 𝘀𝗼𝗽𝗵𝗶𝘀𝘁𝗶𝗰𝗮𝘁𝗲𝗱 𝗦𝗜𝗢𝗣 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀 for Supply Chain & Manufacturing forecasting, and standardize enterprise data across a national franchise for rental merchandise recommendations.

💡 𝗙𝗮𝘀𝘁 𝗳𝗼𝗿𝘄𝗮𝗿𝗱 𝘁𝗼 𝘁𝗼𝗱𝗮𝘆—AI has evolved from niche research to enterprise game-changer. Since 2020, the rise of LLMs, generative AI, and cloud-based ML frameworks has unlocked new levels of efficiency and decision-making power.

𝗕𝘂𝘁 𝗵𝗲𝗿𝗲’𝘀 𝗼𝗻𝗲 𝗼𝗳 𝗺𝗮𝗻𝘆 𝗼𝗳 𝘁𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝗺𝗶𝘀𝘀𝗲𝗱 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀 𝗜 𝘀𝗲𝗲:

🔹 𝗝𝗗 𝗘𝗱𝘄𝗮𝗿𝗱𝘀 (𝗝𝗗𝗘) 𝗘𝗥𝗣 systems (as well as many others) are sitting on a goldmine of untapped data.

🔹 AI can supercharge Forecasting, DRP, MRP, Inventory & Supply Chain Management.

🔹 𝗦𝗜𝗢𝗣 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸𝘀 (Sales, Inventory & Operations Planning) can be enhanced with AI-driven forecasting models that continuously improve themselves.

🔹 𝗔𝗜 𝗰𝗮𝗻 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗘𝗥𝗣 𝗺𝗲𝘁𝗮𝗱𝗮𝘁𝗮—improving everything from demand planning to production scheduling and automating tedious and often insurmountable updates to application parameters and codes!

I know this firsthand—I’ve been a 𝗵𝗮𝗻𝗱𝘀-𝗼𝗻 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗲𝗿 𝗼𝗻 𝟮𝟵 𝗝𝗗 𝗘𝗱𝘄𝗮𝗿𝗱𝘀 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀, working extensively with Manufacturing, Distribution, Forecasting/Planning, and Finance. The data is there, the tools exist, but most companies haven’t yet connected the dots between AI and their ERP transformation.

𝙏𝙝𝙚 𝙦𝙪𝙚𝙨𝙩𝙞𝙤𝙣 𝙞𝙨𝙣’𝙩 𝙬𝙝𝙚𝙩𝙝𝙚𝙧 𝘼𝙄 𝙘𝙖𝙣 𝙩𝙧𝙖𝙣𝙨𝙛𝙤𝙧𝙢 𝙀𝙍𝙋—𝙞𝙩’𝙨 𝙬𝙝𝙚𝙩𝙝𝙚𝙧 𝙤𝙧𝙜𝙖𝙣𝙞𝙯𝙖𝙩𝙞𝙤𝙣𝙨 𝙖𝙧𝙚 𝙧𝙚𝙖𝙙𝙮 𝙩𝙤 𝙡𝙚𝙫𝙚𝙧𝙖𝙜𝙚 𝙞𝙩.

💬 Are you using AI to optimize your ERP data yet? If not, what’s holding you back? Let’s discuss how AI can unlock new levels of efficiency in enterprise systems.