🏭 Industrial IoT + AI / Generative AI > Agentic AI 🤖

Actual Case Studies, Insights and Perspectives >>>🚀🚀🚀 | Dec '24 / Jan 2025

Hi everybody, I'm back... Happy new year! 🎇🎉🎆

2025 has just started and I am already struggling (again.. .???!!!😉) to efficiently cope with the frenetic pace of Agentic AI / AI Agents 🤖 news, announces, insights and, of course, case studies!

It wasn't easy to review and select what I consider the most "reliable" ones, but I hope you'll appreciate the effort!

Ciao, Fabio

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

Super Heavy booster's tower catch on Starship's seventh flight test | @SpaceX (1/21)

#industrial #iot #iiot #ai #genai #generativeai #agenticai #aiagents #casestudies #insights #perspectives

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𝐀 𝐏𝐑𝐈𝐌𝐄𝐑! >>> 𝐖𝐡𝐚𝐭 𝐀𝐫𝐞 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 𝐚𝐧𝐝 𝐖𝐡𝐲 𝐀𝐫𝐞 𝐓𝐡𝐞𝐲 𝐍𝐨𝐰 𝐒𝐨 𝐏𝐞𝐫𝐯𝐚𝐬𝐢𝐯𝐞? 𝘈𝘨𝘦𝘯𝘵𝘪𝘤 𝘈𝘐 𝘪𝘴 𝘵𝘩𝘦 𝘭𝘢𝘵𝘦𝘴𝘵 𝘱𝘩𝘢𝘴𝘦 𝘪𝘯 𝘵𝘩𝘦 𝘦𝘷𝘰𝘭𝘶𝘵𝘪𝘰𝘯 𝘰𝘧 𝘨𝘦𝘯𝘦𝘳𝘢𝘵𝘪𝘷𝘦 𝘈𝘐 𝘮𝘰𝘥𝘦𝘭𝘴; 𝘵𝘩𝘦𝘺 𝘤𝘢𝘯 𝘢𝘶𝘵𝘰𝘯𝘰𝘮𝘰𝘶𝘴𝘭𝘺 𝘤𝘰𝘮𝘱𝘭𝘦𝘵𝘦 𝘵𝘢𝘴𝘬𝘴, 𝘢𝘯𝘥 𝘦𝘷𝘦𝘯 𝘮𝘪𝘮𝘪𝘤 𝘵𝘩𝘦 𝘣𝘦𝘩𝘢𝘷𝘪𝘰𝘳 𝘰𝘧 𝘩𝘶𝘮𝘢𝘯𝘴 🚀🚀🚀

Via Computerworld | December 5, 2024 | @VINCI_Digital

𝐆𝐞𝐧𝐀𝐈’s latest big step forward has been the arrival of autonomous agents, or AI-enabled applications capable of perceiving their environment, making decisions, and taking actions to achieve specific goals

🔹The key word here is “𝒂𝒈𝒆𝒏𝒄𝒚,” which allows the software to take action on its own. Unlike 𝐠𝐞𝐧𝐀𝐈 tools — which usually focus on creating content such as text, images, and music —𝐚𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈 𝐢𝐬 𝐝𝐞𝐬𝐢𝐠𝐧𝐞𝐝 𝐭𝐨 𝐞𝐦𝐩𝐡𝐚𝐬𝐢𝐳𝐞 𝐩𝐫𝐨𝐚𝐜𝐭𝐢𝐯𝐞 𝐩𝐫𝐨𝐛𝐥𝐞𝐦-𝐬𝐨𝐥𝐯𝐢𝐧𝐠 𝐚𝐧𝐝 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐭𝐚𝐬𝐤 𝐞𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧.

🔹The simplest definition of an 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭 is the combination of a large language model (𝐋𝐋𝐌) and a traditional software application that can act independently to complete a task.

𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈 𝐨𝐩𝐞𝐫𝐚𝐭𝐞𝐬 𝐢𝐧 𝐭𝐰𝐨 𝐤𝐞𝐲 𝐰𝐚𝐲𝐬

A) First, it offers 𝐬𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐳𝐞𝐝 𝐚𝐠𝐞𝐧𝐭𝐬 capable of autonomously completing tasks across the open web, in mobile apps, or as an operating system:

>>>A specific type of 𝐚𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈, called conversational web agents, functions much like chatbots

>>> In this case, the 𝐚𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈 engages users through multimodal conversations, extending beyond simple text chats to accompany them as they navigate the open web or use apps, according to Larry Heck, a professor at Georgia Institute of Technology’s schools of Electrical and Computer Engineering and Interactive Computing

B) 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 are already showing up in places you might not expect:

>>> For example, most 𝐬𝐞𝐥𝐟-𝐝𝐫𝐢𝐯𝐢𝐧𝐠 𝐯𝐞𝐡𝐢𝐜𝐥𝐞𝐬 today use sensors to collect data about their surroundings, which is then processed by 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐢𝐜 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 to create a map and navigate the vehicle

>>> 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 play several other critical roles in 𝐚𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬 𝐯𝐞𝐡𝐢𝐜𝐥𝐞 𝐫𝐨𝐮𝐭𝐞 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧, 𝐭𝐫𝐚𝐟𝐟𝐢𝐜 𝐦𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭, and 𝐫𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐦𝐚𝐤𝐢𝐧𝐠 — they can even 𝐩𝐫𝐞𝐝𝐢𝐜𝐭 𝐰𝐡𝐞𝐧 𝐚 𝐯𝐞𝐡𝐢𝐜𝐥𝐞 𝐧𝐞𝐞𝐝𝐬 𝐦𝐚𝐢𝐧𝐭𝐞𝐧𝐚𝐧𝐜𝐞

Source: https://bit.ly/4fBYUnP

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#iot #ai #genai #agenticai #autonomous #aiagents

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DeepSeek AI 𝐑𝟏 >>> A PRIMER! <<< 🚀🚀🚀 January 22-28, 2025 | @VINCI_Digital

DeepSeek R1

Via AI Mindset / By Conor Grennan

🔹DeepSeek 𝐑𝟏 >>> 𝘈𝘐 𝘳𝘦𝘷𝘰𝘭𝘶𝘵𝘪𝘰𝘯

Source: https://www.linkedin.com/posts/conorgrennan_lets-break-down-deepseek-ais-sputnik-moment-activity-7289982653087313921-7dbM

🔹DeepSeek 𝐑𝟏 >>> 𝘈𝘐 𝘦𝘧𝘧𝘪𝘤𝘪𝘦𝘯𝘤𝘺 "𝘰𝘯 𝘴𝘵𝘦𝘳𝘰𝘪𝘥𝘴"

Source: https://www.linkedin.com/posts/conorgrennan_how-did-deepseek-ai-actually-revolutionize-activity-7290432085347975169-RZUN/

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Via AI with Alex / @aiwithaz

🔹DeepSeek 𝐑𝟏 >>> 𝘌𝘹𝘱𝘭𝘢𝘪𝘯𝘦𝘥 𝘵𝘰 𝘺𝘰𝘶𝘳 𝘨𝘳𝘢𝘯𝘥𝘮𝘢!

—

Via arXiv

🔹DeepSeek 𝐑𝟏 >>> 𝘙𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘱𝘢𝘱𝘦𝘳

Source: https://arxiv.org/abs/2501.12948

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#iot #ai #genai #llms #deepseek

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𝐀𝐁𝐁 𝐚𝐜𝐪𝐮𝐢𝐫𝐞𝐬 𝐒𝐞𝐧𝐬𝐨𝐫𝐟𝐚𝐜𝐭: 𝐚 𝐥𝐞𝐚𝐩 𝐟𝐨𝐫𝐰𝐚𝐫𝐝 𝐢𝐧 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐞𝐧𝐞𝐫𝐠𝐲 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲: 𝘚𝘦𝘯𝘴𝘰𝘳𝘧𝘢𝘤𝘵 𝘰𝘧𝘧𝘦𝘳𝘴 𝘢 𝘴𝘤𝘢𝘭𝘢𝘣𝘭𝘦 𝘚𝘢𝘢𝘚 𝘴𝘰𝘭𝘶𝘵𝘪𝘰𝘯 𝘵𝘩𝘢𝘵 𝘩𝘦𝘭𝘱𝘴 𝘴𝘮𝘢𝘭𝘭 𝘢𝘯𝘥 𝘮𝘦𝘥𝘪𝘶𝘮-𝘴𝘪𝘻𝘦𝘥 𝘦𝘯𝘵𝘦𝘳𝘱𝘳𝘪𝘴𝘦𝘴 𝘶𝘴𝘦 𝘈𝘐 𝘪𝘯 𝘵𝘩𝘦𝘪𝘳 𝘰𝘱𝘦𝘳𝘢𝘵𝘪𝘰𝘯𝘴 𝘢𝘯𝘥 𝘦𝘯𝘦𝘳𝘨𝘺 𝘮𝘢𝘯𝘢𝘨𝘦𝘮𝘦𝘯𝘵 𝘵𝘰 𝘭𝘰𝘸𝘦𝘳 𝘤𝘰𝘴𝘵𝘴 𝘢𝘯𝘥 𝘪𝘯𝘤𝘳𝘦𝘢𝘴𝘦 𝘦𝘧𝘧𝘪𝘤𝘪𝘦𝘯𝘤𝘺 🚀🚀🚀

Via Tech.eu | January 21, 2025 | @VINCI_Digital

ABB is acquiring Sensorfact — a fast-growing energy management company headquartered in Utrecht, Netherlands

🔹Established in 2017, Sensorfact offers a scalable SaaS solution that helps small and medium-sized enterprises use 𝐀𝐈 𝐢𝐧 𝐭𝐡𝐞𝐢𝐫 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐨𝐧𝐬 and 𝐞𝐧𝐞𝐫𝐠𝐲 𝐦𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭 𝐭𝐨 𝐥𝐨𝐰𝐞𝐫 𝐜𝐨𝐬𝐭𝐬 𝐚𝐧𝐝 𝐢𝐧𝐜𝐫𝐞𝐚𝐬𝐞 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲.

🔹Sensorfact’s SaaS solution includes 𝐩𝐥𝐮𝐠-𝐚𝐧𝐝-𝐩𝐥𝐚𝐲 𝐬𝐞𝐧𝐬𝐨𝐫𝐬 that measure consumption on machine-level and connect to a smart software platform [>>> 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐈𝐨𝐓].

🔹The company uses algorithms to analyse the data, identify energy-saving opportunities and provide 𝐞𝐚𝐬𝐲-𝐭𝐨-𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭 𝐚𝐝𝐯𝐢𝐜𝐞 that is unique to each customer’s operations. [𝐊.𝐈.𝐒.𝐒.= 𝐊𝐞𝐞𝐩 𝐈𝐭 𝐒𝐢𝐦𝐩𝐥𝐞 𝐒𝐭𝐮𝐩𝐢𝐝!😉]

🔹Sensorfact CEO Pieter Broekema said:

>>> 𝘚𝘦𝘯𝘴𝘰𝘳𝘧𝘢𝘤𝘵 𝘱𝘳𝘰𝘷𝘪𝘥𝘦𝘴 𝘢 𝘴𝘪𝘯𝘨𝘭𝘦 𝘴𝘮𝘢𝘳𝘵 𝘧𝘢𝘤𝘵𝘰𝘳𝘺 𝘱𝘭𝘢𝘵𝘧𝘰𝘳𝘮 𝘵𝘩𝘢𝘵 𝘦𝘯𝘢𝘣𝘭𝘦𝘴 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳𝘴 𝘵𝘰 𝘤𝘰𝘭𝘭𝘦𝘤𝘵 𝘶𝘵𝘪𝘭𝘪𝘵𝘺 𝘢𝘯𝘥 𝘱𝘳𝘰𝘥𝘶𝘤𝘵𝘪𝘰𝘯 𝘥𝘢𝘵𝘢 𝒆𝒂𝒔𝒊𝒍𝒚 𝘢𝘯𝘥 𝘵𝘰 𝘳𝘦𝘥𝘶𝘤𝘦 𝘤𝘰𝘴𝘵𝘴 𝘢𝘯𝘥 𝘤𝘢𝘳𝘣𝘰𝘯 𝘦𝘮𝘪𝘴𝘴𝘪𝘰𝘯𝘴.

𝘞𝘦 𝘩𝘦𝘭𝘱 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳𝘴 𝘢𝘤𝘩𝘪𝘦𝘷𝘦 𝒔𝒊𝒈𝒏𝒊𝒇𝒊𝒄𝒂𝒏𝒕 𝒔𝒂𝒗𝒊𝒏𝒈𝒔 𝘢𝘯𝘥 𝘤𝘰𝘯𝘵𝘪𝘯𝘶𝘦 𝘵𝘰 𝘪𝘯𝘯𝘰𝘷𝘢𝘵𝘦 𝘵𝘰 𝘩𝘦𝘭𝘱 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳𝘴 𝘧𝘶𝘳𝘵𝘩𝘦𝘳 𝘳𝘦𝘥𝘶𝘤𝘦 𝘵𝘩𝘦𝘪𝘳 𝘪𝘯𝘥𝘶𝘴𝘵𝘳𝘪𝘢𝘭 𝘸𝘢𝘴𝘵𝘦. 𝘞𝘦 𝘢𝘳𝘦 𝘰𝘯𝘦 𝘰𝘧 𝘵𝘩𝘦 𝘮𝘢𝘳𝘬𝘦𝘵 𝘭𝘦𝘢𝘥𝘦𝘳𝘴 𝘪𝘯 𝘌𝘶𝘳𝘰𝘱𝘦, 𝘢𝘯𝘥 𝘵𝘰𝘨𝘦𝘵𝘩𝘦𝘳 𝘸𝘪𝘵𝘩 𝘈𝘉𝘉 𝘸𝘦 𝘸𝘪𝘭𝘭 𝘣𝘳𝘪𝘯𝘨 𝘰𝘶𝘳 𝘴𝘰𝘭𝘶𝘵𝘪𝘰𝘯𝘴 𝘵𝘰 𝘯𝘦𝘸 𝘨𝘭𝘰𝘣𝘢𝘭 𝘮𝘢𝘳𝘬𝘦𝘵𝘴, 𝘧𝘢𝘴𝘵𝘦𝘳. <<<

Source: https://tech.eu/2025/01/21/sensorfact-joins-abb-a-leap-forward-in-industrial-energy-solution/

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#iot #ai #genai #industrial #energy #efficiency

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𝐓𝐡𝐞 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 & 𝐂𝐨𝐩𝐢𝐥𝐨𝐭𝐬 𝐌𝐚𝐫𝐤𝐞𝐭 𝐌𝐚𝐩: 𝘞𝘦 𝘮𝘢𝘱 𝘰𝘶𝘵 60+ 𝘤𝘰𝘮𝘱𝘢𝘯𝘪𝘦𝘴 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘪𝘯𝘨 𝘈𝘐 𝘢𝘨𝘦𝘯𝘵𝘴 & 𝘤𝘰𝘱𝘪𝘭𝘰𝘵𝘴 𝘧𝘰𝘳 𝘪𝘯𝘥𝘶𝘴𝘵𝘳𝘪𝘢𝘭 𝘢𝘱𝘱𝘭𝘪𝘤𝘢𝘵𝘪𝘰𝘯𝘴, 𝘪𝘯𝘤𝘭𝘶𝘥𝘪𝘯𝘨 𝘮𝘢𝘯𝘶𝘧𝘢𝘤𝘵𝘶𝘳𝘪𝘯𝘨, 𝘭𝘰𝘨𝘪𝘴𝘵𝘪𝘤𝘴, 𝘴𝘦𝘮𝘪𝘤𝘰𝘯𝘥𝘶𝘤𝘵𝘰𝘳𝘴, 𝘥𝘦𝘧𝘦𝘯𝘴𝘦, 𝘢𝘯𝘥 𝘤𝘰𝘯𝘴𝘵𝘳𝘶𝘤𝘵𝘪𝘰𝘯 🚀🚀🚀

Via CB Insights | December 23, 2024 | @VINCI_Digital

𝐊𝐞𝐲 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬

>>> 𝘌𝘢𝘳𝘭𝘺-𝘴𝘵𝘢𝘨𝘦 𝘴𝘵𝘢𝘳𝘵𝘶𝘱𝘴 𝘥𝘰𝘮𝘪𝘯𝘢𝘵𝘦 𝘥𝘦𝘢𝘭 𝘴𝘩𝘢𝘳𝘦 𝘸𝘩𝘪𝘭𝘦 𝘮𝘢𝘫𝘰𝘳 𝘤𝘰𝘳𝘱𝘰𝘳𝘢𝘵𝘪𝘰𝘯𝘴 𝘣𝘢𝘵𝘵𝘭𝘦 𝘢𝘤𝘳𝘰𝘴𝘴 𝘵𝘦𝘤𝘩 𝘷𝘦𝘳𝘵𝘪𝘤𝘢𝘭𝘴

>>> 𝘔𝘢𝘯𝘶𝘧𝘢𝘤𝘵𝘶𝘳𝘪𝘯𝘨 𝘪𝘴 𝘴𝘦𝘦𝘪𝘯𝘨 𝘵𝘩𝘦 𝘮𝘰𝘴𝘵 𝘢𝘤𝘵𝘪𝘷𝘪𝘵𝘺 𝘤𝘰𝘮𝘱𝘢𝘳𝘦𝘥 𝘵𝘰 𝘷𝘦𝘳𝘵𝘪𝘤𝘢𝘭𝘴 𝘭𝘪𝘬𝘦 𝘥𝘦𝘧𝘦𝘯𝘴𝘦, 𝘸𝘢𝘳𝘦𝘩𝘰𝘶𝘴𝘪𝘯𝘨, 𝘢𝘯𝘥 𝘴𝘦𝘮𝘪𝘤𝘰𝘯𝘥𝘶𝘤𝘵𝘰𝘳𝘴

>>> 𝘊𝘰𝘮𝘱𝘢𝘯𝘪𝘦𝘴 𝘢𝘳𝘦 𝘣𝘶𝘪𝘭𝘥𝘪𝘯𝘨 𝘴𝘰𝘭𝘶𝘵𝘪𝘰𝘯𝘴 𝘰𝘯 𝘵𝘰𝘱 𝘰𝘧 𝘣𝘪𝘨 𝘵𝘦𝘤𝘩’𝘴 𝘧𝘰𝘶𝘯𝘥𝘢𝘵𝘪𝘰𝘯

🔹While AI copilots — which work alongside humans to speed up their workflows — currently comprise 90% of company activity, the tech will serve as a stepping stone to more 𝐚𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 in the coming years.

🔹75% of deals in the space go to early-stage startups, suggesting high development potential in the years ahead, especially as copilots gain more agent-like capabilities. The nascent space has no clear leaders yet, signaling a window of opportunity for industrials players to gain an early edge.

🔹𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 is seeing the most activity compared to verticals like defense, warehousing, and semiconductors. The most crowded markets are

- 𝐦𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧

- 𝐝𝐢𝐠𝐢𝐭𝐚𝐥 𝐰𝐨𝐫𝐤 𝐢𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧𝐬

where vendors are building copilots on top of existing technologies like analytics platforms and augmented reality headsets.

𝑰𝒎𝒑𝒓𝒐𝒗𝒊𝒏𝒈 𝒐𝒏 𝒄𝒖𝒓𝒓𝒆𝒏𝒕 𝒘𝒐𝒓𝒌𝒇𝒍𝒐𝒘𝒔 𝒘𝒊𝒕𝒉 𝒂 𝒄𝒐𝒑𝒊𝒍𝒐𝒕 𝒍𝒊𝒌𝒆𝒍𝒚 𝒐𝒇𝒇𝒆𝒓𝒔 𝒕𝒉𝒆 𝒒𝒖𝒊𝒄𝒌𝒆𝒔𝒕 𝒑𝒂𝒕𝒉 𝒕𝒐 𝒄𝒐𝒎𝒎𝒆𝒓𝒄𝒊𝒂𝒍𝒊𝒛𝒂𝒕𝒊𝒐𝒏 𝒗𝒔. 𝒅𝒆𝒗𝒆𝒍𝒐𝒑𝒊𝒏𝒈 𝒂𝒖𝒕𝒐𝒏𝒐𝒎𝒐𝒖𝒔 𝒂𝒈𝒆𝒏𝒕𝒔 𝒂𝒔 𝒔𝒕𝒂𝒏𝒅𝒂𝒍𝒐𝒏𝒆 𝒑𝒓𝒐𝒅𝒖𝒄𝒕𝒔

🔹Big tech is laying the groundwork for 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 & copilots, with Microsoft forming partnerships with all 14 of the public industrials companies in this map.

🔹Google has also inked notable partnerships here. By owning the infrastructure, these tech giants will control how AI develops across industries, creating both dependencies and efficiencies for businesses adopting their solutions.

Source: https://bit.ly/4a7N1ot

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#iot #ai #genai #industrial #aiagents

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𝐈𝐬 𝐧𝐮𝐜𝐥𝐞𝐚𝐫 𝐞𝐧𝐞𝐫𝐠𝐲 𝐭𝐡𝐞 𝐚𝐧𝐬𝐰𝐞𝐫 𝐭𝐨 𝐀𝐈 𝐝𝐚𝐭𝐚 𝐜𝐞𝐧𝐭𝐞𝐫𝐬’ 𝐩𝐨𝐰𝐞𝐫 𝐜𝐨𝐧𝐬𝐮𝐦𝐩𝐭𝐢𝐨𝐧? 𝘕𝘶𝘤𝘭𝘦𝘢𝘳 𝘱𝘰𝘸𝘦𝘳 𝘸𝘪𝘭𝘭 𝘣𝘦 𝘢 𝘬𝘦𝘺 𝘱𝘢𝘳𝘵 𝘰𝘧 𝘢 𝘴𝘶𝘪𝘵𝘦 𝘰𝘧 𝘯𝘦𝘸 𝘦𝘯𝘦𝘳𝘨𝘺 𝘪𝘯𝘧𝘳𝘢𝘴𝘵𝘳𝘶𝘤𝘵𝘶𝘳𝘦 𝘣𝘶𝘪𝘭𝘵 𝘵𝘰 𝘮𝘦𝘦𝘵 𝘴𝘶𝘳𝘨𝘪𝘯𝘨 𝘥𝘢𝘵𝘢-𝘤𝘦𝘯𝘵𝘦𝘳 𝘱𝘰𝘸𝘦𝘳 𝘥𝘦𝘮𝘢𝘯𝘥 𝘥𝘳𝘪𝘷𝘦𝘯 𝘣𝘺 𝘢𝘳𝘵𝘪𝘧𝘪𝘤𝘪𝘢𝘭 𝘪𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘤𝘦 🚀🚀🚀

Via Goldman Sachs | January 23, 2025 | @VINCI_Digital

𝐁𝐮𝐭 𝐧𝐮𝐜𝐥𝐞𝐚𝐫 𝐜𝐚𝐧’𝐭 𝐦𝐞𝐞𝐭 𝐚𝐥𝐥 𝐨𝐟 𝐭𝐡𝐞 𝐢𝐧𝐜𝐫𝐞𝐚𝐬𝐞𝐝 𝐝𝐚𝐭𝐚-𝐜𝐞𝐧𝐭𝐞𝐫 𝐩𝐨𝐰𝐞𝐫 𝐧𝐞𝐞𝐝𝐬. 𝐍𝐚𝐭𝐮𝐫𝐚𝐥 𝐠𝐚𝐬, 𝐫𝐞𝐧𝐞𝐰𝐚𝐛𝐥𝐞𝐬, 𝐚𝐧𝐝 𝐛𝐚𝐭𝐭𝐞𝐫𝐲 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲 will also have a role to play, according to Goldman Sachs Research

🔹Several big tech companies looking for low carbon, round-the-clock energy signed contracts for new nuclear capacity in the last year, and there could be more such deals ahead.

🔹𝐓𝐡𝐨𝐬𝐞 𝐞𝐟𝐟𝐨𝐫𝐭𝐬 𝐜𝐨𝐦𝐞 𝐚𝐬 𝐞𝐥𝐞𝐜𝐭𝐫𝐢𝐜𝐢𝐭𝐲 𝐮𝐬𝐚𝐠𝐞 𝐛𝐲 𝐝𝐚𝐭𝐚 𝐜𝐞𝐧𝐭𝐞𝐫𝐬 𝐢𝐬 𝐞𝐱𝐩𝐞𝐜𝐭𝐞𝐝 𝐭𝐨 𝐦𝐨𝐫𝐞 𝐭𝐡𝐚𝐧 𝐝𝐨𝐮𝐛𝐥𝐞 𝐛𝐲 𝟐𝟎𝟑𝟎, according to reports led by Brian Singer, Jim Schneider, and Carly Davenport.

🔹In total, the team forecasts 𝟖𝟓-𝟗𝟎 𝐠𝐢𝐠𝐚𝐰𝐚𝐭𝐭𝐬 (𝐆𝐖) 𝐨𝐟 𝐧𝐞𝐰 𝐧𝐮𝐜𝐥𝐞𝐚𝐫 𝐜𝐚𝐩𝐚𝐜𝐢𝐭𝐲 would be needed to meet all of the data center power demand growth expected 𝐛𝐲 𝟐𝟎𝟑𝟎 (relative to 2023).

>>> 𝐁𝐮𝐭 𝐰𝐞𝐥𝐥 𝐥𝐞𝐬𝐬 𝐭𝐡𝐚𝐧 𝟏𝟎% 𝐰𝐢𝐥𝐥 𝐛𝐞 𝐚𝐯𝐚𝐢𝐥𝐚𝐛𝐥𝐞 𝐠𝐥𝐨𝐛𝐚𝐥𝐥𝐲 𝐛𝐲 𝟐𝟎𝟑𝟎 <<<

Source: https://www.goldmansachs.com/insights/articles/is-nuclear-energy-the-answer-to-ai-data-centers-power-consumption

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#iot #ai #genai #datacenters #nuclear #energy

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𝐅𝐫𝐨𝐦 𝐒𝐭𝐚𝐭𝐢𝐜 𝐓𝐨𝐨𝐥𝐬 𝐭𝐨 𝐒𝐦𝐚𝐫𝐭 𝐒𝐲𝐬𝐭𝐞𝐦𝐬: 𝐓𝐡𝐞 𝐑𝐢𝐬𝐞 𝐨𝐟 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 >>> 𝘋𝘪𝘴𝘤𝘰𝘷𝘦𝘳 𝘩𝘰𝘸 𝘈𝘐 𝘢𝘨𝘦𝘯𝘵𝘴 𝘢𝘳𝘦 𝘤𝘩𝘢𝘯𝘨𝘪𝘯𝘨 𝘪𝘯𝘥𝘶𝘴𝘵𝘳𝘪𝘦𝘴 𝘣𝘺 𝘢𝘶𝘵𝘰𝘮𝘢𝘵𝘪𝘯𝘨 𝘵𝘢𝘴𝘬𝘴, 𝘪𝘮𝘱𝘳𝘰𝘷𝘪𝘯𝘨 𝘸𝘰𝘳𝘬𝘧𝘭𝘰𝘸𝘴, 𝘢𝘯𝘥 𝘪𝘯𝘵𝘳𝘰𝘥𝘶𝘤𝘪𝘯𝘨 𝘯𝘦𝘸 𝘢𝘱𝘱𝘭𝘪𝘤𝘢𝘵𝘪𝘰𝘯𝘴 𝘪𝘯 𝘢𝘳𝘦𝘢𝘴 𝘭𝘪𝘬𝘦 𝘩𝘦𝘢𝘭𝘵𝘩𝘤𝘢𝘳𝘦, 𝘧𝘪𝘯𝘢𝘯𝘤𝘦, 𝘢𝘯𝘥 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳 𝘴𝘦𝘳𝘷𝘪𝘤𝘦 🚀🚀🚀

Via AI Entrepreneurs | January 24, 2025 | @VINCI_Digital

🔹𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 (𝐀𝐈) is no longer confined to isolated functions or tools; it has evolved into robust systems capable of mimicking human decision-making and autonomously completing complex tasks.

𝑾𝒉𝒂𝒕 𝑨𝒓𝒆 𝑨𝑰 𝑨𝒈𝒆𝒏𝒕𝒔?

At their core, 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 𝐚𝐫𝐞 𝐬𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐭𝐡𝐚𝐭 𝐮𝐬𝐞 𝐚𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐭𝐨 𝐨𝐛𝐬𝐞𝐫𝐯𝐞, 𝐩𝐥𝐚𝐧, 𝐚𝐧𝐝 𝐚𝐜𝐭 𝐚𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬𝐥𝐲 𝐰𝐢𝐭𝐡𝐢𝐧 𝐬𝐩𝐞𝐜𝐢𝐟𝐢𝐜 𝐞𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭𝐬 𝐭𝐨 𝐚𝐜𝐡𝐢𝐞𝐯𝐞 𝐬𝐞𝐭 𝐠𝐨𝐚𝐥𝐬

Unlike static tools, 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 𝐝𝐲𝐧𝐚𝐦𝐢𝐜𝐚𝐥𝐥𝐲 𝐚𝐝𝐚𝐩𝐭, 𝐥𝐞𝐚𝐫𝐧 𝐟𝐫𝐨𝐦 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞𝐬, 𝐚𝐧𝐝 𝐡𝐚𝐧𝐝𝐥𝐞 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐦𝐮𝐥𝐭𝐢-𝐬𝐭𝐞𝐩 𝐭𝐚𝐬𝐤𝐬 𝐰𝐢𝐭𝐡 𝐦𝐢𝐧𝐢𝐦𝐚𝐥 𝐡𝐮𝐦𝐚𝐧 𝐢𝐧𝐭𝐞𝐫𝐯𝐞𝐧𝐭𝐢𝐨𝐧

𝐊𝐞𝐲 𝐂𝐡𝐚𝐫𝐚𝐜𝐭𝐞𝐫𝐢𝐬𝐭𝐢𝐜𝐬 𝐨𝐟 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬

>>> 𝐀𝐮𝐭𝐨𝐧𝐨𝐦𝐲: Operate independently to execute tasks

>>> 𝐌𝐞𝐦𝐨𝐫𝐲: Retain context across tasks and interactions

>>> 𝐂𝐡𝐚𝐢𝐧𝐢𝐧𝐠: Perform sequential actions based on prior steps and results

>>> 𝐓𝐨𝐨𝐥 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧: Leverage internal or external systems to complete workflows

Source: https://medium.com/the-ai-entrepreneurs/from-static-tools-to-smart-systems-the-rise-of-ai-agents-e7d07ab6e694

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#iot #ai #genai #agenticai #aiagents

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𝐖𝐡𝐚𝐭 𝐂𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐒𝐮𝐜𝐜𝐞𝐞𝐝𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐀𝐈 𝐃𝐨 𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭𝐥𝐲 🚀🚀🚀

Via Harvard Business Review | January 9, 2025 | @VINCI_Digital

𝐅𝐨𝐮𝐫 𝐟𝐚𝐜𝐭𝐨𝐫𝐬 𝐬𝐞𝐭 𝐥𝐞𝐚𝐝𝐢𝐧𝐠 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐚𝐩𝐚𝐫𝐭

1. 𝐄𝐱𝐞𝐜𝐮𝐭𝐢𝐯𝐞 𝐬𝐩𝐨𝐧𝐬𝐨𝐫𝐬𝐡𝐢𝐩

🔹In our 2023 survey, more than three-quarters of AI leaders had 𝐂-𝐥𝐞𝐯𝐞𝐥 𝐬𝐩𝐨𝐧𝐬𝐨𝐫𝐬𝐡𝐢𝐩 — most of the time coming from the 𝐂𝐄𝐎 or 𝐛𝐨𝐚𝐫𝐝.

🔹𝘋𝘦𝘵𝘦𝘳𝘮𝘪𝘯𝘪𝘯𝘨 𝘵𝘩𝘦 𝘳𝘦𝘵𝘶𝘳𝘯 𝘰𝘯 𝘪𝘯𝘷𝘦𝘴𝘵𝘮𝘦𝘯𝘵 (𝘙𝘖𝘐) 𝘧𝘰𝘳 𝘈𝘐 𝘪𝘯𝘪𝘵𝘪𝘢𝘵𝘪𝘷𝘦𝘴 𝘪𝘴 𝘥𝘪𝘧𝘧𝘪𝘤𝘶𝘭𝘵: The savings may not be immediate, and some of the benefits, such as freeing up employee time to perform more value-added work, are indirect.

2. 𝐀 𝐧𝐞𝐭𝐰𝐨𝐫𝐤 𝐨𝐟 𝐩𝐚𝐫𝐭𝐧𝐞𝐫𝐬

🔹In-house capabilities are necessary; almost 90% of leaders in the 2023 survey reported using internal resources to develop AI solutions.

🔹But they’re often not sufficient: 𝐓𝐰𝐨-𝐭𝐡𝐢𝐫𝐝𝐬 𝐨𝐟 𝐥𝐞𝐚𝐝𝐞𝐫𝐬 𝐚𝐥𝐬𝐨 𝐡𝐚𝐝 𝐨𝐮𝐭𝐬𝐢𝐝𝐞 𝐩𝐚𝐫𝐭𝐧𝐞𝐫𝐬, typically to fill gaps in expertise and to accelerate development and payback.

3. 𝐂𝐫𝐨𝐬𝐬-𝐝𝐞𝐩𝐚𝐫𝐭𝐦𝐞𝐧𝐭 𝐜𝐨𝐦𝐦𝐮𝐧𝐢𝐜𝐚𝐭𝐢𝐨𝐧

🔹In successful companies, we saw smooth collaboration between IT and operations. One common approach is to create a “𝒄𝒆𝒏𝒕𝒆𝒓 𝒐𝒇 𝒆𝒙𝒄𝒆𝒍𝒍𝒆𝒏𝒄𝒆” (𝐂𝐨𝐄), a cross-silo internal organization staffed with employees with data-science skills.

🔹The 𝐂𝐨𝐄 ensures that AI projects get implemented efficiently and deliver value, while also addressing issues such as cybersecurity, data error, and compliance. 𝐂𝐨𝐄s typically create standardized processes and keep the talent pipeline filled, through both hiring and capability-building.

🔹They can leverage the greater collaboration, talent, and diversity in experience that comes with a larger team. Almost six in 10 leaders surveyed have a 𝐂𝐨𝐄 reporting at either the corporate or business-unit level.

4. 𝐃𝐚𝐭𝐚 𝐦𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭

🔹For companies to use AI well, they need accurate, pertinent, and well-organized data. 𝘛𝘰𝘰 𝘰𝘧𝘵𝘦𝘯, 𝘵𝘩𝘰𝘶𝘨𝘩, 𝘵𝘩𝘦𝘺 𝘦𝘪𝘵𝘩𝘦𝘳 𝘥𝘰𝘯’𝘵 𝘤𝘰𝘭𝘭𝘦𝘤𝘵 𝘵𝘩𝘦 𝘳𝘪𝘨𝘩𝘵 𝘪𝘯𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘰𝘯, 𝘰𝘳 𝘪𝘵 𝘪𝘴 𝘴𝘰 𝘪𝘯𝘢𝘤𝘤𝘶𝘳𝘢𝘵𝘦 𝘢𝘯𝘥 𝘱𝘰𝘰𝘳𝘭𝘺 𝘮𝘢𝘯𝘢𝘨𝘦𝘥 𝘵𝘩𝘢𝘵 𝘪𝘵 𝘪𝘴𝘯’𝘵 𝘶𝘴𝘦𝘧𝘶𝘭.

🔹The leaders we talked to invest in systems and processes to make sure that doesn’t happen. For a start, they are much more likely to record 𝐫𝐞𝐥𝐞𝐯𝐚𝐧𝐭 𝐞𝐪𝐮𝐢𝐩𝐦𝐞𝐧𝐭 𝐝𝐚𝐭𝐚, 𝐬𝐮𝐜𝐡 𝐚𝐬 𝐜𝐫𝐢𝐭𝐢𝐜𝐚𝐥-𝐭𝐨-𝐪𝐮𝐚𝐥𝐢𝐭𝐲 𝐩𝐫𝐨𝐜𝐞𝐬𝐬 𝐦𝐞𝐚𝐬𝐮𝐫𝐞𝐦𝐞𝐧𝐭𝐬, 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐫𝐚𝐭𝐞, 𝐚𝐧𝐝 𝐝𝐨𝐰𝐧𝐭𝐢𝐦𝐞. [ >>> 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐈𝐨𝐓]

🔹Then they manage it meticulously, often in the cloud, allowing them to make informed decisions that drive efficiency and innovation.

Source: https://bit.ly/3BYh1Xz

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#industrial #iot #iiot #ai #genai #hbr

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𝐐𝐮𝐢𝐧𝐝𝐢 𝐫𝐚𝐢𝐬𝐞𝐬 €𝟓𝟐𝟓𝐊 𝐒𝐞𝐞𝐝 𝐟𝐨𝐫 𝐬𝐦𝐚𝐫𝐭 𝐦𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐜𝐨-𝐩𝐢𝐥𝐨𝐭: 𝘘𝘶𝘪𝘯𝘥𝘪 𝘦𝘯𝘢𝘣𝘭𝘦𝘴 𝘧𝘢𝘤𝘵𝘰𝘳𝘺 𝘴𝘵𝘢𝘧𝘧 𝘵𝘰 𝘬𝘯𝘰𝘸 𝘪𝘯 𝘳𝘦𝘢𝘭-𝘵𝘪𝘮𝘦 𝘢𝘯𝘺 𝘤𝘳𝘪𝘵𝘪𝘤𝘢𝘭 𝘦𝘷𝘦𝘯𝘵, 𝘴𝘶𝘤𝘩 𝘢𝘴 𝘢 𝘮𝘢𝘤𝘩𝘪𝘯𝘦 𝘢𝘯𝘰𝘮𝘢𝘭𝘺 𝘰𝘳 𝘵𝘩𝘦 𝘶𝘯𝘦𝘹𝘱𝘦𝘤𝘵𝘦𝘥 𝘢𝘣𝘴𝘦𝘯𝘤𝘦 𝘰𝘧 𝘢𝘯 𝘦𝘮𝘱𝘭𝘰𝘺𝘦𝘦, 𝘢𝘯𝘥 𝘵𝘰 𝘢𝘤𝘵 𝘱𝘳𝘰𝘢𝘤𝘵𝘪𝘷𝘦𝘭𝘺 🚀🚀🚀

Via Tech.eu | December 5, 2024 | @VINCI_Digital

𝐒𝐦𝐚𝐫𝐭 𝐦𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 𝐬𝐭𝐚𝐫𝐭𝐮𝐩 𝐐𝐮𝐢𝐧𝐝𝐢 𝐡𝐚𝐬 𝐫𝐚𝐢𝐬𝐞𝐝 €𝟓𝟐𝟓,𝟎𝟎𝟎 𝐢𝐧 𝐢𝐧𝐢𝐭𝐢𝐚𝐥 𝐒𝐞𝐞𝐝 𝐟𝐮𝐧𝐝𝐢𝐧𝐠

🔹Founded in 2022, Quindi — Production Copilot® has developed the first 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐜𝐨𝐩𝐢𝐥𝐨𝐭, an 𝐚𝐝𝐯𝐚𝐧𝐜𝐞𝐝 𝐀𝐈 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧 that integrates all data from machinery, orders, and people to optimise production flows.

𝘛𝘩𝘳𝘰𝘶𝘨𝘩 𝘵𝘩𝘦 𝘤𝘰𝘮𝘣𝘪𝘯𝘦𝘥 𝘶𝘴𝘦 𝘰𝘧 𝘱𝘳𝘰𝘱𝘳𝘪𝘦𝘵𝘢𝘳𝘺 𝘥𝘢𝘵𝘢 𝘢𝘯𝘥 𝘢𝘭𝘨𝘰𝘳𝘪𝘵𝘩𝘮𝘴, 𝐐𝐮𝐢𝐧𝐝𝐢 𝘦𝘯𝘢𝘣𝘭𝘦𝘴 𝘱𝘳𝘰𝘥𝘶𝘤𝘵𝘪𝘰𝘯 𝘳𝘰𝘭𝘦𝘴 𝘵𝘰 𝘬𝘯𝘰𝘸 𝘪𝘯 𝘳𝘦𝘢𝘭-𝘵𝘪𝘮𝘦 𝘢𝘯𝘺 𝘤𝘳𝘪𝘵𝘪𝘤𝘢𝘭 𝘦𝘷𝘦𝘯𝘵, 𝘴𝘶𝘤𝘩 𝘢𝘴 𝘢 𝘮𝘢𝘤𝘩𝘪𝘯𝘦 𝘢𝘯𝘰𝘮𝘢𝘭𝘺 𝘰𝘳 𝘵𝘩𝘦 𝘶𝘯𝘦𝘹𝘱𝘦𝘤𝘵𝘦𝘥 𝘢𝘣𝘴𝘦𝘯𝘤𝘦 𝘰𝘧 𝘢𝘯 𝘦𝘮𝘱𝘭𝘰𝘺𝘦𝘦, 𝘢𝘯𝘥 𝘵𝘰 𝘢𝘤𝘵 𝘱𝘳𝘰𝘢𝘤𝘵𝘪𝘷𝘦𝘭𝘺.

🔹Staff receive operational guidance to overcome critical issues, while production managers can re-schedule production in real-time, choosing from different production scenarios proposed by Quindi — Production Copilot®.

🔹The company brings together manufacturing and IT specialists with decades of experience ranging from mechatronics to AI, from academia to the shop floor.

🔹Founding partners of Quindi Fabio Oscari (CEO), Simone Minto (CTO), Luca Barbazza (COO), and Alberto Frison (Head of Growth) aspire to transform production environments through technological innovation.

Source: https://bit.ly/3ZKujzZ

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#industrial #iot #ai #copilot #manufacturing

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𝟓 𝐰𝐚𝐲𝐬 𝐀𝐈 𝐰𝐢𝐥𝐥 𝐬𝐡𝐚𝐩𝐞 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬𝐞𝐬 𝐢𝐧 𝟐𝟎𝟐𝟓 - 𝘔𝘶𝘭𝘵𝘪𝘮𝘰𝘥𝘢𝘭 𝘈𝘐, 𝘦𝘯𝘩𝘢𝘯𝘤𝘦𝘥 𝘦𝘯𝘵𝘦𝘳𝘱𝘳𝘪𝘴𝘦 𝘴𝘦𝘢𝘳𝘤𝘩 𝘢𝘯𝘥 𝘮𝘰𝘳𝘦: 𝘉𝘦 𝘴𝘶𝘳𝘦 𝘵𝘰 𝘤𝘩𝘦𝘤𝘬 𝘰𝘶𝘵 𝘢𝘭𝘭 𝘰𝘧 𝘎𝘰𝘰𝘨𝘭𝘦 𝘊𝘭𝘰𝘶𝘥’𝘴 𝘵𝘩𝘰𝘶𝘨𝘩𝘵𝘴 𝘰𝘯 𝘩𝘰𝘸 𝘈𝘐 𝘸𝘪𝘭𝘭 𝘪𝘮𝘱𝘢𝘤𝘵 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴𝘦𝘴 𝘵𝘩𝘪𝘴 𝘺𝘦𝘢𝘳 🚀🚀🚀

Via Google / By Oliver Parker | December 17, 2024 | @VINCI_Digital

2025 𝒘𝒊𝒍𝒍 𝒃𝒆 𝒂 𝒑𝒊𝒗𝒐𝒕𝒂𝒍 𝒚𝒆𝒂𝒓 𝒂𝒔 𝑨𝑰 𝒕𝒓𝒂𝒏𝒔𝒇𝒐𝒓𝒎𝒔 𝒉𝒐𝒘 𝒄𝒐𝒎𝒑𝒂𝒏𝒊𝒆𝒔 𝒐𝒑𝒆𝒓𝒂𝒕𝒆, 𝒄𝒐𝒎𝒑𝒆𝒕𝒆 𝒂𝒏𝒅 𝒊𝒏𝒏𝒐𝒗𝒂𝒕𝒆

🔹Today [12/17] Google Cloud dropped its 𝟐𝟎𝟐𝟓 𝐀𝐈 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐓𝐫𝐞𝐧𝐝𝐬 𝐑𝐞𝐩𝐨𝐫𝐭 — here’s a look at 𝐟𝐢𝐯𝐞 𝐤𝐞𝐲 𝐭𝐫𝐞𝐧𝐝𝐬 shaping the future of business:

1. 𝐌𝐮𝐥𝐭𝐢𝐦𝐨𝐝𝐚𝐥 𝐀𝐈 𝐰𝐢𝐥𝐥 𝐝𝐞𝐥𝐢𝐯𝐞𝐫 𝐦𝐨𝐫𝐞 𝐜𝐨𝐧𝐭𝐞𝐱𝐭

>>> Multimodal AI processes information from text, images, audio and video. It allows for more intuitive interactions and significantly 𝘪𝘮𝘱𝘳𝘰𝘷𝘦𝘴 𝘵𝘩𝘦 𝘢𝘤𝘤𝘶𝘳𝘢𝘤𝘺 𝘰𝘧 𝘈𝘐 𝘰𝘶𝘵𝘱𝘶𝘵𝘴. This human-centric approach to AI is essential for businesses in an increasingly data-rich world.

2. 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 𝐰𝐢𝐥𝐥 𝐬𝐢𝐦𝐩𝐥𝐢𝐟𝐲 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐭𝐚𝐬𝐤𝐬

>>> As AI agents become more popular in businesses, they’ll be able 𝘵𝘰 𝘮𝘢𝘯𝘢𝘨𝘦 𝘤𝘰𝘮𝘱𝘭𝘦𝘹 𝘸𝘰𝘳𝘬𝘧𝘭𝘰𝘸𝘴, 𝘢𝘶𝘵𝘰𝘮𝘢𝘵𝘦 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘱𝘳𝘰𝘤𝘦𝘴𝘴𝘦𝘴 𝘢𝘯𝘥 𝘴𝘶𝘱𝘱𝘰𝘳𝘵 𝘦𝘮𝘱𝘭𝘰𝘺𝘦𝘦𝘴. Imagine customer agents providing support with a consistent experience across channels — in person, online and mobile. Employee agents will be able to streamline internal processes; creative agents will enhance design and production skills.

3. 𝐄𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐬𝐞𝐚𝐫𝐜𝐡 𝐰𝐢𝐥𝐥 𝐠𝐢𝐯𝐞 𝐩𝐞𝐨𝐩𝐥𝐞 𝐭𝐡𝐞 𝐤𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐭𝐡𝐞𝐲 𝐧𝐞𝐞𝐝

>>> Enterprise search systems — internal search engines for companies — are no longer limited to keyword-based queries. People will now be able to use images, audio, video and conversational prompts to quickly access and use internal data.

4. 𝐀𝐈-𝐩𝐨𝐰𝐞𝐫𝐞𝐝 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞𝐬 𝐰𝐢𝐥𝐥 𝐠𝐞𝐭 𝐞𝐯𝐞𝐧 𝐛𝐞𝐭𝐭𝐞𝐫

>>> AI-powered solutions are changing the customer experience, in part by anticipating customer needs and helping businesses stay connected to their customers. This translates to increased revenue, efficiency and brand loyalty. Imagine personalized recommendations and AI-enhanced search that understands customer intent.

5. 𝐀𝐈 𝐰𝐢𝐥𝐥 𝐞𝐧𝐡𝐚𝐧𝐜𝐞 𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐬𝐲𝐬𝐭𝐞𝐦𝐬

>>> In 2025, AI will help bolster defenses, identify and combat threats, automate manual security tasks and accelerate response times. However, this also leads to an "𝘢𝘳𝘮𝘴 𝘳𝘢𝘤𝘦" between defenders and attackers, as adversaries leverage AI for more sophisticated attacks. Organizations must proactively address this challenge.

Source: https://bit.ly/3Wh3dy6

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#iot #ai #genai #business #trends #2025

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𝐇𝐨𝐰 𝐀𝐫𝐞 𝐂𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐔𝐬𝐢𝐧𝐠 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬? 𝐇𝐞𝐫𝐞’𝐬 𝐚 𝐋𝐨𝐨𝐤 𝐚𝐭 𝐅𝐢𝐯𝐞 𝐄𝐚𝐫𝐥𝐲 𝐔𝐬𝐞𝐫𝐬 𝐨𝐟 𝐭𝐡𝐞 𝐁𝐨𝐭𝐬: 𝘛𝘩𝘦𝘴𝘦 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴𝘦𝘴 𝘢𝘳𝘦 𝘶𝘴𝘪𝘯𝘨 𝘈𝘐 𝘢𝘨𝘦𝘯𝘵𝘴 𝘧𝘰𝘳 𝘥𝘳𝘶𝘨 𝘥𝘪𝘴𝘤𝘰𝘷𝘦𝘳𝘺, 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳 𝘴𝘦𝘳𝘷𝘪𝘤𝘦, 𝘮𝘢𝘳𝘬𝘦𝘵𝘪𝘯𝘨, 𝘸𝘳𝘪𝘵𝘪𝘯𝘨 𝘤𝘰𝘥𝘦 𝘢𝘯𝘥 𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩. 𝘉𝘶𝘵 𝘵𝘩𝘦𝘺 𝘢𝘳𝘦𝘯’𝘵 𝘲𝘶𝘪𝘵𝘦 𝘳𝘦𝘢𝘥𝘺 𝘵𝘰 𝘭𝘦𝘵 𝘵𝘩𝘦 𝘣𝘰𝘵𝘴 𝘳𝘶𝘯 𝘢𝘮𝘰𝘬 🚀🚀🚀

Via The Wall Street Journal / 𝐂𝐈𝐎 𝐉𝐨𝐮𝐫𝐧𝐚𝐥 - By Belle L. | January 6, 2025 | @VINCI_Digital

🔹Johnson & Johnson >>> 𝘋𝘳𝘶𝘨 𝘥𝘪𝘴𝘤𝘰𝘷𝘦𝘳𝘺 𝘢𝘨𝘦𝘯𝘵𝘴

AI agents are being used to help the healthcare giant with the chemical synthesis process in drug discovery.

An autonomous AI agent that can determine the best time to conduct a solvent switch, a process where one solvent is swapped for another to crystallize a molecule and actually create the drug.

🔹Moody's Corporation >>> 𝘍𝘪𝘯𝘢𝘯𝘤𝘪𝘢𝘭 𝘢𝘯𝘢𝘭𝘺𝘴𝘪𝘴 𝘢𝘨𝘦𝘯𝘵𝘴 𝘵𝘩𝘢𝘵 𝘥𝘪𝘴𝘢𝘨𝘳𝘦𝘦

The company has developed a total of 35 agents, some for smaller tasks like project management, and linked them up with agents for supervising them, creating a 𝘮𝘶𝘭𝘵𝘪-𝘢𝘨𝘦𝘯𝘵 𝘴𝘺𝘴𝘵𝘦𝘮.

Moody's agents are given specific instructions, personalities and access to data and research. As a result, they can come to 𝐝𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐭 𝐜𝐨𝐧𝐜𝐥𝐮𝐬𝐢𝐨𝐧𝐬, especially for complex topics like analyzing the financial fitness of a company that appears healthy, but is facing geopolitical risk.

🔹eBay >>> 𝘈𝘨𝘦𝘯𝘵𝘴 𝘵𝘩𝘢𝘵 𝘸𝘳𝘪𝘵𝘦 𝘤𝘰𝘥𝘦 𝘢𝘯𝘥 𝘴𝘦𝘭𝘭 𝘪𝘵𝘦𝘮𝘴

eBay is using AI agents to help write code and create marketing campaigns. The company also plans to roll out agents that can help buyers find items and sellers list goods, and created its own 𝘢𝘨𝘦𝘯𝘵 𝘧𝘳𝘢𝘮𝘦𝘸𝘰𝘳𝘬 that can use several large language models in the background.

🔹Deutsche Telekom [DT] >>> 𝘈𝘯 𝘢𝘴𝘬 𝘮𝘦 𝘢𝘯𝘺𝘵𝘩𝘪𝘯𝘨 𝘢𝘨𝘦𝘯𝘵 𝘧𝘰𝘳 𝘦𝘮𝘱𝘭𝘰𝘺𝘦𝘦𝘴

DT has rolled out an AI agent for its employees to ask any question about internal policies and benefits, and for its service staff to ask questions about its products and services, also experimenting with letting the agent, which it calls askT, perform tasks on behalf of employees.

🔹COSENTINO >>> 𝘋𝘪𝘨𝘪𝘵𝘢𝘭 𝘞𝘰𝘳𝘬𝘧𝘰𝘳𝘤𝘦' 𝘴𝘰𝘭𝘷𝘪𝘯𝘨 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳 𝘪𝘴𝘴𝘶𝘦𝘴

AI agents fill the gaps in its customer service staff: they need to come with a set of basic skills, but they also get training when they first arrive on the job. AI agents also instructed to follow a strict process, and the company knows if they go off the rails.

Its 𝘥𝘪𝘨𝘪𝘵𝘢𝘭 𝘴𝘵𝘢𝘧𝘧 have entirely replaced the work of 𝐭𝐡𝐫𝐞𝐞 𝐭𝐨 𝐟𝐨𝐮𝐫 𝐩𝐞𝐨𝐩𝐥𝐞 previously involved in clearing customer orders, and those staff are focusing on other areas of service.

Source: https://on.wsj.com/3C5Es10

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#iot #ai #genai #agenticai #aiagents #earlyusers

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𝐇𝐨𝐰 𝐚 𝟏𝟔𝟎-𝐘𝐞𝐚𝐫-𝐎𝐥𝐝 𝐒𝐭𝐚𝐫𝐭𝐮𝐩 𝐔𝐬𝐞𝐬 𝐀𝐈: 𝐓𝐡𝐞 𝐇𝐞𝐢𝐧𝐞𝐤𝐞𝐧 𝐂𝐨𝐦𝐩𝐚𝐧𝐲’𝐬 𝐑𝐨𝐧𝐚𝐥𝐝 𝐝𝐞𝐧 𝐄𝐥𝐳𝐞𝐧 - 𝘈 𝘣𝘦𝘷𝘦𝘳𝘢𝘨𝘦 𝘤𝘰𝘮𝘱𝘢𝘯𝘺 𝘵𝘩𝘪𝘯𝘬𝘴 𝘭𝘪𝘬𝘦 𝘢 𝘴𝘵𝘢𝘳𝘵𝘶𝘱 𝘵𝘰 𝘮𝘢𝘪𝘯𝘵𝘢𝘪𝘯 𝘢 𝘤𝘭𝘰𝘴𝘦𝘳 𝘤𝘰𝘯𝘯𝘦𝘤𝘵𝘪𝘰𝘯 𝘸𝘪𝘵𝘩 𝘪𝘵𝘴 𝘤𝘶𝘴𝘵𝘰𝘮𝘦𝘳𝘴 🚀🚀🚀

Via MIT Sloan Management Review | January 7, 2025 | @VINCI_Digital

🔹After trying his luck at the stock market, Ronald den Elzen landed in a career in technology leadership instead.

🔹Today, as the chief technology and digital officer of The HEINEKEN Company, he encourages his team to think about the legacy beverage company as a 160-year-old startup with global scale, operating with multiple brands in more than 80 markets.

🔹When members of his team can work with agility and less fear of making mistakes, he finds they are more successful at rolling out new technology initiatives

Heineken uses AI extensively in areas including

>>> 𝐫𝐞𝐯𝐞𝐧𝐮𝐞 𝐦𝐚𝐧𝐚𝐠𝐞𝐦𝐞𝐧𝐭

>>> 𝐩𝐫𝐨𝐦𝐨𝐭𝐢𝐨𝐧𝐚𝐥 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧

>>> 𝐥𝐨𝐠𝐢𝐬𝐭𝐢𝐜𝐬

but Ronald believes much value [𝟗𝟓%] still comes from 𝐭𝐫𝐚𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐀𝐈 — such as 𝐩𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 and 𝐦𝐚𝐜𝐡𝐢𝐧𝐞 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐦𝐨𝐝𝐞𝐥𝐬

[>>> 𝑰 𝒕𝒐𝒍𝒅 𝒚𝒐𝒖 𝒔𝒐... 𝒔𝒊𝒏𝒄𝒆 2017...???!!!😉 <<<]

🔹Heineken is focused on using these foundational tools to drive tangible business outcomes, from 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐢𝐧𝐠 𝐬𝐮𝐩𝐩𝐥𝐲 𝐜𝐡𝐚𝐢𝐧𝐬 to 𝐢𝐦𝐩𝐫𝐨𝐯𝐢𝐧𝐠 𝐜𝐮𝐬𝐭𝐨𝐦𝐞𝐫 𝐞𝐧𝐠𝐚𝐠𝐞𝐦𝐞𝐧𝐭

Source: https://bit.ly/4h8ShuC

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#iot #ai #genai #ml #predictiveanalytics

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𝐆𝐨𝐨𝐠𝐥𝐞 𝐌𝐚𝐩𝐬 𝐭𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬: 𝘍𝘪𝘷𝘦 𝘭𝘦𝘴𝘴𝘰𝘯𝘴 𝘧𝘰𝘳 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴𝘦𝘴 🚀🚀🚀

Via VentureBeat / Google | January 6, 2025 | @VINCI_Digital

A new Google white paper, titled “𝑨𝒈𝒆𝒏𝒕𝒔“, imagines a future where AI takes on a more active and independent role in business

🔹It introduces the concept of 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬

>>> 𝘴𝘰𝘧𝘵𝘸𝘢𝘳𝘦 𝘴𝘺𝘴𝘵𝘦𝘮𝘴 𝘥𝘦𝘴𝘪𝘨𝘯𝘦𝘥 𝘵𝘰 𝘨𝘰 𝘣𝘦𝘺𝘰𝘯𝘥 𝘵𝘰𝘥𝘢𝘺’𝘴 𝘈𝘐 𝘮𝘰𝘥𝘦𝘭𝘴 𝘣𝘺 𝘳𝘦𝘢𝘴𝘰𝘯𝘪𝘯𝘨, 𝘱𝘭𝘢𝘯𝘯𝘪𝘯𝘨 𝘢𝘯𝘥 𝘵𝘢𝘬𝘪𝘯𝘨 𝘢𝘤𝘵𝘪𝘰𝘯𝘴 𝘵𝘰 𝘢𝘤𝘩𝘪𝘦𝘷𝘦 𝘴𝘱𝘦𝘤𝘪𝘧𝘪𝘤 𝘨𝘰𝘢𝘭𝘴

🔹Unlike traditional AI systems, which generate responses based solely on pre-existing training data,

>>> 𝘈𝘐 𝘢𝘨𝘦𝘯𝘵𝘴 𝘤𝘢𝘯 𝘪𝘯𝘵𝘦𝘳𝘢𝘤𝘵 𝘸𝘪𝘵𝘩 𝘦𝘹𝘵𝘦𝘳𝘯𝘢𝘭 𝘴𝘺𝘴𝘵𝘦𝘮𝘴, 𝘮𝘢𝘬𝘦 𝘥𝘦𝘤𝘪𝘴𝘪𝘰𝘯𝘴 𝘢𝘯𝘥 𝘤𝘰𝘮𝘱𝘭𝘦𝘵𝘦 𝘤𝘰𝘮𝘱𝘭𝘦𝘹 𝘵𝘢𝘴𝘬𝘴 𝘰𝘯 𝘵𝘩𝘦𝘪𝘳 𝘰𝘸𝘯

“𝑨𝒈𝒆𝒏𝒕𝒔 𝒂𝒓𝒆 𝒂𝒖𝒕𝒐𝒏𝒐𝒎𝒐𝒖𝒔 𝒂𝒏𝒅 𝒄𝒂𝒏 𝒂𝒄𝒕 𝒊𝒏𝒅𝒆𝒑𝒆𝒏𝒅𝒆𝒏𝒕𝒍𝒚 𝒐𝒇 𝒉𝒖𝒎𝒂𝒏 𝒊𝒏𝒕𝒆𝒓𝒗𝒆𝒏𝒕𝒊𝒐𝒏,”

the white paper explains, describing them as systems that combine reasoning, logic and real-time data access

🔹The idea behind these agents is ambitious:

𝘛𝘩𝘦𝘺 𝘤𝘰𝘶𝘭𝘥 𝘩𝘦𝘭𝘱 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴𝘦𝘴 𝘢𝘶𝘵𝘰𝘮𝘢𝘵𝘦 𝘵𝘢𝘴𝘬𝘴, 𝘴𝘰𝘭𝘷𝘦 𝘱𝘳𝘰𝘣𝘭𝘦𝘮𝘴 𝘢𝘯𝘥 𝘮𝘢𝘬𝘦 𝘥𝘦𝘤𝘪𝘴𝘪𝘰𝘯𝘴 𝘵𝘩𝘢𝘵 𝘸𝘦𝘳𝘦 𝘰𝘯𝘤𝘦 𝘩𝘢𝘯𝘥𝘭𝘦𝘥 𝘦𝘹𝘤𝘭𝘶𝘴𝘪𝘷𝘦𝘭𝘺 𝘣𝘺 𝘩𝘶𝘮𝘢𝘯𝘴.

<<< 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 𝐚𝐫𝐞𝐧’𝐭 𝐦𝐞𝐫𝐞𝐥𝐲 𝐚𝐧 𝐮𝐩𝐠𝐫𝐚𝐝𝐞 𝐭𝐨 𝐞𝐱𝐢𝐬𝐭𝐢𝐧𝐠 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐲; 𝐭𝐡𝐞𝐲 𝐫𝐞𝐩𝐫𝐞𝐬𝐞𝐧𝐭 𝐚 𝐬𝐡𝐢𝐟𝐭 𝐢𝐧 𝐡𝐨𝐰 𝐨𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 𝐨𝐩𝐞𝐫𝐚𝐭𝐞, 𝐜𝐨𝐦𝐩𝐞𝐭𝐞 𝐚𝐧𝐝 𝐢𝐧𝐧𝐨𝐯𝐚𝐭𝐞 >>>

Businesses that adopt these systems could see 𝐝𝐫𝐚𝐦𝐚𝐭𝐢𝐜 𝐠𝐚𝐢𝐧𝐬 𝐢𝐧 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 𝐚𝐧𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐯𝐢𝐭𝐲, while those that hesitate may find themselves struggling to keep up.

Five most important insights from Google’s white paper and what they could mean for the future of 𝐀𝐈 𝐢𝐧 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬:

1. 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 𝐚𝐫𝐞 𝐦𝐨𝐫𝐞 𝐭𝐡𝐚𝐧 𝐣𝐮𝐬𝐭 𝐬𝐦𝐚𝐫𝐭𝐞𝐫 𝐦𝐨𝐝𝐞𝐥𝐬

2. 𝐀 𝐜𝐨𝐠𝐧𝐢𝐭𝐢𝐯𝐞 𝐚𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐩𝐨𝐰𝐞𝐫𝐬 𝐭𝐡𝐞𝐢𝐫 𝐝𝐞𝐜𝐢𝐬𝐢𝐨𝐧-𝐦𝐚𝐤𝐢𝐧𝐠

3. 𝐓𝐨𝐨𝐥𝐬 𝐞𝐱𝐩𝐚𝐧𝐝 𝐚𝐠𝐞𝐧𝐭𝐬’ 𝐫𝐞𝐚𝐜𝐡 𝐛𝐞𝐲𝐨𝐧𝐝 𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐝𝐚𝐭𝐚

4. 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥-𝐚𝐮𝐠𝐦𝐞𝐧𝐭𝐞𝐝 𝐠𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 𝐦𝐚𝐤𝐞𝐬 𝐚𝐠𝐞𝐧𝐭𝐬 𝐬𝐦𝐚𝐫𝐭𝐞𝐫

5. 𝐆𝐨𝐨𝐠𝐥𝐞 𝐨𝐟𝐟𝐞𝐫𝐬 𝐭𝐨𝐨𝐥𝐬 𝐭𝐨 𝐚𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐞 𝐚𝐠𝐞𝐧𝐭 𝐝𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭

Source: https://bit.ly/4h4Kvlb

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#iot #ai #genai #agenticai #aiagents #business

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𝐓𝐡𝐞 𝐒𝐭𝐚𝐭𝐞 𝐨𝐟 𝐭𝐡𝐞 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 𝐄𝐜𝐨𝐬𝐲𝐬𝐭𝐞𝐦: 𝘛𝘩𝘦 𝘵𝘦𝘤𝘩, 𝘶𝘴𝘦 𝘤𝘢𝘴𝘦𝘴, 𝘢𝘯𝘥 𝘦𝘤𝘰𝘯𝘰𝘮𝘪𝘤𝘴 🚀🚀🚀

Via Insight Partners | December 17, 2024 | @VINCI_Digital

𝐀 𝐫𝐢𝐜𝐡 𝐞𝐜𝐨𝐬𝐲𝐬𝐭𝐞𝐦 𝐨𝐟 𝐀𝐈 𝐀𝐠𝐞𝐧𝐭𝐬 𝐢𝐬 𝐞𝐦𝐞𝐫𝐠𝐢𝐧𝐠 >>> 𝐚 𝐟𝐞𝐰 𝐩𝐫𝐨𝐦𝐢𝐧𝐞𝐧𝐭 𝐚𝐫𝐜𝐡𝐞𝐭𝐲𝐩𝐞𝐬 𝐢𝐧𝐜𝐥𝐮𝐝𝐞:

🔹𝐕𝐞𝐫𝐭𝐢𝐜𝐚𝐥 𝐀𝐠𝐞𝐧𝐭𝐬: Focused on bounded and well-defined tasks that represent a normalized workflow across a company

>>> They combine AI capabilities with deep functional knowledge to address high-volume use cases like Relevance AI for GTM, Harvey and Flank for Legal, and Sierra for customer service

>>> From a pricing perspective, these Agents fit well into a “𝘏𝘪𝘳𝘦-𝘢𝘯-𝘈𝘨𝘦𝘯𝘵” model or an outcome-based pricing model where there can be direct attribution of value

🔹𝐇𝐨𝐫𝐢𝐳𝐨𝐧𝐭𝐚𝐥 𝐚𝐠𝐞𝐧𝐭𝐢𝐜 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬: These platforms integrate common data sources, tools, UX, and guardrails to build Agents for different workflows and user communities across a company

>>> Examples range from Cohere enterprise platform to traditional RPA companies retrofitting agentic solutions

>>> Given the complexity, some companies are using a consultative approach with users-in-the-loop to optimize success rates

>>> Some sophisticated enterprises are taking a build approach leveraging the rich set of Agent tools

>>> In the SMB/knowledge worker space, startups like Bardeen are targeting simpler use cases using no-code platforms and a rapidly increasing library of reusable Agents across users

🔹𝐌𝐮𝐥𝐭𝐢𝐦𝐨𝐝𝐚𝐥 𝐀𝐠𝐞𝐧𝐭𝐬: While multimodality could be a tool in one of the above Agents, there is an evolving class of Agents focused on multimodal workflows

>>> Use cases here range from video manipulation, video generation, and multilingual chatbots with solutions such as Director framework for video or ElevenLabs and Cognigy’s voice Agents

>>> As these powerful new multimodal models launch, User interfaces will tend toward natural human interfaces of voice and images

🔹𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐢𝐧𝐭𝐞𝐫𝐟𝐚𝐜𝐞𝐬 𝐟𝐨𝐫 𝐜𝐥𝐚𝐬𝐬𝐢𝐜𝐚𝐥 𝐒𝐚𝐚𝐒: Incumbent software platforms are adding Agent overlays to capture a large percentage of the workflows that natively happen in the underlying system of record (Agentforce)

>>> These Agents are an efficient value unlock for users invested in these platforms

𝐀𝐠𝐞𝐧𝐭𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐰𝐢𝐥𝐝: 𝐑𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐜𝐚𝐬𝐞 𝐬𝐭𝐮𝐝𝐢𝐞𝐬 𝐨𝐟 𝐀𝐠𝐞𝐧𝐭𝐬 𝐢𝐧 𝐭𝐡𝐞 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞

🔹Developer-facing (SDLC)

AI Agents are augmenting workflows across the Software Development Lifecycle (SDLC), including code generation, end-to-end testing, provisioning infrastructure, approvals, compliance, and even observability.

• Identity Access Management (Production): An asset manager uses AI Agents to automate complex IAM and IaC workflows, including infrastructure provisioning and access approvals. Task-planning Agents coordinate across cloud environments (AWS, Microsoft, on-premises), enabling developers to focus on high-priority coding and saving hours on repetitive tasks.

• Automated testing and provisioning (Production): A global holdings corporation leverages AI Agents to automate user story creation, test case generation, and infrastructure tasks like setting up VMs and managing deployments via Terraform. This reduces DevOps, TPM, and SRE overhead, freeing teams to focus on complex development challenges.

• Code generation and compliance (Production): A large bank employs AI Agents for code commenting, unit testing, regulatory compliance, and validating data models, minimizing errors while prioritizing quality and reducing manual workload across its software lifecycle.

• AI for software development at AT&T (Production): AT&T uses autonomous Agents to streamline software development by automating user story creation, coding, and test execution. A “master Agent” oversees task-specific Agents, allowing developers to tackle complex issues while the AI handles routine operations.

🔹Customer experience

AI Agents in customer experience can transform brand interactions by delivering personalized, seamless journeys and improving service quality across channels.

• Retail advisor training (Experiment): A beauty retailer uses an AI Agent as a virtual beauty advisor to onboard and train store associates. Drawing on chatbot interactions from the COVID-19 era, the Agent builds a knowledge platform to enhance product knowledge and customer service as part of a three-year program.

• Product discovery and assistance (Experiment): A retail giant deploys AI Agents across the customer journey, from product discovery to post-purchase support. Category-specific Agents for hair care and skincare provide tailored assistance via a natural language web interface, integrating in-store and online customer context.

• Gift finder experience (Experiment): For the holiday season, a retailer pilots an AI Agent offering personalized gift recommendations. The Agent analyzes prior customer interactions, product catalogs, and customer preferences, including skin characteristics, to suggest ideal products.

• Customer service AI Agent (Buy): A customer service solutions provider uses AI Agents to assist human Agents by automating repetitive tasks, suggesting responses, and streamlining workflows. This builds on call-center AI use cases, leveraging agentic workflows for real-time approvals, document completion, and data gathering.

• Insurance loan AI sales Agent (Buy): A leading EU bank employs outbound voice AI Agents to increase conversions for loan insurance products. The Agent proactively calls customers who abandoned transactions, using a natural voice and personalized insights to re-engage and convert them.

🔹Backoffice (Finance, Procurement)

AI Agents streamline back-office operations by automating tasks like inventory monitoring, invoicing, and research. Thus, they reduce errors and workloads and improve decision-making with data-driven insights.

• Supply chain inventory and triage (Production): A consumer goods company uses AI Agents to monitor stock levels, trigger replenishment orders, and address availability issues, preventing stockouts and ensuring product availability.

• Automated invoicing (Production): The same consumer goods company employs AI-driven invoicing Agents that streamline invoice processing, enhancing accuracy, and reducing manual tasks in finance.

• Research and document analysis (Production): An investment bank uses AI Agents for research tasks such as reading unstructured documents, summarizing content, and mapping company names to tickers for investment analysis.

• Stock behavior forecasting (Experiment): A financial exchange leverages AI to predict stock behavior based on historical data and real-time trends, providing insights for trading decisions.

• Financial auditing (Buy): KPMG has deployed teams of AI Agents that autonomously plan, coordinate, and execute actions under human supervision for audit, tax, and advisory workflows.

🔹Data analysis

AI Agents can enhance data-intensive workflows by managing, analyzing, and ensuring data quality, enabling reliable insights with minimal human effort.

• Cloud usage analysis (Experiment): An industrial solutions firm’s cloud data AI Agent detects anomalies and suggests cost-saving optimizations. Their AI Agent can interface between platforms like AWS Cloudwatch, Azure, and Google Cloud’s FinOps platforms, ingest structured data, and identify abnormalities around cloud usage.

• Text-to-SQL and data analysis (Production): A global telecom company utilizes a Multi-Agent system to interpret natural language queries to convert text to SQL. The system determines the relevant database, identifies the appropriate tables and columns, generates the SQL query, and employs a reflection Agent to verify and refine the output.

• Compliance-driven data querying (Production): A financial services firm’s AI Agents perform data queries and compliance checks, ensuring internal data quality control and compliance adherence without exposing client data directly.

🔹Operations

From document summarization to network diagnostics and workflow management in clinical settings, these Agents speed up critical processes and ensure quality control. Their ability to generate comprehensive reports and insights can help executives and employees make quicker, more informed decisions.

• Automated network diagnostics (Production): A global telecom employs an AI Agent to identify and resolve network issues, reducing manual diagnostics time. The Agent analyzes complex logs and structured data tables to detect abnormalities and alert the appropriate security or development team.

• Executive reporting and knowledge retrieval (Production): A second investment bank leverages AI Agents to produce monthly executive briefing reports. Functional Agents collect business metrics company-wide, while a drafting Agent compiles and finalizes the CEO’s tear sheet for enhanced decision-making.

Source: https://bit.ly/3W7Y7UO

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#iot #ai #genai #agenticai #aiagents #casestudies

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𝐆𝐞𝐧 𝐀𝐈 𝐢𝐧 𝟐𝟎𝟐𝟓: 𝐏𝐥𝐚𝐲𝐭𝐢𝐦𝐞 𝐢𝐬 𝐨𝐯𝐞𝐫, 𝐭𝐢𝐦𝐞 𝐭𝐨 𝐠𝐞𝐭 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐚𝐥! 𝘗𝘪𝘭𝘰𝘵 𝘧𝘢𝘵𝘪𝘨𝘶𝘦, 𝘢𝘪𝘮𝘭𝘦𝘴𝘴 𝘦𝘹𝘱𝘦𝘳𝘪𝘮𝘦𝘯𝘵𝘢𝘵𝘪𝘰𝘯, 𝘢𝘯𝘥 𝘧𝘢𝘪𝘭𝘶𝘳𝘦 𝘳𝘢𝘵𝘦𝘴 𝘩𝘢𝘷𝘦 𝘮𝘢𝘯𝘺 𝘰𝘳𝘨𝘢𝘯𝘪𝘻𝘢𝘵𝘪𝘰𝘯𝘴 𝘴𝘩𝘪𝘧𝘵𝘪𝘯𝘨 𝘨𝘦𝘯𝘦𝘳𝘢𝘵𝘪𝘷𝘦 𝘈𝘐 𝘪𝘯𝘷𝘦𝘴𝘵𝘮𝘦𝘯𝘵𝘴 𝘵𝘰𝘸𝘢𝘳𝘥 𝘮𝘰𝘳𝘦 𝘵𝘢𝘳𝘨𝘦𝘵𝘦𝘥 — 𝘢𝘯𝘥 𝘱𝘳𝘰𝘮𝘪𝘴𝘪𝘯𝘨 — 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴 𝘶𝘴𝘦 𝘤𝘢𝘴𝘦𝘴 🚀🚀🚀

Via CIO Online / By Grant Gross | January 2, 2025 | @VINCI_Digital

🔹𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 playtime may be over, as organizations cut down on experimentation and pivot toward achieving 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐯𝐚𝐥𝐮𝐞, with a focus on fewer, 𝐦𝐨𝐫𝐞 𝐭𝐚𝐫𝐠𝐞𝐭𝐞𝐝 𝐮𝐬𝐞 𝐜𝐚𝐬𝐞𝐬

🔹Nearly nine out of 10 senior decision-makers said they have gen AI pilot fatigue and are shifting their investments to projects that will 𝐢𝐦𝐩𝐫𝐨𝐯𝐞 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐩𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞, according to a recent survey from NTT DATA

"However, organizations expect the assessment of complementary technologies, including IoT, to be the number-one challenge in adopting GenAI in the next two years"

🔹Organizations will still experiment with new gen AI pilots, but a more targeted approach focused on use cases specific to their businesses is increasingly becoming central to IT leaders’ AI strategies, says Andrew Wells, chief data and AI officer for NTT DATA North America

🔹NTT DATA | 𝑮𝒍𝒐𝒃𝒂𝒍 𝑮𝒆𝒏𝑨𝑰 𝑹𝒆𝒑𝒐𝒓𝒕 >>> https://services.global.ntt/en-us/campaigns/global-genai-report

Source: https://www.cio.com/article/3629824/gen-ai-in-2025-playtime-is-over-time-to-get-practical.html

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#industrial #iot #ai #genai #business #usecases

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𝐖𝐡𝐚𝐭’𝐬 𝐧𝐞𝐱𝐭 𝐟𝐨𝐫 𝐀𝐈? 𝘞𝘩𝘪𝘭𝘦 𝘭𝘢𝘳𝘨𝘦 𝘭𝘢𝘯𝘨𝘶𝘢𝘨𝘦 𝘮𝘰𝘥𝘦𝘭𝘴 𝘤𝘰𝘯𝘵𝘪𝘯𝘶𝘦 𝘵𝘰 𝘢𝘥𝘷𝘢𝘯𝘤𝘦, 𝘯𝘦𝘸 𝘮𝘰𝘥𝘦𝘭𝘴 𝘢𝘯𝘥 𝘢𝘨𝘦𝘯𝘵𝘴 𝘢𝘳𝘦 𝘱𝘳𝘰𝘷𝘪𝘯𝘨 𝘵𝘰 𝘣𝘦 𝘮𝘰𝘳𝘦 𝘦𝘧𝘧𝘦𝘤𝘵𝘪𝘷𝘦 𝘢𝘵 𝘥𝘪𝘴𝘤𝘳𝘦𝘵𝘦 𝘵𝘢𝘴𝘬𝘴. 𝘈𝘐 𝘯𝘦𝘦𝘥𝘴 𝘥𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘵 𝘩𝘰𝘳𝘴𝘦𝘴 𝘧𝘰𝘳 𝘥𝘪𝘧𝘧𝘦𝘳𝘦𝘯𝘵 𝘤𝘰𝘶𝘳𝘴𝘦𝘴 🚀🚀🚀

Via Deloitte / Deloitte Consulting / Deloitte Digital / Deloitte Insights - By Kelly Raskovich, Bill Briggs, Mike Bechtel, Abhijith Ravinutala | December 11, 2024 | @VINCI_Digital

𝐋𝐞𝐚𝐝𝐢𝐧𝐠 𝐨𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 𝐚𝐫𝐞 𝐚𝐥𝐫𝐞𝐚𝐝𝐲 𝐜𝐨𝐧𝐬𝐢𝐝𝐞𝐫𝐢𝐧𝐠 𝐀𝐈’𝐬 𝐧𝐞𝐱𝐭 𝐜𝐡𝐚𝐩𝐭𝐞𝐫

🔹Instead of relying on foundation models built by large players in 𝐀𝐈, which may be more powerful and built on more data than needed, enterprises are now thinking about implementing 𝐦𝐮𝐥𝐭𝐢𝐩𝐥𝐞, 𝐬𝐦𝐚𝐥𝐥𝐞𝐫 𝐦𝐨𝐝𝐞𝐥𝐬 𝐭𝐡𝐚𝐭 𝐜𝐚𝐧 𝐛𝐞 𝐦𝐨𝐫𝐞 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭 𝐟𝐨𝐫 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐫𝐞𝐪𝐮𝐢𝐫𝐞𝐦𝐞𝐧𝐭𝐬.

🔹𝐋𝐋𝐌𝐬 will continue to advance and be the best option for certain use cases, like general-purpose chatbots or simulations for scientific research, but the chatbot that peruses your financial data to think through missed revenue opportunities doesn’t need to be the same model that replies to customer inquiries.

𝑷𝒖𝒕 𝒔𝒊𝒎𝒑𝒍𝒚, 𝒘𝒆’𝒓𝒆 𝒍𝒊𝒌𝒆𝒍𝒚 𝒕𝒐 𝒔𝒆𝒆 𝒂 𝒑𝒓𝒐𝒍𝒊𝒇𝒆𝒓𝒂𝒕𝒊𝒐𝒏 𝒐𝒇 𝒅𝒊𝒇𝒇𝒆𝒓𝒆𝒏𝒕 𝒉𝒐𝒓𝒔𝒆𝒔 𝒇𝒐𝒓 𝒅𝒊𝒇𝒇𝒆𝒓𝒆𝒏𝒕 𝒄𝒐𝒖𝒓𝒔𝒆𝒔 >>>🏇 🐎 🐴 🎠

🔹A series of 𝐬𝐦𝐚𝐥𝐥𝐞𝐫 𝐦𝐨𝐝𝐞𝐥𝐬 [𝐒𝐋𝐌𝐬] working in concert may end up serving different use cases than current 𝐋𝐋𝐌 approaches. New 𝐨𝐩𝐞𝐧-𝐬𝐨𝐮𝐫𝐜𝐞 𝐨𝐩𝐭𝐢𝐨𝐧𝐬 𝐚𝐧𝐝 𝐦𝐮𝐥𝐭𝐢𝐦𝐨𝐝𝐚𝐥 𝐨𝐮𝐭𝐩𝐮𝐭𝐬 (𝘢𝘴 𝘰𝘱𝘱𝘰𝘴𝘦𝘥 𝘵𝘰 𝘫𝘶𝘴𝘵 𝘵𝘦𝘹𝘵) are enabling organizations to unlock entirely new offerings.

🔹In the years to come, the progress toward a growing number of 𝐬𝐦𝐚𝐥𝐥𝐞𝐫, 𝐦𝐨𝐫𝐞 𝐬𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐳𝐞𝐝 𝐦𝐨𝐝𝐞𝐥𝐬 could once again move the goalposts of 𝐀𝐈 in the enterprise.

𝑶𝒓𝒈𝒂𝒏𝒊𝒛𝒂𝒕𝒊𝒐𝒏𝒔 𝒎𝒂𝒚 𝒘𝒊𝒕𝒏𝒆𝒔𝒔 𝒂 𝒇𝒖𝒏𝒅𝒂𝒎𝒆𝒏𝒕𝒂𝒍 𝒔𝒉𝒊𝒇𝒕 𝒊𝒏 𝐀𝐈 𝒇𝒓𝒐𝒎 𝒂𝒖𝒈𝒎𝒆𝒏𝒕𝒊𝒏𝒈 𝒌𝒏𝒐𝒘𝒍𝒆𝒅𝒈𝒆 𝒕𝒐 𝒂𝒖𝒈𝒎𝒆𝒏𝒕𝒊𝒏𝒈 𝒆𝒙𝒆𝒄𝒖𝒕𝒊𝒐𝒏

🔹Investments being made today in 𝐚𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈, as this next era is termed, could upend the way we work and live by arming consumers and businesses with armies of silicon-based assistants.

🔹Imagine 𝐀𝐈 𝐚𝐠𝐞𝐧𝐭𝐬 that can carry out discrete tasks, like delivering a financial report in a board meeting or applying for a grant.

“𝑻𝒉𝒆𝒓𝒆’𝒔 𝒂𝒏 𝒂𝒑𝒑 𝒇𝒐𝒓 𝒕𝒉𝒂𝒕” could well become “𝑻𝒉𝒆𝒓𝒆’𝒔 𝒂𝒏 𝒂𝒈𝒆𝒏𝒕 𝒇𝒐𝒓 𝒕𝒉𝒂𝒕.” >>> 🤖 🤖 🤖

Source: https://www2.deloitte.com/us/en/insights/focus/tech-trends.html#what%E2%80%99s-next-for-ai

VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

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#ai #genai #aiagents #llms #slms #multimodal

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Bio: :🔹Fabio Bottacci is a relationship builder, creative problem solver, and strategic thinker. Senior industrial executive and former strategic consultant, he acquired a solid background in large multinational organizations across Brazil, US, and Western Europe. He is known for his ability to deliver results despite ambiguity and obstacles, to build bridges between people, and to manage conflict and negotiations.

Fabio graduated in Economics & Business Administration from Università Bocconi and from Stanford University School of Engineering in Internet of Things [IoT]. Recently, Fabio has successfully completed a Private Equity & Venture Capital course by SDA Bocconi [Final Grade: 94%], and two accredited certifications: Generative AI by Databricks Academy and Generative AI by Andrew Ng, founder DeepLearning.AI [Final Grade: 96%].

He began his career at Accenture Italia/Accenture, strategy practice, while attending MBA courses. He then moved to Brazil, where he consistently proved, during more than 20 years of professional experience, strong clients' network, industry knowledge and business development expertise in the automotive, oil and gas, energy, and utilities verticals.

Since 2015, he has been the founder & CEO @VINCI Digital | IIoT + AI/GenAI Strategic Advisory 🚀 , being recognized internationally as a thought leader by well-known organizations, such as the World Economic Forum, the IOT Solutions World Congress, and the BNDES (Brazilian Federal Development Bank), and - lately - the Harvard Business Review Advisory Council.

Recently, Fabio has been contracted by Bain & Company as Senior Advisor to its Advanced Manufacturing & Services and Energy & Natural Resources global practices, with a particular focus on Industrial IoT + AI / Generative AI's end-to-end solutions and their actual deployment, at-scale, within the Oil & Energy / Utilities, Metals & Mining, Automotive, Agriculture, and Pulp & Paper verticals.

In 2023, he had joined the European Research Executive Agency (REA) as an Industrial IoT + AI / Generative AI Expert and Evaluator for the HORIZON Europe Programme of the European Commission, and Kobo Funds as Venture Partner, focused on Deeptech Seed/Series A startups, helping investors work successfully with entrepreneurs.

Fabio's mission is to help startups/scaleups, SME, and corporations to thrive within the current digital transformation environment, by increasing productivity, developing new business models, and delivering actual results / ROI in months, not years!

NO MAGIC! >>>It's all about data >>> quality, reliable, consistent data... 😉😉😉

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VINCI Digital | IIoT + AI / GenAI Strategic Advisory 🚀

#industrial #iot #iiot #ai #genai #generativeai #agenticai #aiagents #casestudies #insights #perspectives

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