🏭 Industrial AI 🤖 >>> Actual Case Studies, Insights & Perspectives 🚀🚀🚀 | January 2026

Hello everyone,

First of all, better late than never >>> Happy New Year! 🎇🎆🎇

After well-deserved holidays/rest time — in order to opportunely recharge our “human“ batteries — we are entering 2026 at full force/speed, testifying an acceleration on physical AI / robotics investments and respective actual tests/pilots, especially in the industrial sector 🏭.

As most of you for sure already noticed, humanoids development is taking the stage! 🦾🤖🦿

I dare say that in 2026 most of humanoids’ demos/teleoperations, constantly showed off to sustain the hype/$$$, will come to a reckoning

>>> REALITY CHECK! <<<

starting in such a way the highly expected natural evolution/selection process amid the hundreds of auto-certified “industrial-grade/efficiently scalable“ humanoids vendors currently present in the market.

Looking forward to it! 😉

Ciao, Fabio

Boston Dynamics “Atlas” Industrial / All-Electric Humanoid Robot, Unveiled @CES 2026

VINCI Digital | Industrial AI Strategic Advisory 🚀

#industrialai #industrial #iot #iiot #ai #genai #aiagents #agenticai #physicalai #robotics #humanoids #casestudies #insights #perspectives #realitycheck

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🏭 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐀𝐈 𝐢𝐧 𝟐𝟎𝟐𝟔 🤖: 𝘛𝘩𝘦 “𝘏𝘢𝘳𝘥-𝘏𝘦𝘢𝘥𝘦𝘥 𝘌𝘷𝘢𝘭𝘶𝘢𝘵𝘪𝘰𝘯” 𝘪𝘴 𝘧𝘪𝘯𝘢𝘭𝘭𝘺 𝘩𝘦𝘳𝘦 >>> 𝐀𝐫𝐞 𝐲𝐨𝐮 𝐫𝐞𝐚𝐝𝐲 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐫𝐞𝐚𝐥𝐢𝐭𝐲 𝐜𝐡𝐞𝐜𝐤?

By 🔹Fabio Bottacci, founder & CEO @VINCI Digital | Industrial AI Strategic Advisory 🚀

✅ Financial Times just published what every industrial executive needs to hear: after two years of AI experimentation (2024) and implementation (2025), 𝐰𝐞’𝐫𝐞 𝐞𝐧𝐭𝐞𝐫𝐢𝐧𝐠 𝐭𝐡𝐞 𝐞𝐫𝐚 𝐨𝐟 𝐡𝐚𝐫𝐝-𝐡𝐞𝐚𝐝𝐞𝐝 𝐞𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧!

✅ The industry must now answer three uncomfortable questions to justify the projected $𝟓𝟎𝟎+billion AI capex in 2026

The question isn’t “𝑪𝒂𝒏 𝒘𝒆 𝒅𝒆𝒑𝒍𝒐𝒚 𝑨𝑰?” It’s “𝑪𝒂𝒏 𝒘𝒆 𝒅𝒆𝒎𝒐𝒏𝒔𝒕𝒓𝒂𝒕𝒆 𝒄𝒍𝒆𝒂𝒓 𝑹𝑶𝑰?”

1️⃣ Is scaling dead?

🔹Generative AI may be hitting computational limits

🔹The game is shifting from “throw more compute at it“ to smarter algorithms and 𝐧𝐞𝐮𝐫𝐨𝐬𝐲𝐦𝐛𝐨𝐥𝐢𝐜 𝐀𝐈 >>> 𝐦𝐞𝐫𝐠𝐢𝐧𝐠 𝐝𝐚𝐭𝐚-𝐝𝐫𝐢𝐯𝐞𝐧 𝐧𝐞𝐮𝐫𝐚𝐥 𝐧𝐞𝐭𝐰𝐨𝐫𝐤𝐬 𝐰𝐢𝐭𝐡 𝐫𝐮𝐥𝐞𝐬-𝐛𝐚𝐬𝐞𝐝 𝐬𝐲𝐦𝐛𝐨𝐥𝐢𝐜 𝐫𝐞𝐚𝐬𝐨𝐧𝐢𝐧𝐠

🔹Translation for industrial leaders >>> your AI strategy can’t rely on brute force anymore!

2️⃣ Where’s the viable business model?

🔹As AI commoditizes, the differentiation battle intensifies: Some hyperscalers will win

🔹Many AI startups planning 2026 IPOs (OpenAI, Anthropic) still need to prove they can build sustainable competitive moats

3️⃣ The Chinese disruption nobody saw coming

🔹DeepSeek AI‘s $𝟓.𝟓𝐌 training cost (vs. $100M+ for Western competitors) wasn’t a fluke

🔹Chinese open-weight models now command 𝟏𝟕% of global downloads vs. US 𝟏𝟓.𝟖%, the 1st time China has overtaken the US in this critical segment

🔹Even Sam Altman admitted OpenAI might be on “the wrong side of history”

4️⃣ Why this matters for industrial sectors?

The FT nails it: “𝘛𝘩𝘪𝘴 𝘺𝘦𝘢𝘳 𝘣𝘰𝘵𝘩 𝘶𝘴𝘦𝘳𝘴 𝘢𝘯𝘥 𝘪𝘯𝘷𝘦𝘴𝘵𝘰𝘳𝘴 𝘸𝘪𝘭𝘭 𝘥𝘪𝘴𝘤𝘳𝘪𝘮𝘪𝘯𝘢𝘵𝘦 𝘣𝘦𝘵𝘸𝘦𝘦𝘯 𝘵𝘩𝘰𝘴𝘦 𝘴𝘦𝘳𝘷𝘪𝘤𝘦𝘴 𝘢𝘯𝘥 𝘣𝘶𝘴𝘪𝘯𝘦𝘴𝘴𝘦𝘴 𝘵𝘩𝘢𝘵 𝘰𝘧𝘧𝘦𝘳 𝘳𝘦𝘢𝘭 𝘷𝘢𝘭𝘶𝘦 𝘢𝘯𝘥 𝘵𝘩𝘰𝘴𝘦 𝘵𝘩𝘢𝘵 𝘩𝘢𝘷𝘦 𝘫𝘶𝘴𝘵 𝘣𝘦𝘦𝘯 𝘰𝘱𝘱𝘰𝘳𝘵𝘶𝘯𝘪𝘴𝘵𝘪𝘤𝘢𝘭𝘭𝘺 𝘴𝘶𝘳𝘧𝘪𝘯𝘨 𝘵𝘩𝘦 𝘈𝘐 𝘩𝘺𝘱𝘦 𝘸𝘢𝘷𝘦”

5️⃣ The unsexy truth I’ve been preaching

🔹 80-90% of industrial AI ROI still comes from predictive maintenance, computer vision, and visual inspection—not the sexy generative AI everyone’s chasing

>>> You need data quality, infrastructure, and foundation first!

🔹Conservative? Yes. Effective?

The HEINEKEN Company‘s CTO reports 𝟗𝟓% of worldwide operations achieved results from this pragmatic approach

𝐀𝐬 𝟐𝟎𝟐𝟔 𝐮𝐧𝐟𝐨𝐥𝐝𝐬, 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐥𝐞𝐚𝐝𝐞𝐫𝐬 𝐰𝐢𝐥𝐥 𝐬𝐞𝐩𝐚𝐫𝐚𝐭𝐞 𝐢𝐧𝐭𝐨 𝐭𝐰𝐨 𝐜𝐚𝐦𝐩𝐬: 𝐭𝐡𝐨𝐬𝐞 𝐰𝐡𝐨 𝐜𝐡𝐚𝐬𝐞 𝐡𝐞𝐚𝐝𝐥𝐢𝐧𝐞𝐬 𝐚𝐧𝐝 𝐭𝐡𝐨𝐬𝐞 𝐰𝐡𝐨 𝐜𝐡𝐚𝐬𝐞 𝐦𝐞𝐚𝐬𝐮𝐫𝐚𝐛𝐥𝐞 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐨𝐮𝐭𝐜𝐨𝐦𝐞𝐬!😉

Ciao, Fabio

Source: https://on.ft.com/4q7yyQP

VINCI Digital | Industrial AI Strategic Advisory 🚀

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Figure Drops Helix 02, a Unified 🤖 Robot Brain 🧠

Via Figure / The Rundown AI Robotics | January 27 / 29, 2026 | @VINCI_Digital

System 0: Human-like Whole-body Control from Human Data | Figure

California robotics startup Figure just unveiled Helix 02, a unified AI control system that replaces 109K lines of hand-tuned C++ with a 10M‑parameter neural network that teaches robots to move more like humans

✅ Each system operates at its natural timescale

🔹System 2 (S2) reasons slowly about goals: interpreting scenes, understanding language, and sequencing behaviors

🔹System 1 (S1) thinks fast, translating perception into full‑body joint targets at 200 Hz

🔹System 0 (S0) executes at 1 kHz, handling balance, contact, and coordination across the entire body

Together, they form a tightly integrated hierarchy from pixels to torque

Helix 02 extends Figure ‘System1, System 2” architecture with a new foundation layer: System 0 | Figure

Key facts

🔹Figure demoed what it claims is the ‘most complex’ autonomous humanoid task to date: a 4-minute, 61-action dishwasher cycle across a full-sized kitchen

🔹The Figure 03 robot now uses its entire body as a tool — closing drawers with its hip and lifting the dishwasher door with its foot when hands are occupied

🔹New palm cameras and tactile sensors — sensitive to three grams — enable dexterous tasks previously out of reach, like unscrewing bottle caps

🔹The system executes whole-body control at 1 kHz, taking full-body joint state as input and outputting actuator commands directly to every joint

Helix 02 / Figure 03 >>> Dexterity task: “Pick metal pieces from a cluttered box” | Figure

Why it matters

✅ Fusing walking, grasping, and sensing into one learned system moves humanoids from scripted demos to continuous autonomy in unpredictable environments

✅ Branding the AI separately from the hardware hints at a longer play: a general-purpose robot brain for platforms beyond Figure 03

Image source: Figure / Reve

Sources

Figure: https://www.figure.ai/news/helix-02

The Rundown AI Robotics:

https://robotnews.therundown.ai/p/waabi-nabs-1b-in-uber-robotaxi-deal

VINCI Digital | Industrial AI Strategic Advisory 🚀

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🤖 𝐓𝐡𝐞 𝐏𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐀𝐈 𝐌𝐨𝐝𝐞𝐥𝐬 𝐌𝐚𝐫𝐤𝐞𝐭 𝐌𝐚𝐩 🤖: 𝘉𝘦𝘩𝘪𝘯𝘥 𝘵𝘩𝘦 𝘢𝘳𝘮𝘴 𝘳𝘢𝘤𝘦 𝘵𝘰 𝘤𝘰𝘯𝘵𝘳𝘰𝘭 𝘳𝘰𝘣𝘰𝘵 𝘪𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘤𝘦 🚀🚀🚀

Via CB Insights | January 22, 2026 | @VINCI_Digital

CB Insights mapped 𝟕𝟎+ companies developing:

🔹data infrastructure

🔹AI models

🔹observability tools

>>> that bring intelligence to the 𝘱𝘩𝘺𝘴𝘪𝘤𝘢𝘭 𝘸𝘰𝘳𝘭𝘥 🏭

✅ The 𝐫𝐨𝐛𝐨𝐭𝐢𝐜𝐬 𝐬𝐞𝐜𝐭𝐨𝐫 raised a record $𝟒𝟎.𝟕𝐁 in 2025 — up 𝟕𝟒% YoY and 9% of all venture funding — making it a 𝐟𝐮𝐧𝐝𝐢𝐧𝐠 𝐥𝐞𝐚𝐝𝐞𝐫 alongside AI software

✅ 𝐏𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐀𝐈 is driving this progress, 𝘦𝘯𝘢𝘣𝘭𝘪𝘯𝘨 𝘳𝘰𝘣𝘰𝘵𝘴 𝘵𝘰 𝘰𝘱𝘦𝘳𝘢𝘵𝘦 𝘪𝘯 𝘵𝘩𝘦 𝘱𝘩𝘺𝘴𝘪𝘤𝘢𝘭 𝘸𝘰𝘳𝘭𝘥 𝘢𝘯𝘥 𝘭𝘦𝘢𝘳𝘯 𝘧𝘳𝘰𝘮 𝘥𝘢𝘵𝘢 𝘳𝘢𝘵𝘩𝘦𝘳 𝘵𝘩𝘢𝘯 𝘱𝘳𝘦-𝘱𝘳𝘰𝘨𝘳𝘢𝘮𝘮𝘦𝘥 𝘳𝘶𝘭𝘦𝘴

<<< 𝐓𝐡𝐞 𝐫𝐚𝐜𝐞 𝐜𝐞𝐧𝐭𝐞𝐫𝐬 𝐨𝐧 𝐛𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐟𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐦𝐨𝐝𝐞𝐥𝐬 𝐟𝐨𝐫 𝐫𝐨𝐛𝐨𝐭𝐬 𝐭𝐨 𝐥𝐞𝐚𝐫𝐧 𝐚𝐜𝐫𝐨𝐬𝐬 𝐭𝐚𝐬𝐤𝐬 >>>

✅ Unlike language models trained on text, the 𝐩𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐀𝐈 𝐦𝐨𝐝𝐞𝐥𝐬 that power these systems require 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐫𝐨𝐛𝐨𝐭 𝐝𝐚𝐭𝐚, creating an early window for market control

✅ In the market map below, CB Insights identified 𝟕𝟎+ companies — 𝘢𝘤𝘳𝘰𝘴𝘴 10 𝘱𝘩𝘺𝘴𝘪𝘤𝘢𝘭 𝘈𝘐 𝘮𝘰𝘥𝘦𝘭 𝘤𝘢𝘵𝘦𝘨𝘰𝘳𝘪𝘦𝘴 — organized these companies into the following groups:

🔹𝐃𝐚𝐭𝐚 & 𝐬𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧

>>> Synthetic data generation, real-world robot demonstrations, and simulation platforms where robots learn in virtual environments

🔹𝐌𝐨𝐝𝐞𝐥 𝐚𝐩𝐩𝐫𝐨𝐚𝐜𝐡𝐞𝐬

>>> Core AI architectures that enable robots to understand their environment (VLMs), generate actions (VLAs), and predict outcomes (world models)

🔹𝐅𝐨𝐮𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐦𝐨𝐝𝐞𝐥𝐬

>>> Pre-trained robot intelligence that combines various model architectures for general manipulation and inference, autonomous driving, and multi-robot coordination

🔹Observability

>>> Platforms that monitor deployed robots and feed real-world data back into training to improve performance

𝐊𝐞𝐲 𝐭𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬

1️⃣ 𝐏𝐫𝐨𝐩𝐫𝐢𝐞𝐭𝐚𝐫𝐲 𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐝𝐚𝐭𝐚 is a critical competitive advantage for physical AI, with tech leaders racing to secure access through acquisitions

2️⃣ 𝐖𝐨𝐫𝐥𝐝 𝐦𝐨𝐝𝐞𝐥𝐬 𝐞𝐧𝐚𝐛𝐥𝐞 𝐫𝐨𝐛𝐨𝐭𝐬 𝐭𝐨 𝐩𝐫𝐞𝐝𝐢𝐜𝐭 𝐚𝐧𝐝 𝐩𝐥𝐚𝐧 𝐚𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬𝐥𝐲 — a capability beyond what large-language models (LLMs) can achieve

3️⃣ 𝐌𝐮𝐥𝐭𝐢-𝐫𝐨𝐛𝐨𝐭 𝐜𝐨𝐨𝐫𝐝𝐢𝐧𝐚𝐭𝐢𝐨𝐧 remains the critical missing piece in physical AI

Source: https://bit.ly/4qNmOU0

VINCI Digital | Industrial AI Strategic Advisory 🚀

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🤖 𝐇𝐮𝐦𝐚𝐧𝐨𝐢𝐝 𝐑𝐨𝐛𝐨𝐭 𝐀𝐥𝐩𝐡𝐚 𝐂𝐨𝐦𝐩𝐥𝐞𝐭𝐞𝐬 𝐋𝐢𝐯𝐞 𝐒𝐢𝐞𝐦𝐞𝐧𝐬 𝐋𝐨𝐠𝐢𝐬𝐭𝐢𝐜𝐬 𝐓𝐫𝐢𝐚𝐥 𝐚𝐭 𝟔𝟎 𝐓𝐨𝐭𝐞𝐬 𝐚𝐧 𝐇𝐨𝐮𝐫 🏭️: 𝘈𝘭𝘱𝘩𝘢 𝘮𝘰𝘷𝘦𝘥 60 𝘵𝘰𝘵𝘦𝘴/𝘩𝘰𝘶𝘳, 𝘩𝘢𝘯𝘥𝘭𝘦𝘥 𝘵𝘸𝘰 𝘴𝘪𝘻𝘦𝘴, 𝘳𝘢𝘯 𝘧𝘰𝘳 30+ 𝘮𝘪𝘯 𝘢𝘶𝘵𝘰𝘯𝘰𝘮𝘰𝘶𝘴𝘭𝘺, 𝘢𝘤𝘩𝘪𝘦𝘷𝘦𝘥 8+ 𝘩𝘳 𝘶𝘱𝘵𝘪𝘮𝘦, 𝘢𝘯𝘥 𝘢𝘤𝘩𝘪𝘦𝘷𝘦𝘥 90 𝘱𝘦𝘳𝘤𝘦𝘯𝘵 𝘱𝘪𝘤𝘬-𝘢𝘯𝘥-𝘱𝘭𝘢𝘤𝘦 𝘴𝘶𝘤𝘤𝘦𝘴𝘴 🚀🚀🚀

Via Interesting Engineering | January 16, 2026 | @VINCI_Digital

Humanoid @Siemens | Testing Humanoid Robots in Industrial Logistics

✅ AI and robotics firm Humanoid and industrial technology giant Siemens have completed a proof-of-concept demonstrating 𝐡𝐮𝐦𝐚𝐧𝐨𝐢𝐝 𝐫𝐨𝐛𝐨𝐭𝐬 𝘪𝘯 𝘢𝘤𝘵𝘪𝘷𝘦 𝘪𝘯𝘥𝘶𝘴𝘵𝘳𝘪𝘢𝘭 𝘭𝘰𝘨𝘪𝘴𝘵𝘪𝘤𝘴

✅ The trial saw Humanoid’s 𝐇𝐌𝐍𝐃 𝟎𝟏 wheeled 𝐀𝐥𝐩𝐡𝐚 robot operate in 𝐫𝐞𝐚𝐥 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 at a Siemens facility, 𝘩𝘢𝘯𝘥𝘭𝘪𝘯𝘨 𝘵𝘢𝘴𝘬𝘴 𝘶𝘯𝘥𝘦𝘳 𝘭𝘪𝘷𝘦 𝘰𝘱𝘦𝘳𝘢𝘵𝘪𝘰𝘯𝘢𝘭 𝘤𝘰𝘯𝘥𝘪𝘵𝘪𝘰𝘯

✅ The companies said the deployment marks an early step toward using 𝐡𝐮𝐦𝐚𝐧𝐨𝐢𝐝 𝐫𝐨𝐛𝐨𝐭𝐬 𝐢𝐧 𝐟𝐚𝐜𝐭𝐨𝐫𝐢𝐞𝐬 𝐚𝐧𝐝 𝐰𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞𝐬, and the start of a broader partnership to test and validate their 𝐫𝐞𝐚𝐥-𝐰𝐨𝐫𝐥𝐝 𝐢𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐮𝐬𝐞

🏭️ 𝐖𝐨𝐫𝐤𝐢𝐧𝐠 𝐭𝐡𝐞 𝐒𝐡𝐨𝐩 𝐅𝐥𝐨𝐨𝐫 🏭️

✅ Robotics startup Humanoid just completed a proof-of-concept at a 𝒍𝒊𝒗𝒆 Siemens facility, where its wheeled 𝐇𝐌𝐍𝐃 𝟎𝟏 𝐀𝐥𝐩𝐡𝐚 𝐡𝐮𝐦𝐚𝐧𝐨𝐢𝐝 handled logistics tasks for 𝘵𝘸𝘰 𝘸𝘦𝘦𝘬𝘴 𝘴𝘵𝘳𝘢𝘪𝘨𝘩𝘵

✅ 𝐀𝐥𝐩𝐡𝐚:

🔹 moved 𝟔𝟎 𝐭𝐨𝐭𝐞𝐬 𝐩𝐞𝐫 𝐡𝐨𝐮𝐫

🔹 achieved 𝟗𝟎% 𝐩𝐢𝐜𝐤-𝐚𝐧𝐝-𝐩𝐥𝐚𝐜𝐞 𝐚𝐜𝐜𝐮𝐫𝐚𝐜𝐲

🔹 and 𝐫𝐚𝐧 𝐚𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬𝐥𝐲 for 𝟑𝟎+ 𝐦𝐢𝐧𝐮𝐭𝐞𝐬 at a time, an early step toward deploying humanoids in 𝐚𝐜𝐭𝐢𝐯𝐞 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐞𝐧𝐯𝐢𝐫𝐨𝐧𝐦𝐞𝐧𝐭𝐬!

📹 𝘞𝘢𝘵𝘤𝘩 𝘪𝘵 𝘪𝘯 𝘢𝘤𝘵𝘪𝘰𝘯 𝘩𝘦𝘳𝘦! 📹 >>> https://lnkd.in/d8aqJq-u

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

VINCI Digital | Industrial AI Strategic Advisory 🚀

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🛢️𝐄𝐪𝐮𝐢𝐧𝐨𝐫 𝐒𝐚𝐲𝐬 𝐀𝐈 𝐒𝐚𝐯𝐞𝐝 𝐈𝐭 $𝟏𝟑𝟎𝐌 𝐢𝐧 𝟐𝟎𝟐𝟓 🤖: 𝘛𝘩𝘦 𝘕𝘰𝘳𝘸𝘦𝘨𝘪𝘢𝘯 𝘮𝘢𝘫𝘰𝘳 𝘴𝘢𝘪𝘥 𝘪𝘵 𝘪𝘴 𝘶𝘴𝘪𝘯𝘨 𝘈𝘐 𝘧𝘰𝘳 𝘱𝘳𝘦𝘥𝘪𝘤𝘵𝘪𝘷𝘦 𝘮𝘢𝘪𝘯𝘵𝘦𝘯𝘢𝘯𝘤𝘦 𝘵𝘩𝘳𝘰𝘶𝘨𝘩𝘰𝘶𝘵 𝘪𝘵𝘴 𝘧𝘢𝘤𝘪𝘭𝘪𝘵𝘪𝘦𝘴 𝘢𝘯𝘥 𝘧𝘰𝘳 𝘪𝘯𝘵𝘦𝘳𝘱𝘳𝘦𝘵𝘢𝘵𝘪𝘰𝘯 𝘰𝘧 𝘴𝘦𝘪𝘴𝘮𝘪𝘤 𝘥𝘢𝘵𝘢 𝘧𝘳𝘰𝘮 𝘵𝘩𝘦 𝘕𝘰𝘳𝘸𝘦𝘨𝘪𝘢𝘯 𝘤𝘰𝘯𝘵𝘪𝘯𝘦𝘯𝘵𝘢𝘭 𝘴𝘩𝘦𝘭𝘧 🚀🚀🚀

Via JPT - Journal of Petroleum Technology | January 7, 2026 | @VINCI_Digital

Source: Arne Reidar Mortensen/Equinor

✅ Norwegian major Equinor said that using artificial intelligence (𝐀𝐈) contributed to value creation and savings for the company and its partners amounting to $𝟏𝟑𝟎 𝐦𝐢𝐥𝐥𝐢𝐨𝐧 𝐢𝐧 𝟐𝟎𝟐𝟓

✅ The use of artificial intelligence only at the Johan Sverdrup field in the North Sea saved the company and its partners $12 million

✅ Equinor:

🔹uses 𝐀𝐈 on offshore platforms and land facilities to solve industrial tasks on a large scale

🔹𝐀𝐈 is crucial to achieving its ambition for the Norwegian continental shelf by 2035

<<< “𝘈𝘐 𝘪𝘴 𝘢 𝘤𝘦𝘯𝘵𝘳𝘢𝘭 𝘱𝘢𝘳𝘵 𝘰𝘧 𝘰𝘶𝘳 𝘰𝘱𝘦𝘳𝘢𝘵𝘪𝘰𝘯𝘴,” said Hege Skryseth, Equinor’s executive vice president for technology, digital, and innovation.

“𝘔𝘰𝘷𝘪𝘯𝘨 𝘧𝘰𝘳𝘸𝘢𝘳𝘥, 𝘈𝘐 𝘸𝘪𝘭𝘭 𝘣𝘦𝘤𝘰𝘮𝘦 𝘦𝘷𝘦𝘯 𝘮𝘰𝘳𝘦 𝘪𝘮𝘱𝘰𝘳𝘵𝘢𝘯𝘵 𝘧𝘰𝘳 𝘴𝘰𝘭𝘷𝘪𝘯𝘨 𝘪𝘯𝘥𝘶𝘴𝘵𝘳𝘪𝘢𝘭 𝘵𝘢𝘴𝘬𝘴 𝘴𝘢𝘧𝘦𝘭𝘺, 𝘧𝘢𝘴𝘵𝘦𝘳, 𝘮𝘰𝘳𝘦 𝘱𝘳𝘰𝘧𝘪𝘵𝘢𝘣𝘭𝘺, 𝘢𝘯𝘥 𝘢𝘵 𝘴𝘤𝘢𝘭𝘦.

𝘞𝘪𝘵𝘩 𝘈𝘐, 𝘸𝘦 𝘤𝘢𝘯 𝘢𝘯𝘢𝘭𝘺𝘻𝘦 𝘴𝘦𝘪𝘴𝘮𝘪𝘤 𝘥𝘢𝘵𝘢 10 𝘵𝘪𝘮𝘦𝘴 𝘧𝘢𝘴𝘵𝘦𝘳, 𝘱𝘭𝘢𝘯 𝘸𝘦𝘭𝘭𝘴 𝘢𝘯𝘥 𝘧𝘪𝘦𝘭𝘥 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘮𝘦𝘯𝘵 𝘪𝘯 𝘯𝘦𝘸 𝘢𝘯𝘥 𝘣𝘦𝘵𝘵𝘦𝘳 𝘸𝘢𝘺𝘴, 𝘢𝘯𝘥 𝘰𝘱𝘦𝘳𝘢𝘵𝘦 𝘰𝘶𝘳 𝘧𝘢𝘤𝘪𝘭𝘪𝘵𝘪𝘦𝘴 𝘮𝘰𝘳𝘦 𝘦𝘧𝘧𝘪𝘤𝘪𝘦𝘯𝘵𝘭𝘺.

🏭 𝘐𝘯𝘥𝘶𝘴𝘵𝘳𝘪𝘢𝘭 𝘱𝘳𝘰𝘤𝘦𝘴𝘴𝘦𝘴 𝘨𝘦𝘯𝘦𝘳𝘢𝘵𝘦 𝘷𝘢𝘴𝘵 𝘢𝘮𝘰𝘶𝘯𝘵𝘴 𝘰𝘧 𝘥𝘢𝘵𝘢, 𝘢𝘯𝘥 𝘸𝘦 𝘤𝘢𝘯 𝘶𝘴𝘦 𝘈𝘐 𝘵𝘰 𝘱𝘳𝘰𝘥𝘶𝘤𝘦 𝘬𝘯𝘰𝘸𝘭𝘦𝘥𝘨𝘦 𝘧𝘳𝘰𝘮 𝘵𝘩𝘪𝘴 𝘥𝘢𝘵𝘢.

𝘛𝘩𝘪𝘴 𝘩𝘢𝘴 𝘢𝘭𝘳𝘦𝘢𝘥𝘺 𝘣𝘦𝘦𝘯 𝘵𝘳𝘢𝘯𝘴𝘧𝘰𝘳𝘮𝘢𝘵𝘪𝘷𝘦 𝘢𝘯𝘥 𝘱𝘳𝘰𝘧𝘪𝘵𝘢𝘣𝘭𝘦, 𝘦𝘷𝘦𝘯 𝘵𝘩𝘰𝘶𝘨𝘩 𝘸𝘦 𝘢𝘳𝘦 𝘴𝘵𝘪𝘭𝘭 𝘦𝘢𝘳𝘭𝘺 𝘪𝘯 𝘵𝘩𝘦 𝘈𝘐 𝘳𝘦𝘷𝘰𝘭𝘶𝘵𝘪𝘰𝘯.” >>>

✅ Equinor currently uses 𝐀𝐈 for a range of applications and says it has identified more than 𝟏𝟎𝟎 new use cases

🔹AI is being used by the company- to monitor more than 𝟕𝟎𝟎 rotating machines with 𝟐𝟒,𝟎𝟎𝟎 sensors across all of its facilities- to predict failures and maintenance needs

<<< “𝘚𝘪𝘯𝘤𝘦 2020, 𝘸𝘦 𝘩𝘢𝘷𝘦 𝘳𝘦𝘢𝘭𝘪𝘻𝘦𝘥 𝘷𝘢𝘭𝘶𝘦𝘴 𝘰𝘧 𝘰𝘷𝘦𝘳 $330 𝒎𝒊𝒍𝒍𝒊𝒐𝒏 𝘸𝘪𝘵𝘩 𝘢𝘳𝘵𝘪𝘧𝘪𝘤𝘪𝘢𝘭 𝘪𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘤𝘦 𝘪𝘯 𝘪𝘯𝘥𝘶𝘴𝘵𝘳𝘪𝘢𝘭 𝘱𝘳𝘰𝘤𝘦𝘴𝘴𝘦𝘴, 𝘰𝘧 𝘸𝘩𝘪𝘤𝘩 $130 𝒎𝒊𝒍𝒍𝒊𝒐𝒏 𝘤𝘢𝘮𝘦 𝘪𝘯 2025,” Hege Skryseth said.

“𝑾𝒆 𝒑𝒓𝒊𝒎𝒂𝒓𝒊𝒍𝒚 𝒖𝒔𝒆 𝒕𝒓𝒂𝒅𝒊𝒕𝒊𝒐𝒏𝒂𝒍 𝒎𝒂𝒄𝒉𝒊𝒏𝒆 𝒍𝒆𝒂𝒓𝒏𝒊𝒏𝒈 𝒐𝒏 𝒐𝒖𝒓 𝒐𝒑𝒆𝒓𝒂𝒕𝒊𝒐𝒏𝒂𝒍 𝒅𝒂𝒕𝒂. [𝘐 𝘵𝘰𝘭𝘥 𝘺𝘰𝘶 𝘴𝘰...😉]

Our employees can use AI tools like copilots, chatbots, and agentic AI to solve tasks and work in new ways.” >>>

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

VINCI Digital | Industrial AI Strategic Advisory 🚀

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🤖 𝐓𝐡𝐞 𝐏𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐀𝐈 𝐃𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐆𝐚𝐩 🏭: 𝘛𝘩𝘦 𝘨𝘢𝘱 𝘣𝘦𝘵𝘸𝘦𝘦𝘯 𝘵𝘩𝘦 𝘧𝘳𝘰𝘯𝘵𝘪𝘦𝘳 𝘰𝘧 𝘳𝘰𝘣𝘰𝘵𝘪𝘤𝘴 𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘢𝘯𝘥 𝘵𝘩𝘦 𝘥𝘦𝘱𝘭𝘰𝘺𝘮𝘦𝘯𝘵 𝘰𝘧 𝘳𝘰𝘣𝘰𝘵𝘴 𝘪𝘯 𝘱𝘳𝘰𝘥𝘶𝘤𝘵𝘪𝘰𝘯 𝘴𝘦𝘵𝘵𝘪𝘯𝘨𝘴, 𝘢𝘯𝘥 𝘸𝘩𝘺 𝘪𝘵 𝘮𝘢𝘵𝘵𝘦𝘳𝘴 🚀🚀🚀

Via Andreessen Horowitz / By Oliver Hsu | January 13, 2026 | @VINCI_Digital

𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 𝐚𝐧𝐝 𝐰𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 𝐥𝐞𝐚𝐝𝐞𝐫𝐬: 𝐛𝐞𝐰𝐚𝐫𝐞 𝐭𝐡𝐞 𝐏𝐡𝐲𝐬𝐢𝐜𝐚𝐥 𝐀𝐈 𝐝𝐞𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐠𝐚𝐩

✅ A recent 𝐚𝟏𝟔𝐳 report warns that despite “𝘨𝘦𝘯𝘶𝘪𝘯𝘦 𝘣𝘳𝘦𝘢𝘬𝘵𝘩𝘳𝘰𝘶𝘨𝘩𝘴 𝘪𝘯 𝘳𝘰𝘣𝘰𝘵𝘪𝘤 𝘪𝘯𝘵𝘦𝘭𝘭𝘪𝘨𝘦𝘯𝘤𝘦…𝘳𝘦𝘴𝘦𝘢𝘳𝘤𝘩 𝘱𝘳𝘰𝘨𝘳𝘦𝘴𝘴 [𝘣𝘦𝘪𝘯𝘨] 𝘳𝘦𝘢𝘭, 𝘢𝘤𝘤𝘦𝘭𝘦𝘳𝘢𝘵𝘪𝘯𝘨, 𝘢𝘯𝘥 𝘪𝘮𝘱𝘳𝘦𝘴𝘴𝘪𝘷𝘦”, “𝒕𝒉𝒆 𝒗𝒂𝒔𝒕 𝒎𝒂𝒋𝒐𝒓𝒊𝒕𝒚 𝒐𝒇 𝒓𝒐𝒃𝒐𝒕𝒔 𝒊𝒏 𝒑𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏 𝒆𝒏𝒗𝒊𝒓𝒐𝒏𝒎𝒆𝒏𝒕𝒔 𝒓𝒆𝒎𝒂𝒊𝒏 𝒏𝒂𝒓𝒓𝒐𝒘𝒍𝒚 𝒑𝒓𝒆𝒑𝒓𝒐𝒈𝒓𝒂𝒎𝒎𝒆𝒅”, the deployment gap has never been wider

✅ In other words, 𝐜𝐮𝐭𝐭𝐢𝐧𝐠‐𝐞𝐝𝐠𝐞 𝐀𝐈/𝐫𝐨𝐛𝐨𝐭𝐢𝐜𝐬 𝐚𝐫𝐞 𝐡𝐨𝐭 𝐢𝐧 𝐭𝐡𝐞 𝐥𝐚𝐛, but your shop floor is still running yesterday’s code

>>> 𝘛𝘩𝘢𝘵 𝘮𝘪𝘴𝘢𝘭𝘪𝘨𝘯𝘮𝘦𝘯𝘵 𝘪𝘴 𝘲𝘶𝘪𝘦𝘵𝘭𝘺 𝘣𝘭𝘦𝘦𝘥𝘪𝘯𝘨 𝘺𝘰𝘶𝘳 𝘰𝘱𝘦𝘳𝘢𝘵𝘪𝘰𝘯𝘴 𝘰𝘧 𝘦𝘧𝘧𝘪𝘤𝘪𝘦𝘯𝘤𝘺 𝘢𝘯𝘥 𝘷𝘢𝘭𝘶𝘦

🔹A “𝟗𝟓% 𝐚𝐜𝐜𝐮𝐫𝐚𝐭𝐞” bin-picking robot will still jam ~𝟓𝟎 𝐭𝐢𝐦𝐞𝐬 𝐩𝐞𝐫 𝐝𝐚𝐲, each stoppage requiring a human to clear and reset the system

🔹 In practice, that 𝟗𝟓% lab reliability can fall to ~𝟖𝟎% on the floor, meaning 𝐡𝐮𝐧𝐝𝐫𝐞𝐝𝐬 𝐨𝐟 𝐟𝐚𝐢𝐥𝐮𝐫𝐞𝐬 𝐝𝐚𝐢𝐥𝐲 in a busy warehouse

<<< 𝐄𝐚𝐜𝐡 𝐟𝐚𝐢𝐥𝐮𝐫𝐞 𝐢𝐬 𝐮𝐧𝐬𝐜𝐡𝐞𝐝𝐮𝐥𝐞𝐝 𝐝𝐨𝐰𝐧𝐭𝐢𝐦𝐞, 𝐦𝐚𝐧𝐮𝐚𝐥 𝐥𝐚𝐛𝐨𝐫 𝐚𝐧𝐝 𝐥𝐨𝐬𝐭 𝐭𝐡𝐫𝐨𝐮𝐠𝐡𝐩𝐮𝐭 – 𝐞𝐫𝐨𝐝𝐢𝐧𝐠 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐯𝐢𝐭𝐲 𝐚𝐧𝐝 𝐑𝐎𝐈 >>>

✅ This gap isn’t just academic, 𝐢𝐭’𝐬 𝐚 𝐭𝐡𝐫𝐞𝐚𝐭 𝐚𝐧𝐝 𝐚𝐧 𝐨𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐲!

🔹𝘊𝘰𝘮𝘱𝘦𝘵𝘪𝘵𝘰𝘳𝘴 𝘵𝘩𝘢𝘵 𝘴𝘰𝘭𝘷𝘦 𝘪𝘵 𝘸𝘪𝘭𝘭 𝘴𝘭𝘢𝘴𝘩 𝘤𝘰𝘴𝘵𝘴 𝘢𝘯𝘥 𝘶𝘯𝘭𝘰𝘤𝘬 𝘩𝘶𝘨𝘦 𝘵𝘩𝘳𝘰𝘶𝘨𝘩𝘱𝘶𝘵 𝘨𝘢𝘪𝘯𝘴, while laggards watch profit margins shrink

🔹As Oliver Hsu notes, to get “𝘰𝘳𝘥𝘦𝘳𝘴 𝘰𝘧 𝘮𝘢𝘨𝘯𝘪𝘵𝘶𝘥𝘦 𝘮𝘰𝘳𝘦 𝘳𝘰𝘣𝘰𝘵𝘴” – faster, cheaper, easier to deploy – we must bridge the gap between R&D & reality

🔹Moreover, when robots finally do work in the real world, they create data 𝐚𝐧𝐝 value simultaneously, 𝐤𝐢𝐜𝐤𝐬𝐭𝐚𝐫𝐭𝐢𝐧𝐠 𝐚 𝐟𝐥𝐲𝐰𝐡𝐞𝐞𝐥 𝐭𝐡𝐚𝐭 𝐫𝐚𝐩𝐢𝐝𝐥𝐲 𝐝𝐫𝐢𝐯𝐞𝐬 𝐝𝐨𝐰𝐧 𝐜𝐨𝐬𝐭𝐬

💡Bottom line >>> The future of manufacturing isn’t on paper, 𝐢𝐭’𝐬 𝐡𝐞𝐫𝐞!

🔹Don’t let your plant be held back by yesterday’s robots

🔹If your line is still riddled with manual resets and hidden drag, let’s talk 𝐬𝐭𝐫𝐚𝐭𝐞𝐠𝐲

🔹Connect with me to build a no-nonsense 𝐀𝐈/𝐫𝐨𝐛𝐨𝐭𝐢𝐜𝐬 𝐫𝐨𝐚𝐝𝐦𝐚𝐩 that turns the deployment gap into your competitive edge

Source: https://bit.ly/49Khae6

VINCI Digital | Industrial AI Strategic Advisory 🚀

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🤖 𝐀𝐭𝐥𝐚𝐬 𝐇𝐮𝐦𝐚𝐧𝐨𝐢𝐝 𝐑𝐨𝐛𝐨𝐭𝐬 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 ‘𝐅𝐮𝐥𝐥𝐲 𝐂𝐨𝐦𝐦𝐢𝐭𝐭𝐞𝐝’ 𝐅𝐨𝐫 𝟐𝟎𝟐𝟔 >>> 🏭 𝘍𝘢𝘤𝘵𝘰𝘳𝘺 𝘞𝘪𝘭𝘭 𝘉𝘶𝘪𝘭𝘥 30,000 𝘗𝘦𝘳 𝘠𝘦𝘢𝘳 🚀🚀🚀

Via Forbes / By John Koetsier | January 6, 2026 | @VINCI_Digital

✅ Boston Dynamics unveiled its latest 𝐀𝐭𝐥𝐚𝐬 𝐡𝐮𝐦𝐚𝐧𝐨𝐢𝐝 𝐫𝐨𝐛𝐨𝐭 this week at the 𝘊𝘰𝘯𝘴𝘶𝘮𝘦𝘳 𝘌𝘭𝘦𝘤𝘵𝘳𝘰𝘯𝘪𝘤𝘴 𝘚𝘩𝘰𝘸 (𝘊𝘌𝘚) in 𝘓𝘢𝘴 𝘝𝘦𝘨𝘢𝘴, and its entire production run for 2026 is already sold and accounted for

✅ And its majority owner Hyundai Motor Group has plans to build a 𝘳𝘰𝘣𝘰𝘵 𝘧𝘢𝘤𝘵𝘰𝘳𝘺 that can ship 𝟑𝟎,𝟎𝟎𝟎 𝐫𝐨𝐛𝐨𝐭𝐬 𝐚 𝐲𝐞𝐚𝐫😮

<<< 𝘍𝘰𝘳 𝘮𝘰𝘳𝘦 𝘵𝘩𝘢𝘯 30 𝘺𝘦𝘢𝘳𝘴, 𝘉𝘰𝘴𝘵𝘰𝘯 𝘋𝘺𝘯𝘢𝘮𝘪𝘤𝘴 𝘩𝘢𝘴 𝘣𝘦𝘦𝘯 𝘣𝘶𝘪𝘭𝘥𝘪𝘯𝘨 𝘴𝘰𝘮𝘦 𝘰𝘧 𝘵𝘩𝘦 𝘸𝘰𝘳𝘭𝘥’𝘴 𝘮𝘰𝘴𝘵 𝘢𝘥𝘷𝘢𝘯𝘤𝘦𝘥 𝘳𝘰𝘣𝘰𝘵𝘴,” Robert Playter, 𝐂𝐄𝐎 of Boston Dynamics, said in a statement.

“𝘛𝘩𝘪𝘴 𝘪𝘴 𝘵𝘩𝘦 𝘣𝘦𝘴𝘵 𝘳𝘰𝘣𝘰𝘵 𝘸𝘦 𝘩𝘢𝘷𝘦 𝘦𝘷𝘦𝘳 𝘣𝘶𝘪𝘭𝘵. 𝘈𝘵𝘭𝘢𝘴 𝘪𝘴 𝘨𝘰𝘪𝘯𝘨 𝘵𝘰 𝘳𝘦𝘷𝘰𝘭𝘶𝘵𝘪𝘰𝘯𝘪𝘻𝘦 𝘵𝘩𝘦 𝘸𝘢𝘺 𝘪𝘯𝘥𝘶𝘴𝘵𝘳𝘺 𝘸𝘰𝘳𝘬𝘴, 𝘢𝘯𝘥 𝘪𝘵 𝘮𝘢𝘳𝘬𝘴 𝘵𝘩𝘦 𝘧𝘪𝘳𝘴𝘵 𝘴𝘵𝘦𝘱 𝘵𝘰𝘸𝘢𝘳𝘥 𝘢 𝘭𝘰𝘯𝘨-𝘵𝘦𝘳𝘮 𝘨𝘰𝘢𝘭 𝘸𝘦 𝘩𝘢𝘷𝘦 𝘥𝘳𝘦𝘢𝘮𝘦𝘥 𝘢𝘣𝘰𝘶𝘵 𝘴𝘪𝘯𝘤𝘦 𝘸𝘦 𝘸𝘦𝘳𝘦 𝘤𝘩𝘪𝘭𝘥𝘳𝘦𝘯–𝘶𝘴𝘦𝘧𝘶𝘭 𝘳𝘰𝘣𝘰𝘵𝘴 𝘵𝘩𝘢𝘵 𝘤𝘢𝘯 𝘸𝘢𝘭𝘬 𝘪𝘯𝘵𝘰 𝘰𝘶𝘳 𝘩𝘰𝘮𝘦𝘴 𝘢𝘯𝘥 𝘩𝘦𝘭𝘱 𝘮𝘢𝘬𝘦 𝘰𝘶𝘳 𝘭𝘪𝘷𝘦𝘴 𝘴𝘢𝘧𝘦𝘳, 𝘮𝘰𝘳𝘦 𝘱𝘳𝘰𝘥𝘶𝘤𝘵𝘪𝘷𝘦, 𝘢𝘯𝘥 𝘮𝘰𝘳𝘦 𝘧𝘶𝘭𝘧𝘪𝘭𝘭𝘪𝘯𝘨.” >>>

🔹 1st year’s production run of 𝐀𝐭𝐥𝐚𝐬 𝐫𝐨𝐛𝐨𝐭𝐬 will go to

>>> Hyundai Motor Company, 𝘸𝘩𝘪𝘤𝘩 𝘰𝘸𝘯𝘴 80% 𝘰𝘧 Boston Dynamics

>>> and Google DeepMind, 𝘸𝘩𝘪𝘤𝘩 Boston Dynamics 𝘪𝘴 𝘱𝘢𝘳𝘵𝘯𝘦𝘳𝘪𝘯𝘨 𝘸𝘪𝘵𝘩 𝘰𝘯 𝘈𝘐 𝘧𝘰𝘳 𝘪𝘵𝘴 𝘳𝘰𝘣𝘰𝘵𝘴

Boston Dynamics “Atlas” & “Spot” @CES 2026

🔹𝐓𝐡𝐞 𝐧𝐞𝐰 𝐀𝐭𝐥𝐚𝐬 𝐢𝐬 𝐝𝐞𝐬𝐢𝐠𝐧𝐞𝐝 𝐟𝐨𝐫 𝐡𝐚𝐫𝐝 𝐥𝐚𝐛𝐨𝐫: It can carry up to 110 pounds briefly, and 66 pounds for longer periods of time👊👊👊

>>> One-handed, 𝐀𝐭𝐥𝐚𝐬 can carry 44 pounds, which is significantly higher than most humanoid robots, including the very robust EngineAI T800

>>> It offers 56 degrees of freedom, reaches to 7.5 feet overhead, and weighs in at 198 pounds

🔹Unlike the first 𝐀𝐭𝐥𝐚𝐬 𝐫𝐨𝐛𝐨𝐭𝐬 that used hydraulics for motors, this is 𝐟𝐮𝐥𝐥𝐲 𝐞𝐥𝐞𝐜𝐭𝐫𝐢𝐜⚡ 𝘭𝘪𝘬𝘦 𝘢𝘭𝘭 𝘵𝘩𝘦 𝘮𝘰𝘥𝘦𝘳𝘯 𝘩𝘶𝘮𝘢𝘯𝘰𝘪𝘥 𝘳𝘰𝘣𝘰𝘵𝘴 𝘣𝘦𝘪𝘯𝘨 𝘴𝘩𝘪𝘱𝘱𝘦𝘥 𝘵𝘰𝘥𝘢𝘺

🔹It has 4-hour battery life, and can swap its own batteries for continuous work in just 𝟑 𝐦𝐢𝐧𝐮𝐭𝐞𝐬😮

🔹Atlas also is rated at IP67 to work in wet environments and can operate from -20 to 40 degrees Celsius, or -4 to 104 degrees Fahrenheit

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

VINCI Digital | Industrial AI Strategic Advisory 🚀

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🤖 𝐀𝐈 𝐈𝐬𝐧’𝐭 𝐅𝐚𝐢𝐥𝐢𝐧𝐠 𝐅𝐨𝐮𝐫 𝐂𝐨𝐦𝐩𝐚𝐧𝐲 🏭: 𝐘𝐨𝐮𝐫 𝐎𝐩𝐞𝐫𝐚𝐭𝐢𝐧𝐠 𝐌𝐨𝐝𝐞𝐥 𝐈𝐬 - 𝘈𝘐 𝘥𝘰𝘦𝘴 𝘯𝘰𝘵 𝘳𝘦𝘱𝘢𝘪𝘳 𝘦𝘹𝘦𝘤𝘶𝘵𝘪𝘰𝘯 𝘨𝘢𝘱𝘴. 𝘐𝘵 𝘮𝘢𝘨𝘯𝘪𝘧𝘪𝘦𝘴 𝘵𝘩𝘦𝘮!

By 🔹Fabio Bottacci, founder & CEO @VINCI Digital | Industrial AI Strategic Advisory 🚀

AI does not repair execution gaps. It magnifies them. | MoMo Productions / Getty Image

✅ Executives around the world in manufacturing, energy and agribusiness sectors:

Think your AI initiatives are failing?

🔹Fortune recently pointed out

>>> “𝑨𝑰 𝒅𝒐𝒆𝒔 𝒏𝒐𝒕 𝒓𝒆𝒑𝒂𝒊𝒓 𝒆𝒙𝒆𝒄𝒖𝒕𝒊𝒐𝒏 𝒈𝒂𝒑𝒔. 𝑰𝒕 𝒎𝒂𝒈𝒏𝒊𝒇𝒊𝒆𝒔 𝒕𝒉𝒆𝒎!”

✅ In practice, this means 𝐨𝐮𝐭𝐝𝐚𝐭𝐞𝐝 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐧𝐠 𝐦𝐨𝐝𝐞𝐥𝐬 — 𝐧𝐨𝐭 𝐭𝐡𝐞 𝐀𝐈 — 𝐚𝐫𝐞 𝐭𝐨 𝐛𝐥𝐚𝐦𝐞 𝐟𝐨𝐫 𝐬𝐭𝐚𝐥𝐥𝐞𝐝 𝐝𝐢𝐠𝐢𝐭𝐚𝐥 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬

✅ Many companies still run on “𝐞𝐚𝐫𝐥𝐢𝐞𝐫 𝐞𝐫𝐚” structures with centralized approvals and slow information flows, so new technology just exposes hidden frictions and quietly undermines speed and accountability

𝘛𝘩𝘦 𝘶𝘯𝘤𝘰𝘮𝘧𝘰𝘳𝘵𝘢𝘣𝘭𝘦 𝘵𝘳𝘶𝘵𝘩

>>> 𝟒𝟐% of companies scrapped their AI initiatives in 2025, up sharply from 𝟏𝟕% the prior year

🔹The culprit wasn’t model performance or data quality alone, it was the 𝐚𝐛𝐬𝐞𝐧𝐜𝐞 𝐨𝐟 𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐚𝐥 𝐚𝐥𝐢𝐠𝐧𝐦𝐞𝐧𝐭 between how organizations are built to operate and what AI requires to deliver value!

Three breakdowns stand out

1️⃣ 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐫𝐢𝐠𝐡𝐭𝐬

🔹AI can automate faster decisions, but too many firms still require central sign-offs

🔹Insights arrive faster than leaders can process them, nullifying speed

2️⃣ 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐞𝐬

🔹New AI tools are simply bolted onto legacy workflows

🔹In response, employees bypass these tools, normalizing complexity and friction

3️⃣ 𝐂𝐮𝐥𝐭𝐮𝐫𝐞

🔹Data-driven insight challenges intuition and disrupts roles

🔹Without norms for learning and accountability, these insights often remain “𝒂𝒅𝒗𝒊𝒔𝒐𝒓𝒚 𝒓𝒂𝒕𝒉𝒆𝒓 𝒕𝒉𝒂𝒏 𝒂𝒄𝒕𝒊𝒐𝒏𝒂𝒃𝒍𝒆”

The good news?

>>> 𝐆𝐫𝐨𝐰𝐭𝐡 𝐟𝐫𝐨𝐦 𝐀𝐈 𝐢𝐬 𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐚𝐥, 𝐧𝐨𝐭 𝐦𝐞𝐫𝐞𝐥𝐲 𝐭𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥

🔹By realigning decision rights, accountability and workflows, you turn insights into action

🔹When the model is right, “𝑨𝑰 𝒘𝒊𝒍𝒍 𝒏𝒐𝒕 𝒇𝒆𝒆𝒍 𝒍𝒊𝒌𝒆 𝒂 𝒈𝒂𝒎𝒃𝒍𝒆. 𝑰𝒕 𝒘𝒊𝒍𝒍 𝒇𝒆𝒆𝒍 𝒍𝒊𝒌𝒆 𝒍𝒆𝒗𝒆𝒓𝒂𝒈𝒆”!

Bottom line

✅ Your next competitive advantage won’t come from having the most sophisticated AI: 𝐈𝐭 𝐰𝐢𝐥𝐥 𝐜𝐨𝐦𝐞 𝐟𝐫𝐨𝐦 𝐡𝐚𝐯𝐢𝐧𝐠 𝐚𝐧 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐧𝐠 𝐦𝐨𝐝𝐞𝐥 𝐭𝐡𝐚𝐭 𝐜𝐚𝐧 𝐚𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐞𝐱𝐞𝐜𝐮𝐭𝐞 𝐨𝐧 𝐰𝐡𝐚𝐭 𝐀𝐈 𝐫𝐞𝐯𝐞𝐚𝐥𝐬!

✅ Don’t let legacy processes blindside your AI efforts: 𝐈𝐟 𝐲𝐨𝐮’𝐫𝐞 𝐫𝐞𝐚𝐝𝐲 𝐭𝐨 𝐫𝐞𝐭𝐡𝐢𝐧𝐤 𝐲𝐨𝐮𝐫 𝐨𝐩𝐞𝐫𝐚𝐭𝐢𝐧𝐠 𝐦𝐨𝐝𝐞𝐥 𝐚𝐧𝐝 𝐮𝐧𝐥𝐨𝐜𝐤 𝐀𝐈’𝐬 𝐟𝐮𝐥𝐥 𝐩𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥, 𝐥𝐞𝐭’𝐬 𝐜𝐨𝐧𝐧𝐞𝐜𝐭!😉

✅ Subscribe to my newsletter for practical strategies to make 𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐀𝐈 a true competitive advantage >>> https://bit.ly/3ZpuDSa

Ciao, Fabio

Source: https://bit.ly/3Z96Y9S

VINCI Digital | Industrial AI Strategic Advisory 🚀

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Author >>> 🔹Fabio Bottacci

I’m a Senior Business Advisor / Venture Partner, an expert in Industrial IoT + AI/ML, GenAI, AI Agents/Agentic AI, and Physical AI technologies, and their actual impacts on business results.

With over 20 years of professional experience spanning the Oil & Gas, Automotive, Energy, and Utilities verticals, I help startups, SMEs, and corporations thrive in the digital transformation era by increasing productivity, developing new business models, and delivering actual results within months, not years.

As an Executive Director of Business Development and, lately, a Perplexity AI Business Fellow , I combine deep industry knowledge with cutting-edge technological expertise to drive impactful business transformations.

LinkedIn >>> https://www.linkedin.com/in/fabiobottacci/

Email >>> contato@vincidigital.net.br | Mobile >>> +55 (11) 98151-8572

Book an appointment >>> https://calendly.com/vincidigital-iiot-ai-genai/45min

VINCI Digital | Industrial AI Strategic Advisory 🚀 |

https://www.vincidigital.net.br/

#industrial #iot #iiot #ai #genai #aiagents #agenticai #physicalai #robotics #humanoids #casestudies #insights #perspectives #realitycheck

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