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Why AI adoption fails (and how to fix it)

YouTube-Video: Author: Microsoft - Bewertung: 18x - Views:106 AI's promise is real—but the challenge to realizing its value isn't technology, it's people.…

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Author: Microsoft - Bewertung: 18x - Views:106

AI's promise is real—but the challenge to realizing its value isn't technology, it's people.



AI scientist, entrepreneur, and investor Rana el Kaliouby joins host Molly Wood to explore why AI adoption can stall and how leaders can help human-AI teams thrive.



The conversation explores emotional intelligence, empathy, and communication—essential skills for successful AI adoption and sustainable human-AI collaboration. Rana makes the case that leaders must foster trust, build readiness, rethink workflows, and keep humans at the center to unlock AI's full potential and ensure sustainable adoption.



Chapters:

00:00 — Introduction to WorkLab and Rana el Kaliouby

02:06 — AI's missing piece: emotional intelligence

08:11 — AI struggles with real-world context and timing

15:24 — Two mindsets: embracing AI vs. resisting it

17:16 — Human skills that matter most in the AI era

19:21 — What separates successful AI organizations



Find this episode on:

- Apple Podcasts: https://podcasts.apple.com/us/podcast/worklab/id1582908812

- Spotify: https://open.spotify.com/show/2vApnLW5XfXoP8WDYGzFkT

- WorkLab Podcast: https://www.microsoft.com/en-us/worklab/podcast/



About the WorkLab Podcast:

Join host Molly Wood as she explores what leaders need to know to prepare their organizations for the innovations and disruptions that are transforming the way we work. Listen to her conversations with leading economists, technologists, and researchers on everything from how to use AI effectively to what it takes to thrive in a digital age.



For more insights on the future of work, visit: https://www.microsoft.com/en-us/worklab/

1. Sofort-Triage & Abwehrmaßnahmen

SOC Incident Playbook: Vulnerability Remediation & Verification
Syntax validiert (0 Fehler)
title: Detect Exploitation - Why AI adoption fails (and how to fix it)
id: 836a090c-71bb-4c79-89e4-a214bb4fda1b
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-26
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
Syntax validiert (0 Fehler)
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-26"
        description = "YARA Signature for "
    strings:
        $str = "Why AI adoption fails (and how" ascii wide
    condition:
        any of them
}
Syntax validiert (0 Fehler)
index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
("Why AI adoption fails and how to fix it")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count
Syntax validiert (0 Fehler)
message: "*Why AI adoption fails and how to fix it*"
Syntax validiert (0 Fehler)
CommonSecurityLog
| where Message has "Why AI adoption fails and how to fix it"
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

2. Cyber Threat Intelligence & Forensik

CTI Threat Relationship Graph3 Knoten / 2 Relationen
CVE / Incident Software MITRE ATT&CK CWE Weakness IoC
🎯
MITRE ATT&CK Matrix Navigator 14 Taktiken
Reconnaissance
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Resource Development
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Initial Access
Execution
Persistence
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Privilege Escalation
Defense Evasion
Credential Access
-
Discovery
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Lateral Movement
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Collection
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Command and Control
Exfiltration
-
Impact
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich Why AI adoption fails (and how to fix it.... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

🛡️ Angriffsfläche & Exposure

Netzwerk/Remote-Zugriff ohne Vorauthentifizierung möglich.

⚡ Empfohlene Sofortmaßnahmen
  • 1. Perimeter-Inspektion: Relevante Portfreigaben und exponierte Endpunkte unverzüglich scannen.
  • 2. Patch-Applikation: Hersteller-Hotfix einspielen oder betroffene Daemons in isolierte DMZ-Segmente überführen.
  • 3. Telemetrie & EDR-Alerts: Prozessaufrufe und Child-Processes auf anomale Shell-Spawns überwachen.
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