The hardest resistance to spot is silent resistance.
Nodding in meetings. Alignment on paper. Then… nothing changes.
People rarely resist change openly. They protect what already feels safe.
Have you seen this?
For 2 years, AI buying was driven by innovation teams.
Now it sits with CIOs and CDOs.
The question has changed.
Not “Which model is smartest?”
But “Which one fails safely in production?”
Anyone else seeing this shift?
Unpopular opinion: GCCs didn’t evolve. They were forced to.
Cost centres became owners over the time. Tech & AI accelerated it.
Now the real gap isn’t talent. It’s leadership depth.
Are we building operators or enterprise thinkers?
Most enterprise AI strategies optimized for intelligence access.
The next phase is different.
The constraint is no longer the model. It’s the organization’s ability to absorb change fast enough.
Anyone else seeing this?
By the end of last year, over 50% of GenAI projects were abandoned after the proof-of-concept stage. The main reasons?
➡️ Poor data quality
➡️ Insufficient risk controls
➡️ Rising costs
➡️ Unclear business value
Gartner analyzed hundreds of GenAI implementations and identified the top culprits behind project abandonment. Find out more: https://t.co/apoGbaqV5r
#GenAI #ArtificialIntelligence #ProjectManagement
AI adoption is no longer a technology challenge. It’s now an operating model challenge.
The winners won’t be the companies running the most AI pilots. They’ll be the ones redesigning workflows, decisions, and execution around AI orchestration.
Which layer runs the enterprise?
Most people remember “95% of AI pilots fail.”
But now:
1 in 3 Fortune 500 companies has already deployed AI in production.
Coding, support, and search moved first because outcomes are measurable.
This is moving faster than most leaders realise.
How prepared is your industry?
Most high performers don’t fail from speed.
They fail because they never question it.
Speed feels like progress.
But it often hides lack of clarity.
The real edge? Pause. Then move with intent.
Are you moving fast… or avoiding the hard thinking?
40% of hiring in some GCCs is just replacement.
That’s the math of Gen Z attrition.
Recruiting costs are visible.
The real loss is institutional knowledge walking out the door.
If tenure keeps falling, knowledge systems become critical.
How are you solving this?
#GCC#GenZ
🫵🏻 Unpopular opinion: Adoption is not AI impact.
But without adoption, impact is impossible.
Most enterprises buy AI tools and expect transformation.
Reality: nobody builds the habit.
No habit → no impact.
Seeing this pattern too?
#AI#EnterpriseAI#AIAdoption
🔥Hot take: AI lock-in will be the next enterprise risk.
One model. One stack. One vendor.
Feels fast today.
Weak negotiating power tomorrow.
AI strategy is optionality.
Portable data. Switchable models.
Are we adopting AI… or depending on it?
#AI#EnterpriseAI
🚨 One Disney employee spammed Claude 460,000 times in 9 days. That’s ~51,000 calls a day.
Disney launched an internal AI leaderboard ranking employees by prompts and tokens.
Make usage visible → behavior follows.
Genius productivity hack…
or gamified nonsense?
Thoughts?
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