Agentic AI is no longer a thought experiment.
IDC (in research sponsored by Amazon Web Services (AWS)) just published new data on how organisations are actually using agentic AI. A few highlights that jumped out at me 👇 🔹 Adoption vs reality - 23% expect full deployment of agentic AI in the next 12 months - 65% expect to get there by 2027 - But only 3% are scaling agentic AI across departments today Everyone believes there’s a productivity prize here.
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Agentic AI is no longer a thought experiment. It’s becoming a question of operating model.
IDC (in research sponsored by Amazon Web Services (AWS)) just published new data on how organisations are actually using agentic AI. A few highlights that jumped out at me 👇
-
Adoption vs reality
-
23% expect full deployment of agentic AI in the next 12 months
-
65% expect to get there by 2027
-
But only 3% are scaling agentic AI across departments today
Everyone believes there’s a productivity prize here. Almost no one has figured out how to scale it.
- Where agents live today
Most examples are operational and customer-facing:
- Advanced support “copilots”
- Workflow / process automation
- Autonomous data analysis and reporting
In other words: a lot of chatbot-like and task agents, embedded in business workflows.
- The real brakes
Top blockers in the study line up with what I’m seeing every day:
- Observability and trust
- Data privacy and governance
- Talent and skills to design, orchestrate and manage agents
- Confidence in cost and ROI
This is exactly where my current work on agentic coding lives: using fleets of agents in software engineering, with hard quality gates, policy-as-code, and flow observability so leaders can trust what’s being shipped.