Does using no-code tools make AI agents easier?

It lowers development difficulty but not adoption or operations difficulty. Selecting the target task, cleaning data, and designing approval lines remain regardless of the tool.

Are AI agents harder than RPA?

They take less effort to configure but more effort to run than RPA. RPA follows fixed steps with stable outputs; AI agents work with less detail defined but produce variable results, requiring ongoing post-launch checking.

Can small companies adopt AI agents?

Yes. Narrowing to a single task is actually easier for smaller firms, since there is less cross-department coordination. However, staff time for operations must still be secured, or the agent will sit idle after launch.

Large Language ModelsAI Business & IndustryAINOWSep 18, 2026Sep 19, 2026, 04:00 JST

Gartner: over 40% of agentic AI projects to be canned by 2027

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3 Key Points

What happened
Gartner predicts over 40% of agentic AI projects will be canceled by end of 2027, citing rising costs, unclear business value, and weak risk management; a McKinsey report cited by Daiwa Institute says under 10% of tested use cases reach full deployment.
Why it matters
The bottleneck is not immature technology but undiagnosed failure — companies throw budget at pilots without identifying whether they are stuck at adoption, development, or operations, so spending continues while outcomes go unmeasured.
What to watch
The outcome hinges on whether firms define evaluation criteria and a "kill switch" (e.g. "3 months," a budget cap, a missed success-rate target) before starting PoC, rather than discovering overruns only on the monthly invoice.

WHO IT HITSCorporate AI project owners, IT governance and internal audit teams, and information-system departments evaluating agent deployments are most affected. For them, the practical takeaway is to split the approval and logging design from the build, since governance requirements — not model capability — are where operations stall.

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FAQ

Does using no-code tools make AI agents easier?: It lowers development difficulty but not adoption or operations difficulty. Selecting the target task, cleaning data, and designing approval lines remain regardless of the tool.
Are AI agents harder than RPA?: They take less effort to configure but more effort to run than RPA. RPA follows fixed steps with stable outputs; AI agents work with less detail defined but produce variable results, requiring ongoing post-launch checking.
Can small companies adopt AI agents?: Yes. Narrowing to a single task is actually easier for smaller firms, since there is less cross-department coordination. However, staff time for operations must still be secured, or the agent will sit idle after launch.

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