Context Is All You Need: Audit-Proof AI for Finance
Gartner says more than 40% of agentic AI projects will be canceled by the end of 2027. The three causes they name are cost, unclear value, and inadequate risk controls. Not one of those is a model-quality problem. All three are trust problems.
Finance did not reject AI. Finance rejected AI it could not defend to an auditor. We treated that failure rate as the design spec.
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It is the keynote Kognitos delivered at Ai4 Las Vegas, now published in full for everyone who could not be in the room. See the rest of what Kognitos brought to Ai4 2026. The argument starts from Gartner’s projection that more than 40% of agentic AI projects will be canceled by the end of 2027, and from the three causes it names: cost, unclear value, and inadequate risk controls. None of those is a model-quality problem.
Because the failure is one of trust rather than capability. Finance did not reject AI; it rejected AI it could not defend to an auditor. The session treats that cancellation rate as the design spec and works backwards from what an auditor will accept.
Institutional memory that survives turnover. It reasons exceptions through to resolution and improves with volume rather than with more code, which is what lets autonomy compound after deploy day instead of being capped on it.
Business logic written in language a reviewer can read directly. The session shows the same AP exception logic as 1,400 lines of Python and as 13 lines an auditor reads unaided.
Yes, this is the full Ai4 Las Vegas keynote, plus the live Q&A there was no time for in Vegas.
CFOs, Controllers, VPs of Finance, Heads of Shared Services and GBS, and finance transformation and automation leads.
It is an argument about architecture, with the product as the worked example. The five-questions section is deliberately written to be used against us as well as everyone else.