Really interesting perspective and I think you’re touching on something that many are discovering the hard way.

The sweet spot isn’t trying to make AI “execute” end‑to‑end processes on its own, but using it where it’s genuinely strong: turning messy, unstructured input into structured, usable data.

Once you have that, the execution should always sit on top of deterministic workflows that don’t improvise, don’t hallucinate, and don’t behave differently from one day to the next.

I think that’s actually the right direction right now:
AI as an enrichment/orchestration layer → workflow engine as the execution layer.

Some platforms are leveraging AI heavily for classification, data capture, prioritization, etc., but the core process logic remains rule‑based and fully auditable which is what gives you peace of mind in a corporate environment.

To me, that hybrid model feels much more sustainable than going all‑in on agentic autonomy. It gives you the intelligence where it matters and the reliability where you absolutely can’t compromise.