Does your your enterprise build in-house AI automations and workflows or contract this out? What are the pros and cons of each?

We build our own automations. By building our own automations, we can quickly prototype, test ideas with real data, and keep valuable expertise in-house.

Our organization is big enough to build an own AI platform. Having an own platform makes it easier to experiment with internal data.
But I believe every organization (no matter the size) nowadays needs a training in prompt engineering and data analysis to be able to set requirements correctly and support AI solutions built internally or externally.

We encourage and train our staff to be self sufficient to develop their own automations, workflows etc. You certainly need the guardrails and taking training is the only way people can keep their license.

# In-house gives control and long-term ownership, but is slow, talent-constrained, and expensive before ROI shows up.

#Outsourcing delivers speed and senior expertise fast, but creates dependency risk if knowledge transfer is weak.

#Most enterprises fail by treating AI as a tool rollout instead of an execution discipline.

#Best-performing model is hybrid: external teams deliver first, internal teams take over and scale.

I can help if you want to. OG