AI
Putting Generative AI into Production Without Inventing New Risks
From pilots to production: data boundaries, evaluation, human review, and automation that operators will trust on a Monday morning.
MadyTech AI Practice9 min read
AI
Article
By 2024, every leadership offsite had a generative AI slide. Fewer teams had an evaluation harness, a red-team plan, or a rollback story. Production AI is less about prompting flair and more about systems engineering.
Define the job: summarize, classify, draft, extract, or route. Constrain the data. Log prompts and outcomes. Measure precision against a labeled sample before you wire the model into customer-facing workflows. The NIST AI RMF is a useful vocabulary for those conversations.
Where generative models shine first is assisted work—not unsupervised autonomy. Pair them with the process discipline in our automation playbook and the ROI focus in Finding Real ROI in AI.
Need implementation help? See AI & Automation or contact MadyTech. For a sharper, human take on strategy theater, read Engr. Mudassir’s fancy to-do list essay.
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