The 10x PM: Understanding AI Product Management

With AI being ingrained to each and every digital product there is no doubt that AI Product Management is increasingly becoming more and more popular.

Having worked in this space for a couple of years now, I wanted to summarize my sort of lay a foundation for anyone looking to understand AI product management.

1. Understanding the Technology

The first and foremost step of being an AI Product Manager (in addition to being product manager) is to fundamentally understand what AI is. Your understanding about basics of AI (data preparation, choosing an algorithm, training the model, testing the model, model deployment, ongoing improvement) should be crystal clear. Honestly, no one will ask you to build a ML model, companies have and prefer data scientists to do the work. However, you need this understanding to have intelligent conversations with the data science team on how to leverage AI in the best way possible to solve customer problems.

2. Understanding the Delivery

So your data science team built a shiny new model which is capable enough to solve your customer problems. But how you deliver it to clients? Do you deliver it via an API or build a UI? How do you make the workings of the model explainable to sales, customer service and ultimately the clients? As an AI Product Manager its your responsibility to deliver the complex AI model in the hands of the customers in an easy to use, easy to understand form.

3. Understanding the Risks

Every technology use possess some risk, with AI this risk is magnified because of the level of anonymous and autonomous descision making involved. As an AI Product Manager its your responsibility to make sure the AI Product/System you are building is being used as intended and does not possess risks to the business, user or the ecosystem. This includes learning more about AI risks in your field, working closely with Compliance/Legal stakeholders and pursuing innovative solutions to mitigate those risks.

I would like to conclude this essay by tagging to a few resources which I used to prepare for my AI PM journey. Hope they are helpful to you as well.

1. Deep Learning: https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618/ref=sr_1_16?crid=12VO5O451P1PI&dib=eyJ2IjoiMSJ9.xAwomaxIymCfFuMlQoeVEPypoo3xij43kJuPhi1zk0wsMw2N8V-pp2ZkFa1LJ9TUxzVnzUz1GqOKfoGnO-Hudi4eisFZZp3w-bgcHCI2JaKRkgTSBDh1HDwQIaBAbzFO_ptMxJPrXobklMeheR4DpEmgpTFGoc7G6KgAQGBlKDOU77aPl4_yNquk2j0n7P25yLDAe3ehaeuLQXRm34ALuU8_oILQ4b8pRtTBM6UPO4yPKHsxQs3po4VPdK0xb7HNRNEurndSbLY7cHso0FogvJ35L2pc29HmA8PExwhxEZ8.LvLWXuv-IGYVkUmdtEtKKnSzSlOh8GzUtxIHxH6dEe8&dib_tag=se&keywords=machine+learning&qid=1731884139&sprefix=machine+lea%2Caps%2C199&sr=8-16
2. AI Playbook: https://www.amazon.com/dp/0262048906?ref=ppx_yo2ov_dt_b_fed_asin_title
3. AI Governance: https://www.amazon.com/AI-Governance-Applying-Principles-Assessments/dp/1634624459/ref=sr_1_1_sspa?crid=1O0ZVJD9WZ92Z&dib=eyJ2IjoiMSJ9.VtDBPChL8Mm41WrawOPfN-iYqXkSuGYjutrPC-8wk1-p9YzAzTGzPcO5oPtxA75SQy14qBxVR-0pJl2AF87RESn42tQUDFl8VF_mBKg5F9ZLItHv0HNnEShl-kRdp8yR3lxKSlstGaEQEOUACMwKBMM_ib72tntso6Qq-bMBvG7VD36KMPFyXl0Sf4zifPac4fWjQmt6QtKTrg0CNucprdSISi__iSzhzrm5CFFrSO7E-5WxttrMcxjpgFfUj_TwNf4cuqv2bIwJfFz0ChpofrszXxjLVezcrazINduVRKU.Rqj1B5idVmSY3RO3_aC1GUaGILKrx2eZqgH3Foj1BL8&dib_tag=se&keywords=ai+governance&qid=1731884264&s=books&sprefix=ai+givernance%2Cstripbooks%2C114&sr=1-1-spons&sp_csd=d2lkZ2V0TmFtZT1zcF9hdGY&psc=1