Publicis Sapient’s Post

According to me the one crucial skill to excel in generative AI (GenAI) is prompt engineering. This involves crafting effective prompts to guide AI models in generating accurate and useful outputs, enabling users to maximize the potential of GenAI tools. #linkedin

How does hashtag#GenAI fit into SPEED? Chief Product Officer, Sheldon Monteiro is here to break it down in 30 seconds. 🚀 ⬇️ Tap the link in the comments to stream the full interview with HFS Research. Stay tuned for more videos in this series as leaders across our Product, Experience, Engineering, Data & AI (SPEED) capabilities share insights on navigating the GenAI era. 🧭

Solid guidance from McKinsey to achieve AI at Scale. I would add the need for systematic discovery and execution. Article series on AI Transformation provides perspectives on that. #AITransformation https://lnkd.in/dJsbU7zu

Taking the #DataAISummit keynote stage next week: Brian Ames, Sr Manager Production AI & Data Products at General Motors! Excited to learn how GM has embraced data + AI to drive innovation and change — register now to learn more👇

Great article by my colleagues (Aamer Baig, Douglas Merrill, Megha Sinha, Danesha Mead and Stephen Xu) lays out 7 things CIOs need to know or do when scaling AI: 1) Eliminate the noise, and focus on the signals (i.e., get past experiments by being focused on what can be learnt from POCs and go after solving a small number of big business problems) 2) It's about how the pieces fit together, not the pieces themselves (i.e., too much time is spent on choosing tools that are either obvious or undifferentiated vs integrating them) 3) Get a handle on costs before they sink you (i.e., platinum plating can be extremely expensive in this space with 10-20x variance of spend for similar outcomes, also change mgt vs development should be 3:1 but is often under-estimated) 4) Tame the proliferation of tools and tech (i.e., 'too many platforms' is a leading obstacle to progress) 5) Create teams that can build value, not just models (i.e., getting to impact is 'never just tech') 6) Go for the right data, not the perfect data (i.e., high performing GenAI solutions aren't possible without clean data, this requires real work and focus) 7) Reuse it or lose it (i.e., the name of the game in scaling is reuse - GenAI development can be sped up 30-50% through reuse of code) #NeverJustTech #GenAI #AI #data #McKinseyTechnology #QuantumBlack

Taking the #DataAISummit keynote stage: Brian Ames, Sr Manager Production AI & Data Products at General Motors! Excited to learn how GM has embraced data + AI to drive innovation and change — register now to learn more👇

Taking the #DataAISummit keynote stage: Brian Ames, Sr Manager Production AI & Data Products at General Motors! Excited to learn how GM has embraced data + AI to drive innovation and change — register now to learn more👇

I enjoy my small Easter vacation, taking the opportunity to dive into a short course on GenAI fundamentals. The key takeaway, however, leaned more towards product and growth perspectives: GenAI is accessible to everyone, which means it's not the GenAI itself that sets you apart. What truly differentiates you is how you leverage your proprietary data.

Taking the #DataAISummit keynote stage: Brian Ames, Sr Manager Production AI & Data Products at General Motors! Excited to learn how GM has embraced data + AI to drive innovation and change — register now to learn more👇