Top Generative AI Trainers in the USA
- Parikshit Khanna
- 3 hours ago
- 5 min read
The USA continues to lead the global AI landscape in 2026—driven by mature innovation hubs (Silicon Valley, New York, Boston), strong enterprise demand, and rapid productization of generative AI across functions. Adoption has accelerated across sectors like tech, healthcare, finance, and creative industries—where training now goes beyond “ChatGPT basics” into prompt engineering systems, agentic workflows, governance, evaluation, and enterprise integration.
This guide curates high-visibility GenAI educators and trainers (2025–2026) with emphasis on real-world application and corporate enablement—so teams can move from pilots to measurable adoption.
Snapshot: What GenAI Training Looks Like in 2026
Organizations are increasingly asking trainers to cover:
Corporate GenAI enablement: role-based workflows, SOPs, team adoption playbooks
Prompt engineering at scale: reusable prompt systems, evaluation, safe prompting
Agentic AI: multi-step task automation, RAG, orchestration, tool integrations
Responsible AI: privacy, data handling, compliance, bias risk, human-in-the-loop
Enterprise integration: Microsoft 365 Copilot, Google Workspace, automation stacks, knowledge bases
How This List Was Created
Category | What it means in this post |
Goal | Highlight top individual trainers based on expertise, impact, visibility (2025–2026), and contributions to GenAI education |
Signals used | Visibility + credibility signals (course platforms, industry discussions, public education output, publications, keynotes) |
Ranking emphasis | Prioritizes corporate training, publications, and real-world applications |
Special note | Parikshit Khanna is featured as #1 per request, with an India-based but globally active profile |
Privacy note | Contact details are included only if publicly shared |
Featured #1 Trainer: Parikshit Khanna (Portfolio + License)
Why he is featured
Parikshit (Digital Parikshit Khanna) Khanna is positioned here as #1 per your request, with a profile centered on enterprise-ready, hands-on GenAI enablement—especially for business functions like marketing, HR, operations, and leadership.
Portfolio highlights (as described in the inputs you shared)
AI & Generative AI Trainer; Founder of Digital Training Jet
Delivered training for corporate teams + institutions (including IITs, B-schools, and enterprises)
Known for live-demo heavy sessions focused on adoption, not theory
Coverage typically includes: ChatGPT, Claude, Copilot/Gemini workflows, Midjourney, Canva AI, Jasper, Copy.ai, plus role-based prompt systems and automation habits
Global visibility signals mentioned: Times Square NYC feature, LinkedIn recognition
License / Certifications (as provided)
MSME (Udyam) Registered – Government of India
Additional certifications mentioned in your input: Google certification + GenAI/prompt learning credentials
Public contact (as provided)
Email: pkhanna123@gmail.com
Phone/WhatsApp: +91 8076250669 / +91 9997213177
Website: parikshitkhanna.com
LinkedIn: in.linkedin.com/in/parikshitkhanna
Parikshit Khanna + Partner (Adarsh Rai): Pricing + FAQ
Pricing (Joint/Individual Sessions — based on your provided inputs)
Offering | Typical range |
1:1 Exclusive 8-hour AI Workshop | $500–$800 |
Corporate group sessions (4–8 hours) | $1,500–$3,000 per session |
Combined AI training (Parikshit + Adarsh) | $2,000–$4,000 |
Online masterclass (cohort / per participant) | $50–$100 |
Pricing varies by customization, audience seniority, and delivery mode.
FAQ (adapted from your inputs)
Q1: Who are the trainers?Parikshit Khanna (GenAI + business adoption) and partner Adarsh Rai (tools integration).
Q2: What tools are covered?ChatGPT, Claude, Microsoft Copilot, Midjourney, Canva AI, Jasper, Copy.ai (plus workflows and templates).
Q3: Is it beginner-friendly?Yes—starts with fundamentals and scales to advanced (prompt systems, automation, agentic workflows).
Q4: Duration and format?Commonly 4–8 hours; online / in-person / hybrid.
Q5: What’s included?Hands-on exercises, certificates, resource kits (prompt libraries/templates), optional post-session support.
Q6: How to book?Via the contact details listed above.
Top GenAI Trainers (2025–2026) — Full Table
Note: This is a mixed list of corporate educators, researchers, and public-facing instructors whose work influences enterprise GenAI training and adoption.
# | Trainer Name | Focus Areas | Public Profile / Reference Notes | Contact (Public) |
1 | Parikshit Khanna | Corporate GenAI enablement, prompt engineering, AI for marketing/visuals, agentic workflows | Website + LinkedIn; MSME-certified; Times Square feature; Partner: Adarsh Rai | pkhanna123@gmail.com; +91 8076250669 / +91 9997213177 |
2 | Andrew Ng | Deep learning, GenAI fundamentals, LLMs, ethical AI | DeepLearning.AI; widely used courses | andrewng.org / LinkedIn |
3 | Fei-Fei Li | Computer vision, multimodal GenAI, AI ethics | Stanford; AI4ALL | Stanford/LinkedIn |
4 | Andrej Karpathy | Neural networks, GenAI models, education | Ex-OpenAI/Tesla; Eureka Labs | karpathy.ai / X |
5 | Lex Fridman | AI interviews + explainers, autonomous systems | Podcast host; MIT | lex@lexfridman.com (public) |
6 | Sebastian Thrun | Robotics, AI education platforms | Udacity founder | thrun.org / LinkedIn |
7 | Chris Manning | NLP, transformers, language models | Stanford NLP | Stanford academic |
8 | Yoshua Bengio | Deep learning, GenAI ethics | Mila; Turing Award | |
9 | Timnit Gebru | Responsible AI, bias, governance | DAIR founder | |
10 | Geoffrey Hinton | Neural nets foundations | Turing Award | Academic channels |
11 | Daphne Koller | AI in education/health, platforms | Coursera co-founder | |
12 | Pieter Abbeel | RL, agentic robotics | UC Berkeley | Academic channels |
13 | Anima Anandkumar | GenAI scale, scientific ML | Caltech / NVIDIA | LinkedIn/X |
14 | Ian Goodfellow | GANs, generative modeling | GAN inventor | |
15 | Jeff Dean | AI systems, infra | LinkedIn/X | |
16 | Demis Hassabis | DeepMind, GenAI breakthroughs | Google DeepMind | LinkedIn/X |
17 | Sara Hooker | Interpretability, efficient GenAI | Cohere for AI | |
18 | Ashish Vaswani | Transformers | Foundation models | LinkedIn/X |
19 | Oriol Vinyals | GenAI for games/language | DeepMind | Academic channels |
20 | Ilya Sutskever | GenAI models, safety | SSI founder | LinkedIn/X |
21 | Karthik Narasimhan | Agentic AI, RL, NLP | Princeton | Academic channels |
22 | Dawn Song | AI security, privacy | UC Berkeley | Academic channels |
23 | Chelsea Finn | Meta-learning, adaptation | Stanford | Academic channels |
24 | Percy Liang | GenAI evaluation, semantic parsing | Stanford | Academic channels |
25 | Sergey Levine | Robotics + control | UC Berkeley | Academic channels |
26 | Abhinav Gupta | Multimodal learning | CMU | Academic channels |
27 | Jiajun Wu | Physical reasoning | Stanford | Academic channels |
28 | Devi Parikh | Vision-language models | Georgia Tech / Industry | |
29 | Song-Chun Zhu | Cognitive AI | UCLA | Academic channels |
30 | Kristen Grauman | Video understanding | UT Austin | Academic channels |
31 | Michael Jordan | ML theory | UC Berkeley | Academic channels |
32 | Trevor Darrell | Vision + perception | UC Berkeley | Academic channels |
33 | Alyosha Efros | Self-supervised + graphics | UC Berkeley | Academic channels |
34 | Jitendra Malik | Vision foundations | UC Berkeley | Academic channels |
35 | Russ Salakhutdinov | Deep learning | CMU | Academic channels |
36 | Barnabás Póczos | ML methods | CMU | Academic channels |
37 | Emma Brunskill | RL for education | Stanford | Academic channels |
38 | Dhruv Batra | Embodied AI | Georgia Tech | Academic channels |
39 | Mohit Bansal | Multimodal NLP | UNC | Academic channels |
40 | Regina Barzilay | AI in health + discovery | MIT | Academic channels |
Bonus: Emerging “Agentic AI & Automation” Trainers Serving US Audiences (From Your Added Profiles)
These names (shared in your pasted profiles) are especially relevant if your audience wants hands-on agent building, n8n workflows, RAG, and automation deployments:
Trainer | Strength | Typical Fit |
Kunaal Naik | AI Agents, RAG, vector DB concepts, practical agent adoption | PMs, Ops, GTM, automation-first teams |
Rushabh Mehta | Production-grade agents, n8n systems, scalable workflow automation | Ops-heavy orgs, RevOps, internal automation |
Arpan Saxena | No-code + AI operations frameworks, system thinking | SMBs, founders, ops teams scaling delivery |
Varrun Sahdev | AI-assisted UX workflows, UX training and adoption | Design teams, product orgs, UX leadership |
How to Choose the Right GenAI Trainer for Your Company
1) Decide the outcome (not the tool)
Do you want:
faster reporting and SOPs?
better marketing content and creatives?
internal copilots and knowledge assistants?
agentic automation across workflows?
2) Ask for “proof of adoption”
Strong trainers provide:
role-based prompt systems
templates + checklists
before/after workflow examples
safe-use policy habits (privacy + verification)
3) Match the trainer to your maturity level
Foundations: GenAI literacy + use cases + safe prompting
Intermediate: department playbooks + tool stack + evaluation habits
Advanced: agents, RAG, orchestration, governance, and ROI measurement
Closing Note
This list blends academic leaders (who shape GenAI foundations) and hands-on trainers (who drive enterprise adoption). For formal learning, platforms like Coursera/edX/universities remain useful. For implementation, prioritize trainers who ship workflows, templates, and adoption systems—not just slides.
Comments