Booking Overview

DataFramed is a weekly show that brings in data and AI leaders to explain how AI is reshaping organizations, careers, and real-world risk. For PR pros, it’s a strong placement for credible experts who can translate technical and governance topics into practical leadership insights.

Metrics

Episodes: 300

Frequency: Weekly

Rating: 4.8/5.0

Estimated listeners: 1k-10k

Gender skew: Male

Location: USA

YouTube: 195.0k subscribers

Instagram: 254.0k followers

30s Ad: 183 - 226, 60s Ad: 219 - 263

Contact Form

Contact form available - Official Form

Host

Adel Nehme - Co-host of DataFramed, focusing on how AI and data are changing the world. Engages with data & AI leaders to connect technical trends to organizational practice and leadership decision-making.

Richie Cotton - Co-host of DataFramed, interviewing data & AI leaders about how they lead through the data revolution. Guides discussions that span AI ethics, governance, and agent reliability with a practical, le...

Booking Intelligence

Booking Requirements

medium
Typical Credentials:  
Data & AI leadership with credibility in applied AI, AI research, or AI governance/ethics—e.g., university professors in AI/ethics, CEOs/consultants focused on responsible AI risk, or senior research leaders from major tech companies.
Required Achievements:  
Authorship of recognized books/papers on AI ethics, safety, agents, or companion AI, Senior leadership roles at major research orgs/tech companies or advisory work to government/institutions, Academic prominence (tenured professorships, major research contributions), Track record designing or implementing responsible AI programs or agent-safety frameworks

Recent Guest Discussions

Reid Blackman - AI Ethical Risk In Practice; Training And Governance Frameworks; Agentic Risk And Reliability; Measuring Success By Avoided Disasters

Valerie Tiberius - Moral Psychology And Ethics Of AI Companions; Friendship And Well-being; Risks Of Chatbot Sycophancy; Designing Ethical AI For Human Flourishing

Ruslan Salakhutdinov - How AI Agents Fail In Long-horizon Tasks; Guardrails And Human-in-the-loop Reliability; Agent Safety And Evaluation

Recent Topics

Artificial Intelligence, Data Governance, Machine Ethics, Ai Safety, Ai Agents, Ai Reliability, Risk Management, Responsible Ai, Ai Policy, Human In The Loop

Episodes

Here's the recent few episodes on
DataFramed
:

#360 What's Your Biggest AI Ethical Nightmare? | Reid Blackman, CEO at Virtue Consultants

May 18, 2026

Most AI ethics conversations sound the same: be fair, be transparent, be accountable. The values are right, but in practice they don't get teams out of bed in the morning. Executives nod along, employees take the compliance training, and meanwhile real risks like hallucinations, cascading failures, and autonomous agents acting at scale slip through. So what shifts when teams stop chasing an ethical ideal and start naming the specific disasters they want to avoid? Who needs to be in the room t...

#359 My Best Friend is AI with Valerie Tiberius, Professor of Philosophy at University of Minnesota

May 12, 2026

Valerie Tiberius is the Paul W. Frenzel Chair in Liberal Arts and Professor of Philosophy at the University of Minnesota. She is an expert in ethics, moral psychology, and well-being, and the author of five books including What Do You Want Out of Life? and the forthcoming Artificially Yours: Real Friendship in a World of Chatbots (Princeton University Press, May 2026). She previously served as President of the Central Division of the American Philosophical Association.In the episode, Richie a...

#358 How AI Agents Will Work While You Sleep | Ruslan Salakhutdinov, Professor at Carnegie Mellon

May 04, 2026

Almost every AI agent demo lands in roughly the same place: it works most of the time, looks remarkable, and then fails in a way no one anticipated. Self-driving cars hit this wall a decade ago, and agents are running into it now. For data and AI teams, the question is no longer whether agents can complete a task — it's whether they can complete it reliably enough to remove the human reviewer. Which categories of work tolerate a 90% success rate? Which absolutely don't? And where should the n...

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