AI is revolutionizing marketing—but not the way you think.

Forget flashy automation and mass content production. In this episode, Alexandre Nevski and Zeke Camusio, founder of Data Speaks, explore how AI is transforming marketing by improving accuracy and access to real insights. Learn why traditional attribution models fall short, how AI-driven experimentation uncovers what truly drives revenue, and why better data—not bigger budgets—is the key to smarter marketing decisions. Whether you're in marketing or just fascinated by real-world AI applications, this episode will change the way you think about data and decision-making.

• Data Accuracy Over Volume: Rather than simply pushing out more ads or content, the real power of AI in marketing comes from precise measurement. By focusing on reliable, experiment-based attribution (instead of blanket tracking), companies gain clear insights into which channels actually drive revenue.
• Experimentation Trumps Guesswork: The podcast highlights the importance of testing changes in spend (what they call “designed” or “natural” experiments) to see the true impact on sales. It’s not about tracking individual users, but about measuring how each channel responds when budgets shift.
• AI + Human Insight: While AI handles massive data sets and delivers real-time insights, human judgment remains vital. AI surfaces patterns and opportunities, but people bring strategic context and relationship-building—essential for turning raw analytics into business growth.

Ignoring generative AI isn’t an option—but in high-risk environments, a simple ChatGPT subscription won’t cut it. True enterprise adoption demands security, governance, and a platform built for compliance. In this episode of Innovation Tales, we welcome back Alec Crawford, founder of Artificial Intelligence Risk, Inc., for part two of our conversation on AI security. This time, we dive deeper into how businesses can deploy AI safely, from on-premise security to multi-tiered authorization and real-time compliance monitoring.

• AI Security and Governance Are Non-Negotiable – Enterprises handling high-risk AI applications (such as in healthcare and finance) must implement on-premise or private cloud solutions, enforce role-based access, and utilize encryption and activity logging to ensure compliance with strict regulatory requirements.
• AI Regulations Are Complex and Evolving – From HIPAA in healthcare to state-specific AI laws like Colorado’s AI Act, businesses must navigate a patchwork of AI regulations. The NIST AI Risk Management Framework is emerging as a widely accepted compliance standard that simplifies regulatory alignment.
• AI’s Ethical and Global Impact Matters – Beyond compliance, organizations must address AI’s broader societal implications, including job displacement and economic divides between wealthy and developing nations. The Global AI Ethics Institute plays a key role in shaping discussions around ethical AI governance and responsible innovation.

When did you first realize AI was going to change the way we work? Long before ChatGPT and today’s AI boom, Alec Crawford was already deep in the field—surviving the second AI winter and pioneering predictive analytics. Now, he helps businesses navigate the hidden dangers of AI adoption. From building neural networks at Harvard to founding AI Risk, Inc., his journey is packed with insights for business leaders looking to embrace AI without falling into costly pitfalls.

• AI adoption comes with significant security, compliance, and governance challenges that organizations must proactively address.
• Not every AI use case is worth pursuing—businesses should evaluate whether traditional models or non-AI solutions are more effective.
• Strong AI governance, risk management, and cyber-security strategies can prevent costly mistakes and protect sensitive corporate data.