Imagine a world where crops can text their farmers when they’re feeling sick—weeks before a human eye can spot a single symptom. In this episode, we sit down with Shely Aronov, the visionary CEO and co-founder of InnerPlant, to discuss how her company is turning crops into living sensors. By tapping into a plant's natural immune system and adding a "line of code," InnerPlant enables soybeans and corn to emit optical signals that tell farmers exactly what they need, from fungal defense to nutrient boosts.

Shely shares the "sci-fi" journey of building a deep-tech startup, the reality of "building the plane while flying it" during their first commercial launch in 2025, and why the future of agriculture looks like individualized healthcare for every single plant in the field.

• The "CropVoice" Revolution: InnerPlant’s first commercial product allows crops to communicate stress, such as fungal pressure, via fluorescent signals.
• Early Detection is Everything: Plants can signal an infection weeks before symptoms appear, allowing farmers to act while the "cancer is at stage one" rather than stage four.
• The Tech Stack: InnerPlant uses hyperspectral cameras, drones, and satellites to read non-native fluorescent signals across millions of acres.
• Scaling Deep Tech: Shely explains why traditional 15-year biotech development cycles are fatal for startups and how she utilized the CropVoice launch to validate demand sooner.
• Partnership for Success: InnerPlant integrates with the John Deere platform to ensure the technology is easy for farmers to adopt within their existing machinery and workflows.

• Shely Aronov: CEO and Co-founder of InnerPlant. A serial entrepreneur with a Stanford MBA, she is leading the charge in the first real-time plant disease detection network.
• InnerPlant: Winner of the 2026 Big Innovation Award for their work in enabling plants to communicate their needs to humans.

"The reality is... we've been farming around the plant, not with them. That creates a lot of inefficiencies." — Shely Aronov

"You only know what something's worth when you ask for money." — Shely Aronov

• Visit InnerPlant: To learn more about the future of "talking" crops, visit innerplant.com.
• Subscribe to the Pod: To stay updated on the intersection of biology and AI, subscribe to our feed at bintelligence.com/podcast.
• Join the Circle: If you enjoyed this episode, please like, rate, and subscribe! Your support helps us bring more innovators like Shely into the Winners' Circle.

In this episode, host Russ Fordyce of the Business Intelligence Group brings together a powerhouse panel to tackle one of the most urgent challenges in modern customer experience:

How do we make AI and humans work together without losing context, connection, or quality?

With AI now embedded in every touchpoint—from call centers to underwriting to enterprise-scale CX—organizations are struggling with the “handoff problem”:
👉 What happens when a conversation moves from AI to a human, or from a human back to AI?
👉 How do we preserve context, reduce friction, and keep both customers and employees happy?

Our guests share real-world insights from the front lines of AI deployment across telecom, insurance, and global CX operations.

Chapters

00:00 — Welcome & Framing the Handoff Problem

Russ introduces the panel and sets the stage: AI is transforming customer experience, but the transitions between AI and humans are breaking down. The stakes are high—context, connection, and customer trust.

02:20 — Jason Valdina: What Businesses Get Wrong About AI Handoffs

Jason from Varen explains why companies still treat AI as “done” once a human takes over. He breaks down the critical role of context, how routing should evolve, and why losing bot‑collected data destroys efficiency.
“Businesses undervalue context—and it’s costing them.”

07:00 — The Hidden Power of Context in Routing & Prioritization

Jason dives deeper into how AI can route conversations based on behavior, sentiment, language, and history. Real examples show how smarter routing improves CX and reduces cost.

11:20 — New Metrics for the AI Era

Containment rate, AHT, and the surprising metric that matters most:
employee attrition.
As AI handles simple tasks, humans inherit the hardest cases—raising burnout risk.

15:40 — Emily McGinn: AI in Regulated Industries (Insurance)

Emily from Vertafore explains why regulated industries must use AI differently. Instead of making decisions, AI accelerates intake, summarization, and pattern recognition so underwriters can make better calls faster.

18:00 — Workflow First, AI Second

Emily shares a crucial lesson:
You can’t layer AI on top of broken workflows.
Teams must map processes, identify human checkpoints, and insert AI intentionally—not everywhere.

21:50 — Increasing Human Capacity Without Replacing Humans

AI isn’t eliminating underwriters—it’s multiplying their capacity. Emily explains how niche insurance markets are exploding and why human expertise is still essential.

25:30 — Advice for Small & Regulated Businesses

Start with low‑risk workflows. Add human checkpoints. Treat AI as a tool, not the operating model.

26:50 — Jamie Timm: Scaling AI Across 80,000 Employees

Jamie from TELUS Digital describes deploying 70,000+ AI solutions across global CX teams. She explains how TELUS built a secure, trusted AI backbone and what they’ve learned from real-world implementation at massive scale.

29:30 — The Future of AI + Human Collaboration

Jamie reflects on rapid changes in AI, the rise of autonomous agents, and why data quality and trust are the foundation of every successful AI deployment.

This episode is a masterclass in operationalizing AI responsibly and effectively. From preserving context in customer interactions to redesigning workflows in regulated industries to scaling AI across tens of thousands of employees, the panel delivers practical, grounded insights for leaders navigating AI transformation.

In this episode of the Winners' Circle, host Russ Fordyce sits down with Daniel Ziv, Global VP of AI and Analytics at Verint, to discuss the revolutionary impact of Generative AI on the customer experience (CX) landscape.

Verint recently took home an award from the Business Intelligence Group for GenieBot, a tool that is turning decades of "bottlenecked" call center data into actionable business intelligence in seconds. Daniel shares his 23-year journey from pioneering speech analytics to leading the charge in "agentic" AI.

We dive deep into why the specific data you feed your AI is your ultimate "behavioral moat" and how companies are seeing multi-million dollar ROI within days—not months—of deployment.

• The Death of the Data Bottleneck: How GenieBot democratizes insights, allowing users to ask natural language questions of their organizational data.

• The "Behavioral Moat": Why generic AI models are a commodity, but your unique customer interaction data is your true competitive edge.

• Eliminating Hallucinations: How Verint ensures AI trust by automatically linking every insight back to specific source quotes from customer interactions.

• Real-World Impact: Examples of organizations saving between $2M and $6.5M almost immediately by identifying website bugs and operational inefficiencies.

• The Future is Agentic: A sneak peek into the roadmap where AI won't just find problems—it will proactively take action to fix them with human oversight.

00:01 – Meet Daniel Ziv & Verint Introduction to Verint’s mission in CX automation and Daniel’s history in the speech analytics market.

03:33 – The "Behavioral Data Moat" Why the AI model matters less than the data you feed it. Using unique customer behavioral data as a competitive shield.

04:04 – Rapid ROI: From Weeks to Seconds How GenieBot crunches hundreds of interactions instantly, turning what used to be a week-long manual task into a "split second" result.

06:41 – Solving the Hallucination Problem The importance of validation and how GenieBot provides direct citations from the actual source of the interaction.

09:34 – Will AI Replace Analysts? Debunking the myth that AI eliminates jobs. Like radiologists in healthcare, AI allows analysts to focus on high-level strategic thinking rather than just pulling reports.

11:56 – Operationalizing Insights Moving from raw data to action. Automating executive PowerPoints and identifying million-dollar cost-saving opportunities in finance and utilities.

17:17 – Finding the "Invisible" Friction A real-world case study on how GenieBot discovered a specific website payment bug that was causing massive customer churn before they even officially became customers.

19:13 – The Biggest GenAI Misconception Why "wait and see" is a dangerous strategy. Adopting AI is now a survival tactic, comparable to the mobile internet revolution.

23:42 – Roadmap: Agentic Analytics What’s next for Verint? A look at "Spikebot" and the transition toward AI that can autonomously suggest and monitor operational changes.

• Learn more about GenieBot: Verint.com
• Subscribe and Like: To hear more from product leaders like Daniel, visit bintelligence.com/podcast to subscribe and stay updated on the latest in business innovation.