ITTech Pulse Exclusive Interview with Dr. Zohar Bronfman, CEO & Co-Founder, Pecan AI
Welcome to ITTech Pulse! We chat with Dr. Zohar Bronfman, CEO and Co-Founder of Pecan AI, blends neuroscience and innovation to simplify predictive analytics and empower businesses with automated, actionable data insights.
What motivated your shift from academia and the IDF to founding Pecan AI, and how has that influenced your leadership style?
In academia, I built predictive models that emulated brain processes to forecast human behavior. The potential was clear, yet most businesses weren’t using predictions to guide everyday decisions. That gap became the idea behind Pecan. If predictive modeling can be automated, every company should have access to it. That mindset still shapes how I lead; make complex things simple and make them useful.
Read More: ITTech Pulse Exclusive Interview with Jay Lindenauer Vice President of Network Security WatchGuard
What are the biggest challenges organizations face when adopting predictive AI for business decision-making, and how does Pecan AI address them?
Most companies run into two problems: not enough data-science expertise and data that isn’t ready for AI use. Pecan automates the entire process from raw data to live models, so teams without deep technical skills can start generating accurate predictions within days. The goal is simple: make predictive AI something every business can use, not just those with data scientists on staff.
How do you view the differences between generative AI and predictive analytics in delivering tangible business value?
Generative AI can deliver predictive insights, but its defining enterprise use case hasn’t arrived yet. Predictive AI, meanwhile, has been driving real results for more than a decade, improving retention, boosting share of wallet, and optimizing supply chains. While GenAI is still searching for its breakthrough, predictive AI already shows how data-driven foresight creates measurable business impact.
What role does explainability play in successful predictive modeling for enterprises, and how does your platform ensure transparency in AI outputs?
No business can act on something it doesn’t understand. Explainability shows how and why a prediction was made, helping teams see the reasoning behind each outcome. That clarity builds trust and often reveals insights that improve strategy and execution.
How can businesses overcome the AI talent gap to successfully implement and scale machine learning across teams?
You no longer need an army of data scientists to make AI work. Platforms like Pecan automate what used to take months of coding and model tuning. Connect your data, ask a clear question, like “Which customers are likely to churn?”, and you’ll have a working predictive model in seconds. That’s how companies scale AI without adding complexity.
Can you share a real-world example where Pecan AI’s predictive insights directly improved a company’s bottom line or operational efficiency?
The Credit Pros used Pecan to build a churn-prediction model in just a few weeks, instead of the usual six months. The result was a 25 percent drop in new-customer churn. When the time from insight to action shrinks, the business impact shows up fast.
Looking forward, what skills or qualities do you believe are most critical for technology leaders to succeed in an AI-driven future?
Leaders who understand how their business really runs, not just how the technology works, will stand out. The technical side is easier than ever. The real skill lies in spotting where predictive automation can streamline operations, boost performance, and align with strategy.
Read More: ITTech Pulse Exclusive Interview with Sergio Gago CTO at Cloudera
Before we wrap up, we’d love to hear your advice for those looking to grow their careers in AI and predictive analytics. What key steps or mindsets do you recommend for breaking into and excelling in this field?
Get your hands dirty. Find real datasets, build models, and see what it takes to create AI that actually moves a business metric. At the same time, strengthen your business acumen so you can spot where predictive AI makes the biggest impact. Knowing how to build a model is valuable, but knowing where to apply it is what makes you indispensable.
Thank you, Dr. Zohar, for sharing your insights with us.
Write to us [wasim.a@demandmediaagency.com] to learn more about our exclusive editorial packages and programmes.
As CEO of Pecan AI, I lead the charge in redefining predictive analytics. With dual PhDs in philosophy and computational neuroscience and a passion for innovation, I’ve helped businesses unlock the power of their data, automating forecasts like customer behavior with ease and precision.
A contributor to Forbes Technology Council and other outlets, I blend academic depth with entrepreneurial drive, sharing insights that bridge cutting-edge AI theory with real-world impact. My mission? To empower analysts and businesses of all sizes to turn data into strategic foresight – faster, smarter, and more effectively than ever before.
Pecan AI helps all businesses turn their data into precise, actionable predictions for growth and efficiency. Our platform uses generative AI to deliver accurate forecasts in days, not months – no code or data science experience needed.
No Data Science Team Needed: Empower your existing analysts and BI teams to build and deploy AI models. Pecan’s no-code interface and automated machine learning mean you don’t need PhDs or hard-to-find data scientists on staff.
Works with Messy Data: No pristine data required. Pecan handles the cleaning and feature engineering behind the scenes, so you can feed in real-world, messy datasets and still get reliable predictions.
Rapid Deployment & Results: Go from raw data to live predictive models in record time (often within days). Our automated model-building and built-in intelligence let you iterate quickly, so you can act on insights while they’re fresh and relevant.
High ROI Impact: Focus on opportunities that drive revenue and reduce costs. Pecan’s customers have significantly boosted marketing ROI, improved customer retention, and avoided the high costs of building in-house data science teams.
Friendly, Approachable Experience: Advanced AI, but in a user-friendly package. Pecan’s intuitive platform guides you step by step, making predictive analytics approachable for any data-savvy team – no intimidation or jargon.
Ready to turn your data into growth?
Visit http://www.pecan.ai to see Pecan in action, and follow us here for insights on how predictive analytics can power your business forward.
