AI's Evolutionary Potential: Generative Meets Predictive | Pecan AI

AI’s Evolutionary Potential: Generative Meets Predictive

Zohar Bronfman, our CEO and co-founder, talks with PYMNTS about LLMs, the AI talent gap, and tying predictive models to business needs.

In a nutshell:

  • AI is revolutionary for businesses, offering generative AI and predictive analytics capabilities.
  • Organizational readiness for AI adoption varies, with the talent gap being a major challenge.
  • Pecan's Predictive GenAI platform combines generative AI with predictive machine learning for accurate predictions.
  • Industries with rich transactional data are best positioned to benefit from predictive analytics.
  • Responsible AI use is crucial, with the focus shifting toward prescribing actions in addition to predicting events.

AI is "evolutionary in terms of how businesses can operate."

It's a big claim, but it's a transformative technology. Zohar Bronfman, our CEO and co-founder, makes a convincing argument for this revolutionary capability in a recent interview with Austin Prey, a senior writer at PYMNTS.

They dove deep into the current state of AI, specifically digging into the unique business contributions of generative AI and predictive analytics.

Watch the full 25-minute interview, or read on for highlights.

Austin Prey and Zohar Bronfman in screen capture from video interview

Austin Prey and Zohar Bronfman in conversation at PYMNTS

Generative AI vs. Predictive Analytics

While many today tend to refer to "AI" as a broad and general term, Zohar distinguished between these two branches of AI. Generative AI and large language models are extremely good at interacting with humans and making knowledge accessible.

However, large language models aren't well designed for making predictions about future events using business data. That's the core strength of predictive AI.

Organizational Readiness for AI Adoption

Zohar suggests that organizations have varying levels of maturity when it comes to readying themselves to implement AI. The biggest challenge is often the talent gap: a lack of enough people with the skills to take advantage of AI's potential.

This gap exists both at the technical level and in terms of integrating AI operationally into business processes.

Read more about why data and business analysts can fill this gap and drive the future of predictive AI.

How Pecan's Predictive GenAI Platform Advances AI Adoption

Through its Predictive GenAI engine, Pecan brings together the natural language capabilities of generative AI with the predictive power of machine learning. This helps organizations turn data into actionable and accurate predictions about future events.

Which Industries Are Most Ready for AI?

The companies best positioned to take advantage of predictive analytics and Pecan's platform are those that have access to rich, proprietary transactional data about customer behavior. With this data, they can use predictive models to make granular predictions about what customers will do next.

Building on Predictive AI Success

Once companies start using predictive analytics, they tend to want more of it. Zohar describes how Pecan has enabled companies to ask questions and get predictions that were never before possible with traditional tools.

Some of Pecan's most popular use cases revolve around predicting customer behavior and metrics like purchase likelihood, churn risk, and customer lifetime value.

Using AI Responsibly

As with any groundbreaking technology, there are risks of misuse and unintended consequences with AI. Zohar explains that regulation and preventative technology are necessary to ensure AI is used responsibly.

The benefits are enormous, but we must rise to meet the challenges as well.

The Next AI Innovations

What's next for business AI? Zohar suggests that the next wave of innovation will focus on not just predicting events, but prescribing actions businesses can take in response. This could help automate and optimize key business processes to levels never before possible.

Want to dive deeper into how AI can help your business? Sign up for a personal tour, or if you want to try building predictive models yourself, try a free trial today.