Busting Myths About AI and Predictive Analytics

Did you catch our #MayMythbusters posts last month on social media? We took a cold, hard look at common myths about AI’s role in business — and we showed them no mercy. 

As with any hot topic, there are inevitably a lot of bad ideas out there about AI’s role in business. But Pecan has a fresh perspective and a sharp focus on rapidly obtaining the real benefits of AI.

Our CEO and co-founder, Zohar Bronfman, recently spoke about some of these misconceptions, challenges and opportunities in the rapid-fire Q&A below, originally recorded for the ScaleUp:AI conference in April 2022. 

Check it out and start exploring a new way of thinking about how AI can boost your business.

Transcript
What is a misconception about what it takes to successfully deploy AI?

The misconception about successfully deploying AI often comes back to the actual business use case. A model is only as good as the business needle it moves, and for you to actually move a business needle with AI, you have to have the business use case in mind when starting. You have to be able to answer questions like, What am I going to do with the outputs of the model? How am I going to measure success? Only if you have very solid answers to these questions should you be starting an AI or data science project.

 

What are some common roadblocks, mistakes, or challenges when designing, building, and launching AI systems?

From our experience, one of the most common and challenging hurdles when applying AI would actually be overlooking the data preparation stage. Counter-intuitively, data preparation takes most of the time and the effort when building out an AI application. Understanding exactly the data state and the data preparation strategy that is required for the data science project is a very important milestone to keep in mind.

 

What is one of the most game-changing ways you’ve seen an AI system drive business innovation? 

Our experience also shows a game-changing place to apply AI is through your CRM-driven business processes. So if a company has some kind of a business process which is based on BI or simple analytics, upgrading it with data science driven or AI-driven business rules is usually very beneficial and can yield tens of percents of improvement in various KPIs.

 

What do you think will be the most exciting AI breakthrough or use case in the next decade?

I think the most exciting breakthrough in AI in the next decade is going to be the democratization of data science capabilities, bringing data science applications to business owners, to business users, to business analysts. It’s going to change the way the data science evolution is done. I’m very much looking forward to seeing this evolution happen.

Want to make your own business breakthroughs with AI? Pecan is here to help you with the next steps. Let’s bust myths about AI together. We’re proud to be part of this evolution of data science — bringing the potential of AI to all business teams without requiring data science resources.

We can assess your predictive readiness with a quick, easy use-case consultation. We’ll help you find the best way to get future-ready.

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