This is how you solve Enterprise AI
Whether you aspire to make complex predictions, improve your efficiency or have identified an area where AI capabilities would give your organization the competitive advantage it needs to scale; AI holds the capacity to get you there. The question is how?
We started this discussion series as we talk to organizations on a daily bases that face problems in scaling their AI efforts. Through the series, we hope to meet your AI worries and questions through the topics we address, with the end goal of empowering you to confidently take the next steps in starting off or scaling your AI efforts. You can follow us through video here and on Youtube or listen to the podcast on Spotify.
Episode #1: How to jump-Start the AI-Driven Transformation in your Enterprise
Software is currently eating the world, but AI will follow. In this introductory episode, Errol & Luka discuss how companies can speed up and scale their AI efforts within the organization.
Episode #2: Strategic direction for your AI
If you don't know where you are going any path will take you there. In order to be able to know if you are successful in your AI projects or not, you need to set a strategic direction and clear targets beforehand.
Episode #3: Diversity is an accelerator
Homogeneous teams will not innovate or complement each other. The key to success is to create autonomous teams that can deliver technology at a rapid pace.
Episode #4: Operating your model(s)
The WAY you work is sometimes more important than THAT you work. If you can't scale your efforts you will have a hard time driving your success.
Episode #5: Software has eaten the world and AI is next
Nobody is arguing that technology has changed the competitive landscape. Today, AI is doing the very same thing. Are you getting the technology right so that you can scale up?
Episode #6: Data-enabled future
At the core of it, data emerges as the most important asset of the future. But how do you extract value from data now?
Episode #7: What makes some companies stand out when delivering with AI?
Research, Ethics, Sustainability, Literacy, Innovation to mention a few. How do they play a key role in standing out when delivering with AI?