About the Episode

Welcome to a special episode of the show brought to you in partnership with Arlington Economic Development, where we discuss issues related to the workforce, the role of place in the future of work, and the role of the creative sector in a larger business context. We call this Return on Creativity.

Today we’re going to talk about artificial intelligence and machine learning in the enterprise, where it is today and where it’s currently headed, as well as the role of place in building talented data and technology teams.

To help me discuss this topic, I’d like to welcome Scott Love, Founder & CEO of Lovelytics.

About Scott Love

Scott Love founded Lovelytics in 2017 after leading sales for other services partners in the data analytics space. Scott is originally from Indianapolis, IN and spent 7 years living abroad in The Netherlands. Currently, Scott Love resides in Arlington, VA.

Resources

The Agile Brand podcast website: https://www.gregkihlstrom.com/theagilebrandpodcast

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For consulting on marketing technology, customer experience, and more visit GK5A: https://www.gk5a.com The Agile Brand podcast is brought to you by TEKsystems.Learn more here: https://www.teksystems.com/versionnextnow

The Agile Brand is produced by Missing Link—a Latina-owned strategy-driven, creatively fueled production co-op. From ideation to creation, they craft human connections through intelligent, engaging and informative content. https://www.missinglink.company

Synopsis

In this episode, the importance of location in the success of a business regarding AI and data maturity is discussed. The guest, Scott Love, explains that having a centralized hub with a large number of people makes it easier to build a strong culture and facilitates opportunities with local large enterprises. This implies that being in a location with a vibrant tech ecosystem and access to a skilled workforce can be advantageous for businesses looking to develop their AI and data capabilities.

Furthermore, the episode emphasizes the significance of foundational data infrastructure for effectively utilizing AI. Companies that have invested in modern data technologies and have processes in place to clean and organize their data will be better positioned to leverage AI and machine learning. Conversely, companies that have not done this foundational work will be starting behind and will need to catch up by accelerating their efforts in data management.

Although the episode does not provide specific examples or further elaboration on how location impacts the success of a business in terms of AI and data maturity, it can be inferred that being in a location with a strong tech ecosystem, access to talent, and proximity to large enterprises can provide networking and collaboration opportunities that contribute to the success of AI and data initiatives.

Ethical considerations in AI are also discussed in the episode. The host and guest acknowledge that ethics is a topic of great importance in current discussions. The guest emphasizes that there is no right or wrong answer when it comes to ethics in AI, but it is something that organizations need to be aware of. They highlight the importance of working with businesses that prioritize ethical practices and ensuring that their own organization is aligned with ethical principles.

This discussion suggests that ethical considerations are crucial in the development and implementation of AI technologies. It implies that organizations should prioritize working with businesses that prioritize ethical practices in AI. This indicates that ethical considerations are not just a matter of compliance, but also a way to ensure responsible and socially acceptable use of AI.

The guest, Scott Love, emphasizes the importance of foundational data infrastructure for organizations that want to catch up in their AI and data maturity. He explains that many companies lack this foundational data infrastructure, which prevents them from effectively utilizing AI technologies. Foundational data infrastructure refers to a centralized location where all the company's data sources, such as CRM systems, finance systems, and EHR systems, are stored. This centralized location should be governed to ensure the accuracy and automatic updating of the data, making it available to users.

Love points out that many companies still heavily rely on outdated technologies like Excel and on-premise databases, which hinders their ability to leverage AI effectively. He suggests that organizations need to prioritize establishing a strong foundational data infrastructure to get their data house in order. This involves consolidating and organizing their data sources into a centralized location, governed by data governance practices.

Love emphasizes that having a foundational data infrastructure is the first step for organizations to effectively use AI technologies. Without it, companies will struggle to leverage the full potential of AI and may be left behind. He advises organizations to make it their top priority if they don't have it already, and for those who do, to have a clear plan on how to use machine learning models (MLMs) and AI in conjunction with their foundational data infrastructure.

Overall, the episode highlights the critical role of foundational data infrastructure in enabling organizations to catch up in their AI and data maturity. It serves as the backbone for effectively utilizing AI technologies and leveraging the benefits they offer.