Maribel Lopez of Lopez Research hosted a podcast at AWS Reinvent, discussing QuickSight with ATracy Daugherty GM, QuickSight at Amazon Web Service and Travis Muhlestein, Chief Data and Analytics Officer at GoDaddy. QuickSight, a cloud-based BI tool, enables real-time data sharing and decision-making through dashboards, pixel-perfect reports, and Q for asking data questions. In the podcast, Muhlstein shares how QuickSight has transformed GoDaddy's approach from static dashboards to real-time, interactive data exploration and analysis, enabling more agile, data-driven decision-making across the organization.

Follow the guests at:
Maribel Lopez https://www.linkedin.com/in/maribellopez/

Travis Muhlestein, Chief Data and Analytics Officer at GoDaddy https://www.linkedin.com/in/travis-muhlestein/

Tracy Daugherty GM, QuickSight at Amazon Web Services https://www.linkedin.com/in/tracy-daugherty-28a1014/

Every industry, including the quick service restaurant (QSR) market, plans to transform its business with artificial intelligence (AI). Several years ago, Wendy's embarked on its AI journey, leveraging cloud services and generative AI to enhance employee and customer experiences. The drive-thru experience presents numerous challenges for QSR restaurants due to the complexities of menu options, limited-time offers, special requests, and ambient noise.

Wendy's chose to tackle the drive-thru experience with AI because 75 to 80 percent of Wendy's customers choose the drive-thru as their preferred ordering channel. The company saw a tremendous opportunity to improve the customer experience by creating a seamless ordering experience using AI automation in the drive-thru.

In an interview with Lopez Research, Wendy's CIO Matt Spessard shared how its AI program had advanced over the past year and shared advice for other leaders looking to tackle AI within their business.

At Amazon Re:Invent, Maribel Lopez met with several industry analysts to discuss their perspectives on what happened at one of the industry's premier cloud computing and AI trade shows.

https://reinvent.awsevents.com/

Episode Summary:
In this episode, Maribel Lopez speaks with Dell’s Chief Technology Officer and Chief AI Officer John Roese about Dell’s enterprise AI technologies from their development to their future. Roese explains how the initial magical thinking around artificial intelligence has shifted into a more practical approach that aims to maximize the benefits of each implementation. He also discusses the emerging trends and ideas that he is seeing in the AI space.

Key Themes:
Maribel and John start by delving into enterprise AI and AI markets in general. John explains the types of AI markets and how enterprise AI differs from other applications. The conversation then moves into the challenges of AI and the steps that Dell is taking to address them.

Next, John and Maribel reflect on the near-universal reactive approach that companies took to AI two years ago and how parts of that approach backfired or fizzled out. While this technology could have been approached better, its widespread use has provided companies with a real world understanding of LLMs and their applications. Now, companies take a more practical approach to AI while continuing to innovate.

The key innovation that Roese highlights is agentic architecture. This technology differs from previous generative AI applications because it can operate autonomously and is highly specialized. Individual “agents” can have job descriptions that they are trained for much like a human being, and they can interact with each other as a human team would.

For detailed show notes, navigate the episode using the time stamps below:

[1:26] Maribel introduces the guest of the episode, John Roese. Roese is the CTO and Chief AI Officer at Dell Technologies.

[1:59] The AI market is not a singular market – there is a traditional market, a training market, and an enterprise market. The enterprise market is very pragmatic in its applications.

[4:10] Maribel asks about the challenges businesses see in enterprise adoption. Early discussions of new AI technology treated it like magic. Now that we have real world use cases and a better understanding of the technology, Dell is able to have grounded conversations about AI applications with real impacts.

[7:48] Roesch explains the challenges that Dell is facing with AI. One of the challenges was determining where to prioritize as a company. Another is the process by which you develop application ideas. Dell had this issue when bringing ideas that were not fully formed to their legal team.

[11:44] No one got AI perfectly right. Almost universally, companies reacted at the technical level before looking at business priorities. Roese encourages companies to move toward a more thoughtful approach to AI technology.

[13:36] Dell learned that its goal was to add in the minimum sufficient AI structure to address the maximum use cases. In Dell’s case, half of their use cases were related to converting proprietary data into generative outcomes. Creating one model to handle all of these cases is the most efficient approach.

[15:05] Maribel asks Roese about the trends Dell is seeing in AI. Roese points to the emergence of agentic architecture. The idea behind agentic architecture is that they are autonomously performing agents with very specialized purposes. They can be combined much like a team of human beings.

Follow John Roese: https://www.linkedin.com/in/johnroese/

Learn more about Dell’s AI solutions: https://www.dell.com/en-us/shop/scc/sc/artificial-intelligence

Follow Maribel Lopez on X/Twitter: https://x.com/maribellopez

Subscribe to Maribel Lopez on YouTube: https://www.youtube.com/c/MaribelLopezResearch

Follow Maribel Lopez on LinkedIn: https://linkedin.com/in/maribellopez/

Episode Summary:
In this episode, Maribel Lopez speaks with Google Cloud Product Manager Bobby Allen about the current benefits and future possibilities of artificial intelligence in the context of Google’s AI services. They explore the flexibility of Googles services that sets them apart, the environmental impacts of LLMs in comparison with their predecessor NLMs, and how companies can take a human approach to AI to make peoples lives better.

Key Themes:
Maribel and Bobby begin by discussing Google’s AI services. Allen explains the wide variety of AI services offered by Google, which fall into three main categories: building AI, building with AI, and using AI. Most organizations are currently interested in using AI, and they have seen tangible benefits from doing so.

Bobby refers to these benefits as the “four I’s”: insight, increase, improvement, and innovation. Companies that adopt AI can see increases in productivity, gain insights into large documents through AI summarization, and more. Ai also has growing applications in compliance and query creation to analyze large datasets.

Last, Maribel and Bobby discuss the future of AI. Bobby points to a human-first future with a focus on the impacts of AI applications, including sustainability and marginalization. He believes that AI should solve real problems and male peoples lives better.

Follow Bobby Allen: https://www.linkedin.com/in/ballen-clt/

Learn more about AWS: http://aws.amazon.com/

Visit Maribel Lopez’s Website: https://www.lopezresearch.com/

Follow Maribel Lopez on X/Twitter: https://x.com/maribellopez

Subscribe to Maribel Lopez on YouTube: https://www.youtube.com/c/MaribelLopezResearch

Follow Maribel Lopez on LinkedIn: https://linkedin.com/in/maribellopez/

Episode Summary:
In this episode, Maribel Lopez speaks with Qventus co-founder and CEO Mudit Garg. Mudit explains how automation can help patients receive efficient care and hospitals maximize their performance. Learn how Qventus is helping hospital systems cut down their “excess days,” why efficiency is essential to care, and Mudit’s predictions for the future of AI in healthcare.

Key Themes:
Maribel begins the episode by speaking with Mudit about how Qventus is changing the hospital system for the better. Mudit explains that AI can be extremely helpful for hospital coordination. There are many cases in healthcare where the patient and the hospital system are aligned in their goals, like booking a surgery for a patient, but administrative complexities make those goals difficult to accomplish.

Qventus bases its system on two crucial components – behavioral science and machine learning. Machine learning is a great tool for determining patterns for coordination and scheduling, but factoring human behavior is crucial to create a model that actually works. Mudit credits the success of Qventus to the combination of these factors.

Maribel and Mudit also discuss the future of artificial intelligence in hospitals. Many industries are adopting AI in a wide range of applications, but Mudit suggests that healthcare systems should focus in on perfecting technology that benefits both patients and hospitals. He also notes his interest in Ai’s potential for data siloing, which would cut down administrative work.

Follow Mudit Garg on LinkedIn: https://www.linkedin.com/in/gargmudit/

Learn more about Qventus: https://qventus.com/

Visit the 3Blue1Brown YouTube Channel: https://www.youtube.com/@3blue1brown

Visit Maribel Lopez’s Website: https://www.lopezresearch.com/

Follow Maribel Lopez on X/Twitter: https://x.com/maribellopez

Subscribe to Maribel Lopez on YouTube: https://www.youtube.com/c/MaribelLopezResearch

Follow Maribel Lopez on LinkedIn: https://linkedin.com/in/maribellopez/