In the course of my work as a consultant for Dell Technologies Customer Solution Centers, I work with many business and IT leaders who want to capitalize on the opportunities brought by big data and advances in artificial intelligence. In this blog post, I will walk through some top-of-mind considerations for organizations that are embarking on the journey to AI.
What are the top considerations for the move from predictive analytics to AI?
The answer is really in the question here. The move to AI should be just that — a move, rather than an abrupt implementation of AI alone. It’s important to understand that the move to AI is a natural progression that begins with your organization’s existing data analytics systems and skillsets. But are you ready for this move?
Many customers who come through our Dell Technologies Customer Solution Centers hear about AI as the next big thing and are eager to try and adopt it to transform their businesses. After briefings and architectural design sessions, we will often discover that they lack the underlying data analytics maturity to implement a proper AI strategy. This is where our offerings can help them build up a solid foundation so that their AI models can thrive. This foundation begins with a steady near-real-time stream of manicured, governed, and secured data that is critical for AI models in the enterprise.
What are the top challenges people struggle with in the AI journey?
Many organizations face challenges related to data analytics, skillsets and the broad vision of AI. In particular, they struggle with:
- Developing a solid data analytics foundation and cultivating AI maturity
- Attracting, retaining, and making productive the talent required to develop, tune, and deploy models
- Failing to think about the ENTIRE model lifecycle — people tend to get “tunnel-vision” around the development process but fail to consider how they will put that “house of cards” into production and then iterate release after release.
What advice do you have for people getting started with AI?
This one is easy. Take advantage of your partners. Get your teams working on the things that make your business unique, not on solving IT problems. There’s no reason to have multiple teams all researching the proper SSD make/model for the proper server platform make/model for a node meant to host training workloads. You should instead be focused around the issues outlined in the previous two questions and how they can be solved in your organization. Keep that wise caveat in mind: “Don’t sweat the small stuff.” That’s what trusted partners are for.
What are some of the ways Dell can help us get going?
A great starting point is to take advantage of the network of Dell Customer Solution Centers. We can help inform, recommend, and demonstrate a whole host of technologies and platforms that create the firm foundation required for AI to thrive.
By our very nature, we talk to a lot of customers and know what unique challenges they have and how they are solving them. This is something you can leverage to your advantage, both inside the solutions portfolio and for the technologies and configurations outside it. Since we’re here and available to all Dell Technologies customers at no charge, it would be a crime not to at least pursue some initiatives and pilot a program with the assistance and resources of a Dell Customer Solution Center.
To learn more about the resources available to organizations exploring AI solutions, visit our Dell Technologies Customer Solution Centers site.
Kris Applegate is a senior solution consultant with Dell Technologies Customer Solution Centers.