Companies in virtually every industry are racing to become AI leaders in their sector. But AI tools are only as effective as the people who use them. As AI permeates every aspect of modern business, the ability to understand, evaluate, and leverage these tools is rapidly becoming a massive differentiator, especially for small- and medium-size businesses looking to create an edge.
“AI literacy is about creating an awareness and understanding of AI: its capabilities, what it can do for us, and our responsibilities when using it,” says Brent Summers, Head of AI Platforms & GTM Innovation at Qualcomm Technologies, Inc. “AI is definitely an amplifier of productivity.”
Multiple training tiers
In most organizations, Summers notes, employees are at various stages in their AI journey. Some might not even understand AI models’ tendency to “hallucinate” incorrect outputs, and others have worked to find reliable, repeatable ways to automate portions of their workflow with AI tools.
The good news: “AI literacy grows with usage,” Summers says.
Qualcomm Technologies employs a dual-track approach to AI education: developing proprietary training materials while partnering with industry organizations, such as the Association of National Advertisers, and platform providers on certification courses. The company also tracks product use as well as self-reported productivity gains. The global marketing team is saving an estimated 2,400 hours a month with generative AI.
Qualcomm Technologies stresses cohort-based learning, bringing together employees from different teams. “We looked at our use cases, and we saw where there were similarities in the kinds of tasks that people were doing,” Summers says. “For example, we put people who had the same writing task together. We found that they could talk about their experiences and expectations for AI. They could also swap relatable stories about wins and challenges.”
Summers offers this advice for IT and business leaders looking to grow AI literacy: As employees become more fluent with AI tools, training should focus more on how workers can bring their own knowledge and critical thinking skills to AI-powered processes. “As production becomes easier, the strategic development and planning become the important piece,” he says. “Even if you’re using AI to assist, a human has to make the judgment calls.”
AI workloads running locally
One aspect of AI literacy that is often overlooked is a simple understanding of where and how AI workloads are running. Many people assume that essentially all AI workloads run in the cloud, but Summers notes the importance of neural processing units (NPUs) in devices powered by Qualcomm Snapdragon® X2 Elite processors.
Leaders and employees who use AI-enabled laptops may not realize that features such as background blur, voice isolation, and real-time translation are running locally on their devices. For example, Summers manages a team in Mexico City and runs Spanish captions for all of his meetings while speaking English, a capability facilitated locally by his laptop powered by Snapdragon X2 Elite.
Device-level AI, Summers notes, also helps optimize battery life, enables advanced security features, and unlocks new capabilities at the application layer. For highly regulated organizations, running AI workloads locally can offer important privacy and security advantages by keeping sensitive data and models on the device rather than transmitting them to the cloud.
“Knowing where the processing is happening is part of AI literacy,” he says. “Decision-makers should be aware that some of the features they need can only run locally.”
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