Three AI Themes That Dominated SXSW and Their Implications for 2025

At SXSW, discussions surrounding artificial intelligence (AI) revealed three prominent themes that can shape its future. While many concerns exist about AI missteps, particularly around safety and ethics, the consensus among industry leaders is not entirely negative. Insights from experts at major tech companies shed light on how these themes can guide us into 2025.

1. Importance of Use Cases

AI systems inherently come with flaws, including bias and hallucination, which raise legitimate concerns about their adoption in corporate environments. Business leaders emphasized that the initial step is to carefully assess the tasks AI is assigned. Sarah Bird, Chief Product Officer for responsible AI at Microsoft, noted that it is vital to choose use cases that align with AI capabilities, saying, "You want to make sure you have the right tool for the job." Some applications, particularly in hiring, have proven problematic due to AI's tendency to reflect existing biases. Consequently, IBM ceased using AI for initial candidate filtering, opting instead to utilize AI for helping to connect candidates to roles.

2. The Role of Humans

Despite ongoing fears that AI could replace human jobs, industry leaders assert that AI will not eliminate human roles outright; instead, it will transform how work is done. Ella Irwin, who heads generative AI safety at Meta, remarked that with every technological advancement, new job roles emerge and existing jobs evolve. Drawing parallels with previous innovations such as the internet, Irwin emphasizes that AI will serve as a platform that enhances productivity rather than displacing it.

3. Building User Trust

One of the greatest challenges facing AI technology is gaining consumer trust. At SXSW, the discussion highlighted that the effectiveness of AI models hinges on how trustworthy they are perceived by users. Lavanya Poreddy, head of trust & safety at HeyGen, mentioned, "AI is only as trustworthy as people place the trust in it." Just like prior technologies faced skepticism during their inception, there is a need for transparency regarding AI systems, including their training processes and safety measures. Companies are beginning to adopt practices, such as model cards, to build this trust.

AI, trust, usecase