In 2024, artificial intelligence (AI) transitioned from a period of awe to a focus on practical applications, as industries sought to make AI technology more accessible and functional. After two years of experimentation with AI models like ChatGPT, the shift was clear: companies were not just releasing new models, but developing products that integrate AI’s capabilities in ways that truly benefit users.
According to Arvind Narayanan, a computer science professor at Princeton University and co-author of AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell The Difference, 2023 was marked by excitement over AI’s potential, but 2024 emphasized its real-world utility. The generative AI that captivated millions—whether in tools like Google Search or photo editing software—was now embedded in everyday services, improving functionality without requiring active user engagement.
Narayanan points out that, initially, powerful AI models were being launched without clear, actionable ways for people to use them. In 2024, however, the focus shifted to crafting products that leverage these models to serve tangible needs, creating tools that offer actual value to individuals and businesses alike.
The Costs of AI’s Expansion
While AI has become an essential part of the tech landscape, the costs involved in its development and implementation are steep. From energy-intensive computing systems to the need for advanced AI chips, the infrastructure to support generative AI tools like OpenAI’s ChatGPT and Google’s Gemini requires massive investments. Some companies have even sought deals with nuclear power providers to help manage the immense energy demands.
Goldman Sachs analyst Kash Rangan highlights the significant capital poured into AI, but some skeptics question whether the technology has yet delivered on its transformative promises. AI’s development has been more gradual than revolutionary, and while it remains costly, its practical applications in fields like sales and design are becoming more evident.
AI and Employment: Augmenting or Replacing Jobs?
As AI continues to evolve, one pressing concern is its potential impact on jobs. For instance, companies like Borderless AI are already using AI chatbots to draft contracts without human lawyers. Meanwhile, workers in fields like video gaming and entertainment are wary of AI replacing their roles, as it can replicate performances without consent.
Despite these fears, experts argue that generative AI is not yet capable of creating truly original work. Walid Saad, a professor at Virginia Tech, points out that while AI can process large amounts of data, it lacks the creativity and common sense that humans possess. For example, when asked to generate an image of salmon swimming in a river, AI produced a photo of cut salmon pieces in a grocery store, demonstrating a lack of understanding about the world’s physical realities.
The Future of AI: Towards “Agentic” Systems
Looking ahead, AI is set to evolve into more sophisticated systems known as “agents.” These agents will be capable of not just performing tasks, but of reasoning and collaborating to solve complex problems. As AI systems become more integrated into various sectors, such as cryptocurrency and pharmaceuticals, they will function like teams of specialized agents working together to achieve shared goals.
Vijoy Pandey of Cisco predicts that in the coming years, AI agents will become highly skilled in specific areas, working together as an ensemble to address problems in a coordinated manner. This shift marks the transition from individual AI tools to collaborative, multifunctional systems capable of tackling ambitious challenges.
AI’s Impact on Medicine
In the medical field, AI is making significant strides in both diagnostics and drug development. In 2024, the Nobel Prize in Chemistry was awarded to research led by Google that could revolutionize the way new medicines are discovered. AI’s ability to process vast amounts of data quickly helps doctors identify potential health issues faster, although human expertise is still needed for accurate diagnoses.
AI is also playing a pivotal role in pharmaceutical research, cutting down the time it takes to move from experimental trials to data analysis. With AI tools bridging the gap between physical and data-based labs, the drug development process, which could traditionally take years, is being expedited.
Conclusion
As AI continues to mature, 2024 has been a year of turning speculative technology into practical tools that enhance productivity, assist in medical advancements, and contribute to industries worldwide. While the road to fully harnessing AI’s potential remains long, its increasing integration into daily services and professional workflows demonstrates that the technology is here to stay—offering both opportunities and challenges for the future.