The rise of AI agents, capable of learning, adapting, and acting independently, signals a new era in software development, a stark departure from the platform-centric era that dominated the past. In traditional applications, devices, or online interactions – let’s call them platforms - most work happens within the platform. Agents, by definition, are autonomous programs designed to interact with their environment, go across platforms to collect data, make decisions, and make platforms perform tasks accordingly.
This paradigm shift poses a significant challenge for companies focused on a single or a small set of applications. AI agents, with their broad capabilities, will need their data access, but otherwise, the narrow focus of many purpose-driven applications could become a liability. With their extensive ecosystems and vast data reserves, tech giants like Google, Microsoft, and Meta are poised to dominate.
Their advantage lies in their ability to create AI agents that seamlessly integrate across multiple platforms. Google's AI-powered suite, for instance, offers personalized recommendations and automated scheduling across various apps, something previously confined to individual platforms. Microsoft similarly integrates AI into Office 365 and enterprise solutions, delivering productivity enhancements smaller providers can't match.
Hardware control further amplifies their edge. These companies ensure efficient operation and a superior user experience by optimizing AI agents for their devices. Smaller firms, lacking such resources, need help to compete in performance and capabilities.
Both large and small companies are anticipated to consider limiting data access in a bid to remain competitive. However, this strategy could potentially backfire. Users are likely to gravitate towards the seamless integration and broader capabilities offered by larger companies, which have a suite of agents that can traverse applications within their ecosystem to begin with.
This raises crucial questions about data ownership and control. As AI agents increasingly rely on data from multiple sources, disputes over access and ownership are inevitable. By restricting data, companies hinder innovation and risk regulatory scrutiny and user dissatisfaction.
In summary, the dawn of AI agents signifies a pivotal moment. It's no longer about the capabilities of a platform within its confines but rather its ability to interface with others. Platforms that can embrace broad data access and integration will thrive—conversely, those with a narrow focus risk being left behind. Agent era will drive home the point that in our multi-modal era, photo companies can not just be about photos, map applications be about maps, or CRM companies be just about customer information. Features offered cannot just be a set of pre-defined choices, like TV program choices in pre-streaming days.
