Agentic AI and the Next Gold Rush: Synthetic Workers, Data Ownership, and the Future of the Workforce

Written by Brandon Lwowski, Nov 2024 |

As artificial intelligence continues its rapid advancement, particularly around foundation models and their multimodal capabilities, the concept of Agentic AI has surged to the forefront of technological discourse. Agentic AI refers to autonomous AI systems capable of making decisions without human intervention, effectively mimicking human agents in complex tasks. The sentiment surrounding these agents and their potential impact on the workforce is as polarized as our political landscape. A quick scroll through platforms like X, LinkedIn, and Reddit reveals a stark divergence in opinions. Will Agentic AI replace human workers, serve as an optimized co-pilot enhancing productivity, or is it simply overrated hype? The answer remains unknown, but the stakes are undeniably high. 

The Giants’ Leap into Agentic AI 

Major tech players are making significant strides in this domain, signaling a collective belief in Agentic AI’s transformative potential. OpenAI’s GPT-1o, rumored to possess advanced reasoning capabilities integrated with desktop applications, promises to revolutionize our interaction with technology (OpenAI, 2024). According to OpenAI, GPT-1o aims to seamlessly blend AI into daily workflows, enhancing productivity and unlocking new creative avenues. 

Similarly, Anthropic’s latest foundation model introduces an AI capable of controlling user environments, pushing the boundaries of autonomy (Anthropic, 2024). Their research indicates these models can understand and execute complex tasks across various applications controlling a user’s computer, potentially reshaping operational dynamics in businesses. 

Not to be outdone, Apple has unveiled “Apple Intelligence,” an AI embedded within its operating systems that controls third-party apps and elevates user experience (Apple, 2024). Apple’s integration focuses on privacy-centric AI, ensuring user data remains secure while providing personalized assistance—a critical balance in today’s data-conscious society. 

These developments underscore a significant investment of resources and belief in Agentic AI’s future. Companies are not merely betting on AI’s potential; they are actively shaping it, positioning themselves at the vanguard of what many consider the next technological revolution. 

The Race for Data Ownership 

Behind the advancements lies a critical and often contentious issue: data ownership. Enterprises are proactively hiring teams to shadow human workers, collecting vast datasets to train agent models that can make human-like decisions. By capturing click data and observing human-software interactions, companies aim to personalize and optimize user experiences at an unprecedented scale. The scope of research is extensive, ranging from agents capable of conducting intricate research tasks to orchestrating multiple agents solving complex problems (IBM, 2023). 

However, a pivotal question looms: Who will own the data layer that feeds these action-oriented foundation models? Historical parallels in other industries highlight the transformative power of data accessibility and ownership. When the Multiple Listing Service (MLS) in real estate digitized and shared its data, it revolutionized home buying and unlocked technologies like Automated Valuation Models (AVMs). The digitization of airline data transformed the travel industry through platforms like Expedia and Booking.com. Similarly, making stock market data live and accessible democratized trading, giving rise to platforms like E*TRADE and Robinhood. 

Bernard Marr, in his Forbes article, emphasizes that Agentic AI could fundamentally alter business and technology landscapes (Marr, 2024). He argues that democratizing data access will be pivotal in determining which companies lead in the AI era. Control over critical data has historically redefined industries and crowned new market leaders—a pattern likely to repeat with Agentic AI. 

Ethical Considerations and Workforce Implications 

The pursuit of Agentic AI raises profound ethical considerations, particularly regarding data collection and workforce displacement. The data required to train Large Action Models—capable of mimicking human interaction with software—is immense and often personal. Questions about privacy, consent, and the extent of data harvesting are more pressing than ever. How will this data be collected, and is it ethical to do so? 

Moreover, the potential for synthetic workers—AI agents replacing human roles—poses significant societal challenges. While some view Agentic AI as a tool for enhancing human capabilities and driving productivity, others fear widespread job displacement. IBM’s research suggests Agentic AI could lead to more efficient operations and unlock new innovation avenues, but they also stress the importance of responsible development, emphasizing transparency and ethical considerations (IBM, 2023). 

Will the rise of Agentic AI create a future where synthetic workers become the norm, or will it open new industries and opportunities for human workers? The dichotomy of opinions highlights the need for a nuanced approach, balancing technological advancement with ethical responsibility. 

Who Will Strike Gold? 

While uncertainties abound, dismissing the potential of Agentic AI would be naive. The critical question is not if Agentic AI will become a cornerstone of future technology but who will unlock its full potential and dominate the data layer powering it. The entity that achieves this will likely emerge as a major force in the AI industry, reshaping economic landscapes and setting new standards for technological capability. 

As we stand on the cusp of this new frontier, it’s imperative for stakeholders—business leaders, policymakers, and the public—to engage in open dialogue about the future we’re engineering. The race for data ownership in Agentic AI is not just about technological supremacy; it’s about shaping the very fabric of our society, our economy, and the ethical frameworks that underpin them. 

In the end, whoever controls the data controls the future. The next big AI company won’t just be the one with the most advanced algorithms but the one that successfully navigates the complex interplay of technology, data ownership, ethical considerations, and societal impact. 

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