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The Dark Side Of Our Agentic Future
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The Dark Side Of Our Agentic Future

As AI agents emerge as the next frontier in technological development, a more concerning narrative is taking shape beneath the surface—one of unprecedented power consolidation in digital markets. These autonomous assistants, designed to interface with apps and execute tasks independently, may fundamentally restructure power dynamics across the digital economy, with particular implications for e-commerce businesses and marketplace sellers.
The New Gatekeepers
Financial analysts at Bernstein wealth management recently made a striking observation: "If AI agents truly become useful, the internet will go dark." This assessment points to a profound shift not just in how consumers interact with digital platforms, but in who—or what—controls access to information and commerce.
For Amazon sellers and e-commerce operators, this transformation represents a significant power transfer. Today's digital platforms already serve as gatekeepers between businesses and consumers. AI agents threaten to establish themselves as meta-gatekeepers, creating a new layer of control that determines which products and services even reach consideration.
"Currently aggregators have control over the supply," note Bernstein analysts Mark Shmulik and Nikhil Devnani, "but if demand consolidates and gets fulfilled through an AI agent, you may never need to open your rideshare app again!" This same principle applies across retail categories, potentially transforming how consumers discover and purchase products online.
Concentration of Decision Authority
The rise of agentic AI carries implications far beyond mere convenience. These systems will encode specific decision criteria and preferences, likely prioritizing metrics that benefit their creators or partners. The question of who designs these systems—and what values they embed—becomes critically important.
Major technology companies already developing these agents maintain vast data resources and market influence. Their control over agent design creates potential for self-preferencing behaviors that could further entrench dominant market positions. For independent sellers and smaller e-commerce businesses, this represents a concerning shift where visibility and access to consumers increasingly depends on alignment with AI systems controlled by already-powerful entities.
The economics of agent development further suggests consolidation. The technical infrastructure, data requirements, and expertise needed to build effective agents create significant barriers to entry. This points toward a future where a small number of agent platforms mediate an increasing share of commercial transactions, potentially extracting value at each step.
The AI Angle: Encoded Preferences and Hidden Influence
What distinguishes the agentic AI shift from previous technological disruptions is the opacity of decision processes. While human consumers make choices based on visible factors—price, reviews, brand recognition—AI agents may incorporate countless additional variables in their decisions, many invisible to both consumers and sellers.
AI systems developed by major platforms will likely incorporate implicit preferences that favor established partners, proprietary products, or higher-commission offerings. These preferences need not be explicitly programmed; they can emerge naturally from training data reflecting existing commercial relationships and platform economics.
For e-commerce businesses, this creates a troubling scenario where the rules governing market access remain unknown or constantly shifting. Optimizing for AI agent preferences could become an increasingly complex undertaking, potentially requiring specialized expertise or partnership arrangements with agent developers—further cementing power relationships.
Information Asymmetry and Market Distortion
The information architecture of an agent-mediated marketplace creates profound asymmetries. Agent operators gain unprecedented visibility into consumer preferences, price sensitivity, and purchasing patterns across platforms. Meanwhile, individual sellers receive only limited insights about why their products are recommended or overlooked.
This information disparity creates competitive advantages for agent operators who can leverage cross-platform insights to develop their own products or services. For Amazon sellers already competing with the platform's private label offerings, agent-based recommendation systems could exacerbate existing concerns about fair competition.
The consolidation extends to consumer data as well. As agents mediate more transactions, they accumulate detailed profiles of consumer behavior that span traditionally separate platforms. This data concentration creates additional competitive advantages while raising questions about privacy and consent in an increasingly mediated commercial environment.
Regulatory Implications and Future Outlook
The concentration of economic power in AI agent systems may eventually attract regulatory scrutiny. Questions of market competition, algorithmic transparency, and data advantage will likely become central to policy discussions as agent adoption increases.
For e-commerce businesses, particularly those operating on platforms like Amazon, this emerging regulatory landscape creates additional uncertainty. As Devnani and Shmulik concluded in their analysis: "Welcome to the Agentic AI era. There's nowhere to hide."
The Quick Read:
With AI-driven search evolving, optimizing for SEO now includes user behavior analysis, focusing on attention, connection, and the entire search journey beyond just clicks.
AI adoption is accelerating, with ChatGPT doubling its user base in six months and new players like DeepSeek disrupting the market, as AI tools move from novelty to daily use.
Critics of AI in writing need first hand experience with tools like GPT-4.5, which has improved but still struggles with literary quality, highlighting the gap between AI’s strengths and human creativity.
Sam Altman on GPT4.5 roll out.
Google rolls out AI-driven tools which allow users to generate outfit ideas, virtually try on beauty products, and visualize clothing on diverse body types.
Amazon is developing a step-by-step reasoning AI model to compete with OpenAI and DeepSeek, aiming for efficiency and reliability in complex queries, with a potential launch as soon as June.
Faced with competition from AI chatbots, Crunchbase has pivoted to predictive analytics, leveraging proprietary user data to forecast startup funding rounds and acquisitions with up to 95% accuracy.
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About The Writer:

Jo Lambadjieva is an entrepreneur and AI expert in the e-commerce industry. She is the founder and CEO of Amazing Wave, an agency specializing in AI-driven solutions for e-commerce businesses. With over 13 years of experience in digital marketing, agency work, and e-commerce, Joanna has established herself as a thought leader in integrating AI technologies for business growth.
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