AI Solutions Are Creating Artificial Needs
Author: Sophia Banton
Originally published on Towards AI.
AI Should Clear Your Desk, Not Clutter It with Artificial Needs
Was that task truly repetitive, or was it labeled as boring to justify automation?
A need is something people genuinely require to make their lives easier, solve a real problem, or improve their daily activities. An artificial need is something people are made to believe they require, even though it doesn’t genuinely improve their well-being or solve a real problem. By creating tools that don’t address actual issues but rather create the illusion of necessity, the AI industry has fallen into the trap of fostering artificial needs.
Make no mistake, AI can certainly address many genuine needs across workplaces — streamlining data analysis, enabling better customer service, and automating truly repetitive tasks. AI can also play a crucial role in specialized fields like medical diagnostics, fraud detection, and scientific research. However, many consumer and enterprise AI companies have fallen into the trap of creating artificial needs.
A Case in Point
Nearly every professional creates PowerPoint slides at some point in their career. This opens the door for enterprise solutions that promise to improve daily workflows. But these solutions haven’t been delivering on their promises to enhance productivity and efficiency.
Time Comparison for Getting an Image for a Presentation
- Google/Creative Commons search: ~2 minutes
- Dedicated image generator: ~5 minutes
- Fumbling with Copilot: Indefinite time + eventual workaround
This raises the question: How often do we actually need unique images? The answer for most business users is rarely. Yet, we’re paying premium prices for AI solutions that complicate simple workflows. The need for AI-generated images in presentations was never a significant pain point for most users, yet it’s being presented as a must-have feature. In other words, AI tools are being marketed for tasks that were never actual pain points.
The True Costs of Irresponsible AI Adoption
These challenges point to a deeper problem. Beyond the immediate frustrations and inefficiencies created by artificial needs, there’s a more significant long-term consequence for organizations investing in these solutions. The greatest cost of AI being marketed for invisible problems isn’t the price companies pay. Rather, it is the erosion of trust in AI tools among employees.
AI Leadership Must Prioritize Real Value
As Jimmy Carter once said, “We must adjust to changing times and still hold to unchanging principles.” In the AI era, that unchanging principle is that we should build technology that solves real-world problems. AI excels when it optimizes data analysis, enhances customer support, and advances fields like clinical diagnostics and anomaly detection — areas where it solves real problems instead of creating artificial needs. It has the potential to open new doors to opportunity when applied with genuine purpose.
For AI to fulfill its promise of expanding opportunity, AI leaders must do more than build AI — they must prioritize solving real problems and driving meaningful progress. AI leadership requires building tools that deliver meaningful value, not digital distractions. Before your next AI investment, challenge vendors to prove they’re solving a problem your team actually has — not one they’ve invented to sell a solution. Remember: A tool without purpose becomes noise.
About the Author
Sophia Banton is an AI Solution Lead specializing in Responsible AI governance, workplace AI adoption, and AI strategy in IT. With a background in bioinformatics, public health, and data science, she brings an interdisciplinary approach to AI implementation and governance. She writes about the real-world impact of AI beyond theory, bridging technical execution with business strategy. Connect with her on LinkedIn or explore more AI insights on Medium.
Conclusion
In conclusion, AI solutions are creating artificial needs, leading to frustration, inefficiencies, and wasted investments. To avoid this, AI leaders must prioritize solving real problems and driving meaningful progress. By doing so, AI can unlock its full potential and make a positive impact on our lives.
Frequently Asked Questions
Q: What are artificial needs?
A: Artificial needs are needs that people are made to believe they require, even though they don’t genuinely improve their well-being or solve a real problem.
Q: What are some examples of AI solutions creating artificial needs?
A: Examples include AI-powered email summaries, AI-generated images for presentations, and AI-driven workflows that complicate simple tasks.
Q: What are the consequences of AI being marketed for invisible problems?
A: The consequences include erosion of trust in AI tools among employees, wasted investments, and frustration with AI outcomes.
Q: How can AI leaders prioritize real value?
A: AI leaders can prioritize real value by building tools that deliver meaningful value, not digital distractions, and by solving real-world problems that genuinely improve people’s lives.
