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Industry leaders from e-commerce, automotive technology, and product discovery outline ways for businesses to accelerate AI adoption while safeguarding trust, safety, and intellectual property.
As artificial intelligence becomes increasingly embedded in business operations, the debate over innovation and ethics has moved to the center of strategic decision-making. From e-commerce imaging and automotive safety systems to AI-powered product discovery, organizations are racing to unlock the technology’s potential. Yet industry leaders argue that rapid advancement without accountability risks undermining customer trust, safety, and intellectual property rights.
Across sectors, ethical AI is not emerging as a barrier to innovation. Instead, it is becoming a prerequisite for sustainable growth.
Building Trust in AI-Powered Imaging
For Jeff Strauss, Head of Imaging at PhotoRoom, the ethical challenge begins with accuracy. Having witnessed nearly four decades of transformation in visual technology, from film photography to AI-generated imagery, Strauss believes AI should enhance reality rather than distort it.
Customer trust, he noted, remains fragile when AI-generated content misrepresents products.
“If you purchase something from an e-commerce site and it has told you a mistruth—the color, the size, whatever it is—you don’t ever want to go back. It’s 37% of businesses that name product inaccuracy as their number one pain point. And that’s because they don’t know how to use AI correctly, honestly,” Strauss said.
While AI can automate complex visual workflows, Strauss argues that human creativity remains essential for producing distinctive outcomes.
According to him, “AI always goes to the middle ground, and it’s going to give you gray. Really great stuff is on the outsides, where it’s black and it’s white. You need to have that. Gray is boring.”
At the same time, Strauss points to a growing governance challenge around intellectual property. Existing AI tools can easily remove identifying information from creative works, making attribution and copyright enforcement increasingly difficult.
“If you give me an image with metadata embedded in it and watermarks on it, I take a screen grab, throw it into AI, and say ‘remove all the letters.’ I have now cleaned that image to where no one knows where it came from. I hope we can find a way to have guidelines, to have governance, that we can make sure that people do the right thing and get paid appropriately for what they’ve created.”
Safety Requires More Than Smart Algorithms
The conversation around ethics becomes even more critical in the automotive sector, where AI-powered decisions can directly affect human safety.
Hareesha KoratikereRameshappa, Electronics Design Engineer at Phantom AI, works on Phantom Vision software, which uses deep learning and computer vision to support Autonomous Emergency Braking (AEB) and Lane Departure Warning (LDW) systems. For him, responsible AI development begins with careful human oversight.
“Whenever I have any AI tool outcome, I will have a more thorough review rather than just using it as-is from the AI. That means individually, I’m applying my own approach to make sure AI is being ethically used,” KoratikereRameshappa said.
Beyond individual responsibility, he advocates for organizational leadership to establish clear standards governing AI use and development.
“Company leaders should set some standard top-to-bottom process and guidelines for how AI will be used within the organization—not only to make innovation, but also by keeping ethics aligned with using AI in the company.”
However, KoratikereRameshappa believes internal policies alone are insufficient. Industry-wide oversight remains necessary to prevent shortcuts that could compromise ethical standards.
“If somebody wants to seek success in the shorter term, there will be shortcuts to achieve that, and they may not follow the ethical rule. There should be broader governing agencies or bodies to make sure that each organization or each product will follow ethical development and deployment before it reaches the people,” he adds.
Why Systemic Solutions Matter
For Rachi Wehbi, CEO of Sell The Trend, the scale of AI’s impact makes ethics a systemic challenge rather than an individual one. His company began using AI in 2019 as a product discovery platform and has since evolved into a comprehensive AI-powered business suite.
Drawing comparisons to the disruption caused by file-sharing platforms in the music industry, Wehbi sees AI creating a similar transformation across multiple sectors simultaneously.
“I’ve lived through the Napster revolution personally. I’ve seen this kind of major shift where something comes into the marketplace that disrupts the entire industry and changes things dramatically. This is happening now—but not just across one industry, across multiple industries,” Wehbi said.
He argues that relying on individual users to make ethical decisions is unrealistic given the technology’s global reach.
“If you leave it to the end user, they are going to be governed by their desires, wants, needs, and on-the-ground reality. If we’re saying the user should have the ethical responsibility—you are talking about 8 billion people in the world. 8 billion people are going to make 8 billion types of decisions.”
Instead, Wehbi believes frameworks that protect creators and compensate original contributors are essential as AI systems continue to learn from existing content.
According to him, “People spend time, money, effort, and creativity to create those original pieces of work that the models are being trained on. There has to be some kind of framework that protects the original work creators.”
A Shared Responsibility Model
Although their industries differ, Strauss, KoratikereRameshappa, and Wehbi arrive at a similar conclusion. Balancing innovation and ethics in AI is not a binary choice but a design challenge that requires layered accountability.
Individuals must critically evaluate AI outputs. Organizations must embed ethical standards into development processes. Governments and regulatory bodies must establish frameworks that encourage innovation while protecting consumers, creators, and public safety.
As AI adoption accelerates, companies aiming for long-term success are treating ethics not as a compliance exercise, but as a foundational principle guiding every stage of design, deployment, and decision-making.
