Beyond Algorithms: Why Human-Centered Design is the Missing Link in AI Success

Coming out of CES 2025, one message rang true: Make AI work for Humans. 

Several members of the Tonic3 team are still digesting what they heard at the largest consumer electronics show in Las Vegas. Yet, as we are a source of insight and innovation for many clients, we’re conveying some of the big take-aways here as quickly as we can. Anyone leaving CES 2025 will be singing the same song— the difference between good and great solutions lies not in the algorithms, but in how well they serve human needs.

The conversations from several influential panel discussions have crystallized a powerful truth about AI's future. From "Empowering Independence: Accessibility and AI Talk" to "The Future of Consumer Engagement," industry leaders are unanimously pointing to one critical factor: human experience is the key differentiator in AI success.

WHY READ THIS ARTICLE:

• You're a Change Champion leading the charge on AI within your organization and need help navigating the cultural and organizational shifts that come with it.
• You're a growth-minded leaders who still need to identify how AI can be leveraged to unlock new market opportunities while maintaining a human-centered approach.

AI for All: The Power of Inclusive Design

It’s no surprise AI was at the center of every presentation, and just about every booth, too. The "Empowering Independence" panel showcased some of the most compelling examples of human-centered AI design. Nico Kelly's introduction of Sign Speak, an AI for automated sign language recognition, and Be My Eyes' innovative app connecting blind users with sighted volunteers, demonstrate how thoughtful AI implementation can transform lives. As Sandy Lacy from the Howe Innovation Center noted, these solutions succeed because they maintain a "strong link with the community's needs." 

Interestingly, accessibility was a large theme across more than one industry, which is further proof there is an essential, dynamic role for UX leaders to play in all AI-related development. The recurring message isn’t just about creating more inclusive experiences, it’s about ensuring we don’t lose connections with humans. 

Healthcare: Where AI Meets Empathy

The healthcare sector provides one of the most compelling arguments for human-centered AI design. At the "AI in Healthcare" panel, Anjal Shah of Hippocratic AI highlighted the massive scale of transformation, noting "$43 billion invested in health AI startups over the last two years." But it's not just about investment—it's about impact. As Rashmi Joshi from Asha AI demonstrated with their voice-enabled conversational AI caregiver, success in healthcare AI comes from combining technical excellence with human empathy.

This theme was further reinforced during the "AI and Brands" discussion, where speakers emphasized how "injecting humanity and assigning mood to AI can lead to more authentic insights." This is particularly crucial in healthcare, where emotional nuance and real-world context can make the difference between compliance and abandonment of treatment plans. As one panelist noted, "AI should augment human work, not replace it"—a principle that's especially vital in healthcare settings.

Trust and Protection: The Regulatory Imperative

During the FTC Commissioner panel, Christine Wilson emphasized the delicate balance between innovation and consumer protection, highlighting the challenges of "AI-assisted fraud affecting vulnerable populations." This underscores why user experience design must incorporate trust and security from the ground up.

Integrating new technologies into existing systems while navigating a complex regulatory landscape presents significant challenges. Concerns are mounting that regulations are not keeping pace with the rapid evolution of these technologies. While there's no single solution, the consensus among many in the industry is that a risk-based, use-case-focused regulatory approach should be prioritized.

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Fragmentation: Breaking Down Data Silos is Still a Priority

It’s not a new sentiment by any means. Bad data IN means bad data OUT. So why is it still such a hot piece of the AI conversation? Some talks suggested several industries are a little late to the game in organizing and restructuring their data to be able to quickly jump from data lakes to LLMs. There are still so many layers and steps to getting data truly structured and ready for AI consumption. At the same time, many senior leaders and decision makers are still playing catch up to understand what they need to be doing to adopt AI quickly and effectively.

Thus, data fragmentation emerged as a common theme. During the "AI and Data Management in Business" discussion, Mary Collins emphasized the importance of "getting the right data, not just all data." Keith Kamusa added that success requires "understanding how people interact with systems, how teams collaborate, and how organizations operate." From evaluating ROI and feasibility, to the Importance of cloud infrastructure for data management, we heard panels reassuring leaders they should make decisions based on research, not competitors, and focus on defining the desired business outcomes. 

The End of Traditional Engagement

It's no longer enough for companies to just throw technology at customers. We've reached a point where technology alone can actually feel impersonal. While this could give a lot of tech people pause, there are plenty of opportunities for success. Whether you're a global giant like Netflix or a local storefront down the street, the key to success has always been creating engaging experiences. The increased power of genAI is just creating new challenges to improve those experience even more. It's about finding ways to use technology to connect with people on a deeper level, whether that means building stronger communities, providing more personalized services, or simply making life a little easier and more enjoyable.

During the "Marketing Evolution and Consumer Engagement" panel, Mastercard's Raja Rajamannar made a striking observation: "Traditional marketing is dying; consumers demand more engagement." This shift mirrors what we're seeing across AI adoption—technical capability alone isn't enough. Netflix's Josh Simon reinforced this point by showcasing how their platform creates "immersive experiences like Squid Game live events" to fuel fandom, demonstrating that technology must enhance, not replace, human connections.

This principle of prioritizing engagement extends beyond the entertainment industry. In the public sector, AI can play a crucial role in enhancing workforce development and citizen services. For example, the Department of Labor can leverage AI to streamline application processing and personalize training programs, potentially even utilizing innovative VR/AR technologies. Similarly, the Washington D.C. government showcased how AI can be used to optimize city planning in emerging communities, ensuring new developments respect and integrate with the city's historical areas.

On a very separate track, but sharing similar challenges, restaurants also face increasing pressure to optimize operations, enhance customer experiences, and adapt to evolving consumer demands. No matter the number of storefronts or menu items, technology is no longer a nice-to-have; it's a critical enabler for success. Tech-enabled delivery and digitized customer interactions can address labor shortages and minimize delivery times, but can it maintain a human-centric experience? 

Whether it's for consumers, employees, or citizens, organizations across all sectors can and need to harness the power of AI to drive positive change and build a more connected future. Doing this while also focusing on creating meaningful and engaging experiences for humans, could prove to be the real differentiator. 

Practical Steps to Make AI Awesome for Humans:

1. Start with Human Understanding As Netflix's approach to experiential marketing shows, success begins with understanding user needs. This principle extends to healthcare, where, as discussed in the "AI and Brands" panel, "codifying brand identity and using AI to behave like consumers can provide valuable insights."
2. Design for Trust and Protection The FTC panels highlighted rising concerns about AI-assisted fraud, while healthcare discussions emphasized the need for what one speaker called "an AI constitution embedded in system prompts." Your AI interfaces must prioritize transparency and ethical use from the ground up.
3. Enable Inclusive Experiences From Be My Eyes to healthcare AI applications, successful solutions must serve diverse populations. As highlighted in the AI and Brands discussion, "detailed prompting is recommended to avoid stereotypes" and ensure inclusive design.
4. Bridge the Technical-Human Gap Success stories from Hippocratic AI to Asha AI show how AI can extend beyond technical capabilities to deliver empathy in critical interactions. As one panelist noted, "gradual implementation and monitoring of AI safety settings is crucial."

Get Started: Let's Build for Humans 

Ready to create AI solutions that truly serve all users while maintaining compliance and security? Let's discuss how our UX+AI+Code approach can help you build AI implementations that don't just work—they transform how humans thrive.

In a world where AI capabilities are advancing daily, the difference between good and great solutions lies not in the algorithms, but in how well they serve human needs. Partner with Tonic3 to ensure your AI initiatives don't just meet technical requirements—they make tech awesome for humans. 

Ready to make AI awesome for humans?