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AI is moving fast – and for many organizations, it’s moving in every direction at once. Teams are under pressure to roll out new tools that promise efficiency, innovation, or a competitive edge. But in the rush to adopt, AI initiatives often launch without a clear understanding of what users actually need and want. The result is fragmented efforts, disjointed experiences, missed opportunities, and wasted investment.

AI can accelerate transformation, but only if it’s pointed toward the right outcomes. User centric design brings focus to that momentum. It helps teams align AI efforts with user needs and organizational priorities, so solutions are more effective, scalable, and valuable over time.

In the push to deliver quick results, design and research (core user design practices) are sometimes seen as barriers to speed. As we note below, evidence is mounting that those technology leaders who remain committed to these core principles will capture AI’s value faster and more successfully than their competitors.

# Without User Centric Design, AI Struggles to Deliver

Business leaders widely agree that AI has the potential to improve organizational growth and productivity. It’s the reason that 78% of companies globally report adopting some form of AI tools for their business. Yet in the rush to realize these overly broad advantages, leaders are implementing AI solutions without a clear understanding of how it will create real value for users.

This speed-first mindset often comes at the expense of usability and adoption. This results in solutions that might look impressive at the outset but struggle to gain traction or improve outcomes for users. When AI efforts aren’t grounded in users’ needs and behaviors, they lead to:

Low engagement
Redundant or disconnected tools
Frustrated employees
Lost ROI

The truth is, AI can move organizations forward faster, but they’ll only move in the right direction when projects are centered in user centric design. This approach keeps user experience at the center of how AI is implemented, adopted, and used. It also considers how AI can enhance human abilities and expertise, not replace them.

# Impactful AI Delivers on User Needs, Not Design Assumptions

In practice, a user-centric approach helps teams move faster and more confidently, ensuring that AI solutions are built around real needs, not assumptions. This approach proved key for a public sector organization that wanted to develop a chatbot to connect target users with employment services. The organization assumed accessibility was the biggest barrier.

During a 7-week design sprint, Propeller’s discovery interviews revealed very different reasons behind users’ reluctance to access services online. The audience consistently cited concerns around how employment could impact their Medicaid benefits as the biggest reason to not access employment services.

Instead of focusing only on access, we designed a proof-of-concept chatbot that connected users to resources and people who could help them better understand their benefits. In testing, prospective users appreciated how quickly the chatbot got them to the services they needed. By rooting the solution in users’ needs, users felt “heard” and supported by the organization.

As this organization learned, businesses that actively seek and incorporate user feedback when integrating AI can better tailor solutions to real needs, and lay the foundation for measuring what matters most.

# User Metrics Reveal AI Design’s True Organizational Impact

One of the biggest challenges in AI integration is knowing what to measure. Leaders often default to technical metrics like system uptime or cost savings because they are easy to track. But those metrics don’t reflect whether AI is actually helping people do their work better.

Experience-focused indicators give a clearer picture of whether a tool is working. These metrics include:

Adoption: Are people using the tool?
Satisfaction: Do people trust the tool? Does it meet their needs?
Alignment: Does the solution support broader business goals?

These metrics are often the earliest signals of success, or early warnings that something isn’t working. Failing to track them risks missing the full value of user-aligned AI integration. The most impactful metrics reflect a unifying vision rooted in real user needs and help align AI efforts with the strategy of the entire organization.

User experience isn’t a soft metric. It’s the most reliable indicator of whether your AI investment will pay off.

# A Unified Roadmap Delivers the Consistent AI Experience Users Expect

Another challenge bogging down AI initiatives is the lack of coordination across solutions. Too often, AI initiatives occur in silos without a cohesive strategy. This reflects the often-siloed nature of departments, each tasked with solving an independent strategic priority. When siloed teams implement AI, solutions target a single problem. The problems with this approach don’t emerge until users navigate various touchpoints and become frustrated by a lack of consistency in their experience.

Operating within this disharmony is like listening to an orchestra playing without a conductor. No matter how masterful each musician might be, a lack of coordination will lead to chaos. Few people would attend such a cacophonous concert. Yet leading companies are taking this unorchestrated approach to AI programs.

To move from noise to harmony, organizations need a unified roadmap that aligns AI efforts across teams, systems, and user journeys.

# Tech Organization Aligns Product Roadmaps Around User Needs

This was the case for a large tech organization that had tasked teams across the enterprise with driving innovation. Propeller was brought in by an employee productivity team to design a future-state support experience and deliver an AI solution that could help employees work more effectively.

During discovery, we found that the organization had launched a plethora of AI tools, but each delivered vastly different experiences. Importantly, few matched the seamless digital experiences that employees were used to navigating in their personal lives.

Through an AI-enabled user centric design sprint, we helped develop a clear employee experience strategy and roadmap across three time horizons. Our team used AI to synthesize findings and accelerate working sessions. Cross-functional teams, each of which owned different solutions that support experience, came together to ideate. These sessions enhanced clarity around vision and helped speed decision-making around product roadmaps. The result was product roadmaps that align with users’ needs and expectations.

By stepping back to orchestrate AI solutions across the user journey, organizations can shape a unifying strategy around which otherwise siloed teams can align. This unified roadmap ensures that users can engage with any touchpoint and find a consistent experience. Orchestration demands collaboration, compromise, and a shared commitment to the end-to-end experience.

# These Three User Centric Models Can Accelerate AI Adoption

To implement AI effectively, organizations must connect AI solutions to real user needs, but they must also ensure this work aligns with the overarching strategy. Success across these measures depends on the facilitation of cross-functional knowledge sharing at every level of the organization.

Based on our experience, a combination of three models is most effective in leveraging knowledge across all levels of the organization:

Dedicated Innovation Engine: Championing AI strategy at the leadership level can accelerate innovation and, when the time is right, help scale implementation throughout the enterprise. Organizations can establish a multidisciplinary team to explore and implement AI solutions that align with organizational goals. This team can help shape a consistent structure and user centric design principles, including clear user-led and experience metrics and feedback loops, for all AI initiatives.
Organic Team Initiatives: Department-led AI initiatives, grounded in real user needs, still hold tremendous value as they drive innovation and foster ownership. Organizations should continue to encourage departments to identify and pilot AI applications relevant to their functions. However, these initiatives should be grounded within a centrally owned, unified user experience strategy. This can guide cross-functional discussions and encourage sharing of lessons learned with other departments in order to broaden AI’s impact and speed adoption.
Individual Incentives: To acnhor AI initiatives in user needs, let users champion AI projects. Champions fuel innovation by connecting AI solutions to real user needs. Organizations that recognize and reward employees who contribute to AI integration can gain powerful insight and speed broader implementations that already demonstrate buy-in. This also promotes a culture of continuous improvement.

Approaching AI initiatives from each of these angles creates the healthy tension that pushes leaders and their teams to innovate.

# Leverage User Feedback to Unlock Value from Past AI Pilots

Nearly half of AI pilots never reach scale. According to S&P Global Market Intelligence, on average, 46% of AI proofs of concept are abandoned. Repeated failure in experimentation has led to a growing sense of “AI fatigue” that can dampen enthusiasm for future deployments. Giving into this fatigue risks overlooking the value that comes from using failure to guide success in future initiatives.

The best AI systems improve through feedback loops. Similarly, AI deployment teams can’t forget the value of incorporating feedback from users. This essential feedback helps users to feel heard and increases the likelihood of buy-in to future initiatives. With orchestration across departments, each team leading AI initiatives can learn from the failures in other departments and move more swiftly to success.

# Propeller Helps You Orchestrate What Comes Next

Propeller has a proven history of guiding organizations through the complex process of AI integration—and applying our own AI tools to speed the successful execution and delivery of projects for clients.

Our depth of experience in designing employee-centric solutions—from onboarding journeys to support systems that drive adoption of new technologies—ensures that user experience is not an afterthought but the foundation of your AI initiative. By leveraging AI to accelerate research and prototyping, we help clients move swiftly from concept to implementation of effective solutions rooted in user needs.

If you're ready to harmonize your organization's AI initiatives with user centric design, Propeller can help.

User Centric Design Is the Missing Piece in Your AI Strategy

Bec Hallett