The precision of product development using Generative AI (GenAI) is evolving at a staggering pace. Tasks that once required specialized skills and vast amounts of time—such as creating website or app mockups—can now be output with high quality through just a few rounds of iteration with AI. We are entering an era where the creative field is fully equipped to instantaneously materialize abstract ideas.
On December 12, 2025, Advanced AI Partners Inc. and Neuromagic Co., Ltd. co-hosted a seminar titled “Breaking the Barrier to GenAI Adoption! Practical Approaches to Moving Teams and Organizations.”
The event featured Tomoki Sekiguchi, AI Strategist at Advanced AI Partners, and Naoto Yoshioka, Design Researcher at Neuromagic. They introduced two pivotal strategies:
- The Production Approach: Rapidly visualizing prototypes and driving consensus through lightweight validation cycles.
- The Implementation Approach: Expanding GenAI utilization from frontline practice to the entire organization.
This article provides a comprehensive report on the insights shared during the session.
Challenges in the GenAI Era and the Importance of Process Design
In the first session, Neuromagic’s Mr. Yoshioka explained the key points of integrating GenAI into the production process.
While GenAI can generate high-quality outputs in minutes, a significant “adoption barrier” remains: many AI-generated deliverables are either rejected on-site or eventually rebuilt from scratch by human hands. The root causes often lie in the creator’s inability to explain the rationale behind the AI’s output and the lack of a process that allows for human intervention. When the generation process is a “black box,” the critical design intent—what inputs were used and why the result took that specific shape—is lost.
Furthermore, presenting a finished image too abruptly deprives stakeholders of the opportunity to validate requirements and reach a consensus on structure. To solve these inherent issues, Mr. Yoshioka emphasized the renewed importance of “Process Design.” He highlighted three pillars for establishing an effective collaboration process with AI:
- Traceability: Ensuring the journey from initial data to final output is trackable.
- Visualization: Distinguishing between AI-generated work and human-led tasks.
- Checkpoints: Integrating specific moments where human judgment is required.
By designing a workflow—starting from a project overview, narrowing down targets, creating personas and customer journey maps, and finally moving to concepts and wireframes—teams can guarantee reproducibility and accountability.
As an example of a tool supporting this collaboration, Mr. Yoshioka cited Miro AI. Its strength lies in its ability to visualize the source information, prompts, and outputs as a continuous sequence on a single board. This allows all project members to trace the logic behind a design, leading to a more convincing and smoother consensus-building process.
Creating Use Cases and the “Ambassador Strategy” to Move Organizations
In the second session, Mr. Sekiguchi of Advanced AI Partners discussed creating use cases and building an internal framework for AI promotion.
He noted that many companies face barriers such as communication gaps with management or a lack of concrete use cases despite having a technical foundation in place. While basic tasks like meeting minutes or brainstorming often stick, many organizations fail to reach the level of advanced utilization that fundamentally transforms business processes.
Often, this is because stakeholders “outsource” the thinking of use cases to others. To break this cycle, he proposed a three-stage internal promotion strategy: Improve AI Literacy → Establish Use Cases → Scale Nationwide.
A key tactic here is “Prototyping” to spark discussion by showing something functional. By selecting an application area based on a hypothesis and performing a simple implementation within weeks, teams can verify “what can and cannot be done” and share those findings with stakeholders. Tools that automatically generate prompts for specific business problems or low-code tools are highly effective in supporting this phase.
Furthermore, Mr. Sekiguchi introduced the “GenAI Ambassador” strategy. This involves appointing individuals with high AI interest and strong communication skills within each department. These ambassadors bridge the gap between stakeholders and the front lines, returning insights to the broader organization. He emphasized that these ambassadors should be trained over roughly six months and supported by internal communities or portals to ensure they don’t become isolated, fostering sustainable AI adoption.
What is Required of Us Moving Forward
This seminar underscored that the roles of creative and business professionals are at a major turning point due to the spread of GenAI.
Now that GenAI can produce high-quality outputs, the value of companies and individuals lies in their ability to verify whether those outputs are “truly valid” from a professional perspective and to lead the way toward consensus. The approaches shared in this seminar suggest that GenAI should not be treated merely as a tool, but as a catalyst for a strategy where human intervention maximizes value.
Embracing the evolution of human roles and building a system of “co-creation”—where humans and AI amplify each other’s strengths—will be the key to overcoming the adoption barrier and achieving true innovation.