What happens to the solution architect's role when AI rewrites the rules of technology — and customer expectations — almost overnight?

At the Tokyo Tech Meetup × IT Career Event 2026 — organized by HirePlanner and Venture Cafe Tokyo on February 19th — three enterprise technology leaders came together to answer exactly that question. 

Their companies operate in very different spaces: open-source infrastructure, AI transformation consulting, and enterprise automation and Integration. Yet the conversation that unfolded revealed a strikingly consistent message about what it takes to succeed as a solution architect or sales engineer in 2026.

The discussion was moderated by Fabien Brogard Cipriani, Founder and CEO of HirePlanner, and featured Shingo KITAYAMA (Principal Specialist Solution Architect at Red Hat Japan), Leo LINDER (Founder and CEO of Emerge AI), and Atsuya YAMAKAWA (Senior Solution Consultant at Workato Japan).

Here is what they shared:

The role of the solution architect has always sat at the intersection of technology and business. But panelists agreed that the terrain has shifted dramatically — and the pace of change is not slowing down.

According to Shingo KITAYAMA (Red Hat Japan), the core challenge today is no longer knowing which technology to choose. It is helping customers navigate a landscape of almost unlimited choices — clouds, tools, SaaS platforms, AI models — without becoming paralyzed by them. "The solution architect," he said, "has a responsibility to architect trust as much as we architect infrastructure. Customers are anxious. Our job is to help them feel safe."

According to Leo LINDER (Emerge AI), the biggest shift isn't technological—it's psychological. When AI begins to disrupt an industry, many C-suite leaders experience what he describes as a moment of "quiet" panic: the fear of being left behind while competitors race ahead.

For solution architects, that means the conversation should begin long before discussing technology. It starts with understanding the business itself: Where is the organization in its transformation journey? How urgent is the need to evolve?

As Leo pointed out, a law firm cautiously exploring AI has very different priorities from an AI robotics startup preparing to launch a humanoid companion for senior citizens.

As he explained, "It's important to go back to the basics and ask ourselves: Who are we building this solution for? How impactful will it be? How urgent is the business need? And how sustainable will this solution be over the long term?"

According to Atsuya YAMAKAWA (Workato Japan), one of the biggest misconceptions he encounters is the belief that AI can solve business problems on its own. In reality, it can't—not without the right business context.

As Atsuya explained, "AI doesn't have access to your business context or understand how your approval workflows operate. It doesn't know where your customer data resides. You have to provide AI with the right context before it can deliver outcomes that truly matter to your business."

He compared AI to hiring 500 highly intelligent new graduates. Intelligence alone doesn't automatically create business value. People need to be trained, given clear objectives, and supported by well-designed processes and workflows before they can make a meaningful impact.

The same applies to AI. Designing that context, defining the architecture, and integrating AI into business processes is exactly where solution architects play a critical role. Their job isn't simply to implement AI—it's to ensure the technology delivers tangible business outcomes.

Each panelist shared the kind of candid lessons that rarely appear in product decks or success stories.

According to Leo LINDER (Emerge AI), one of the most costly mistakes organizations make when adopting AI is treating it like a deterministic system. Unlike traditional software, which produces consistent and predictable results, AI is probabilistic—its outputs can vary depending on the context, prompts, and data it receives. As a result, organizations need to rethink not only how they design AI solutions, but also how they structure their teams and define responsibilities. With AI giving people capabilities that were once limited to specialists, clear governance, collaboration, and human oversight become essential. As Leo explained, successful AI adoption isn't about eliminating failure—it's about experimenting quickly, learning from mistakes, and ensuring those experiments take place within safe boundaries that minimize risk to the business.

According to Atsuya YAMAKAWA (Workato Japan), one of the most common mistakes solution architects make is jumping straight to a solution before fully understanding the problem. When customers ask whether a product has a particular feature or AI capability, the natural instinct is to answer "yes" and immediately start demonstrating it.

However, Atsuya emphasized that the feature being requested is rarely the customer's real need. As he put it, "The person buying a shovel doesn't actually want a shovel—they want to dig a hole. But they don't really want a hole either. They want to plant a tree, build a fence, create shade, or gain privacy."

The real goal lies beyond the feature itself. That's why he encourages solution architects to pause and ask why before discussing how. What business problem is the customer trying to solve? What outcome are they hoping to achieve? In today's AI-driven environment, where many organizations feel pressure to adopt AI simply because it's the latest trend, understanding the customer's underlying objectives is more important than ever. As Atsuya explained, solution architects aren't there simply to showcase product features—they're there to guide customers toward the right solution and meaningful business outcomes.


According to Shingo KITAYAMA (Red Hat Japan), the risk of complexity is not just technical — it is relational. When customers face too many choices and too many moving parts, anxiety replaces confidence. The SA who responds by adding more options or more technical detail only deepens the problem. What customers need first is a trusted partner who helps them make sense of the landscape, not someone selling them another layer of it.

Beyond the mistakes, each panelist shared the habits and frameworks that are genuinely improving outcomes for their teams and clients.

According to Shingo KITAYAMA (Red Hat Japan), the role of a Solution Architect extends far beyond implementing technology—it begins with building trusted relationships. Rather than jumping straight into product demonstrations or AI implementations, Shingo believes the best solution architects first take the time to understand their customers, their culture, and how they work together.

He emphasized that the most successful SAs don't simply promote products; they act as catalysts between business and technology, helping customers embrace collaboration and make better decisions. As he explained, "The best Solution Architects don't just create successful projects—they empower their customers to become champions." He also highlighted the importance of continuously developing a customer-first mindset. While junior solution architects often focus on product features and technical details, experienced professionals learn to prioritize business needs, foster collaboration, and build long-term partnerships that create lasting value.

According to Leo LINDER (Emerge AI), successful AI solutions require solution architects to understand not only the capabilities of AI models, but also their limitations, costs, and architectural implications. As models become more powerful—with larger context windows and increasingly sophisticated reasoning—architects must carefully consider compliance, data privacy, performance, and infrastructure costs before deploying them. Leo stressed that every AI interaction has a cost, making architecture and data design more important than ever. He illustrated this with a project involving 300,000 résumés, where the team initially tried to process every document with AI, resulting in unexpectedly high cloud costs. The breakthrough came when they redesigned the solution, extracting only the metadata needed instead of processing every résumé. As Leo concluded, "Every token costs money. AI is no longer just a networking, data, or security problem—it's an everything problem." The role of the Solution Architect is therefore expanding beyond technology implementation to designing AI systems that are scalable, cost-effective, secure, and aligned with business objectives.

According to Atsuya YAMAKAWA (Workato Japan), great solution architects don't sell features—they communicate business value. He encourages every solution architect to apply what he calls the "So what?" test throughout every presentation and product demonstration. Every feature should be followed by the question, "So what? Why does this matter to the customer?" By repeatedly asking this question, the conversation naturally shifts from technical capabilities to measurable business outcomes, such as reducing operational costs, saving time, improving productivity, or minimizing risk.

Atsuya shared that this mindset was inspired by the book The Six Habits of Highly Effective Sales Engineers by Chris White, which he highly recommends. As he explained, customers aren't ultimately buying features—they're investing in better business results. The role of the Solution Architect is to bridge that gap by translating technology into outcomes that matter.

The session closed with practical, personal advice — the kind each speaker would give to someone standing at the beginning of their SA career.

According to Shingo KITAYAMA (Red Hat Japan), one of the most important qualities for aspiring Solution Architects is grit—the combination of passion and perseverance in the pursuit of continuous improvement. While technical expertise is essential, Shingo believes real growth comes from constantly challenging yourself, building on your strengths, and maintaining a genuine desire to help others. Whether supporting a sales colleague or a customer, he encourages solution architects to listen carefully, stay curious, and approach every interaction with a simple question: "How can I help you?" In his view, that mindset of continuous learning and customer commitment is what ultimately shapes future leaders.

According to Leo LINDER (Emerge AI), the next generation of Solution Architects must develop AI-first habits and a disciplined approach to working with AI. Rather than treating prompts as one-off conversations, Leo encourages teams to follow a consistent framework by first defining the AI's role or persona, understanding the customer's profile, clarifying the business objective, and then assigning a specific task. This structured approach produces more reliable results while allowing organizations to capture reusable knowledge and build a shared source of truth over time. As AI becomes an integral part of solution design, those who learn to collaborate with it systematically—not casually—will have a significant advantage.

According to Atsuya YAMAKAWA (Workato Japan), one of the most valuable qualities a junior Solution Architect can develop is the confidence to be honest when they don't know the answer. Rather than guessing, he believes it's far better to say, "I don't know—but let me find out and get back to you." Technical credibility is built on facts, and customers value honesty far more than speculation. Atsuya drew a clear distinction between the priorities of salespeople and solution architects: while salespeople fear losing the deal, Solution Architects should fear losing the customer's trust. Once credibility is lost, it can be extremely difficult to regain. As he concluded, "Business decisions will still be made by humans." Even in the AI era, trust, honesty, and strong relationships remain the foundation of becoming a true trusted advisor.

Although Red Hat, Emerge AI, and Workato approach enterprise technology from very different perspectives, the discussion revealed several striking themes. The role of the Solution Architect is evolving rapidly—but the qualities that define the best professionals remain remarkably consistent.

Every speaker emphasized that successful Solution Architects begin with the business—not the product. Before discussing AI models, integrations, or product features, they seek to understand the customer's objectives, challenges, level of AI maturity, and the outcomes they are trying to achieve. Technology is simply the vehicle for delivering business value.

As AI becomes embedded in every part of the enterprise, Solution Architects must think beyond implementation. They are increasingly responsible for designing AI architectures, establishing governance, managing costs, ensuring compliance, and helping organizations adopt AI responsibly. The future belongs to architects who understand both the technology and the business context in which it operates.

Whether it's applying the "So What?" test, following a structured prompting methodology, building AI Centers of Excellence, or developing customer-first habits, the best Solution Architects rely on repeatable frameworks that consistently produce better outcomes. Excellence is rarely accidental—it is built through discipline and continuous learning.

Perhaps the strongest message from the panel was that, despite the rapid evolution of AI, business decisions are still made by people. Customers don't simply want product experts—they want trusted advisors who listen, communicate honestly, and help them navigate uncertainty with confidence. Technology may evolve, but credibility, empathy, and long-term relationships remain irreplaceable.

The tools available to Solution Architects are changing faster than ever. AI is transforming how solutions are designed, evaluated, and delivered. Yet the panel made one thing abundantly clear: the future of the profession is not about replacing human expertise with AI—it's about amplifying it.

The Solution Architects who will thrive in 2026 and beyond won't necessarily be the ones who know the most technology. They'll be the ones who combine technical excellence with business acumen, structured thinking, curiosity, empathy, and the ability to build lasting trust.

As one speaker put it, customers aren't buying technology—they're investing in outcomes. Helping them achieve those outcomes is, and will continue to be, the true role of the Solution Architect.

This session was part of HirePlanner's ongoing series of community events connecting tech professionals across Japan.

📺 To Watch the full session on YouTube, please click below 👇:
https://www.youtube.com/watch?v=u57LGm5Xj0Y&t=17s