Answering "Where Do We Even Start?" — Launch of AI Roadmap & Small-Start Hands-On Consulting

"We want to use AI, but where do we even start?" — we answer that question with consulting that walks alongside you, from a current-state diagnosis and ROI-based prioritization to small-start validation and on through production rollout and in-house capability.

Amatsukaze Inc. has launched a consulting service that builds an AI adoption roadmap and provides hands-on, small-start support for small and medium-sized enterprises (SMEs) ready to take their first step into AI. The service is back-cast from real frustrations on the ground — "we want to use AI but don't know where to begin," "there are too many tools to choose from," "we ran a PoC but it never reached production," and "we can't gauge the return, so we can't make an investment decision." Starting from a careful interview and an inventory of your operations, we identify where AI actually pays off based on cost-benefit, start small to verify it, and connect that to production rollout and in-house capability — walking the entire path with you.

The Current Landscape: Caught Between "We Want to Adopt" and "We Can't Move Forward" ​

While generative AI has spread rapidly as a personal productivity tool, adoption at the organizational level — and especially full-scale deployment at SMEs — still lags. A survey conducted in July 2025 by ICR Inc. (published September 2025) found that fewer than 10% of companies with under 10 employees had adopted generative AI, a stark contrast with the more than 30% adoption among large enterprises with 1,000 or more employees — making the gap by company size unmistakable.

The barrier lies less in the technology itself than in knowing how to proceed. In a 2025 survey by Tokyo Shoko Research, the most cited reason for not pursuing generative AI was "we have no specialist staff to drive it" (around 55%), followed by "we cannot evaluate the pros and cons." Japan's Ministry of Internal Affairs and Communications, in its 2025 White Paper on Information and Communications, likewise found "we don't know how to use it effectively" at the top of corporate concerns. In other words, most companies are not rejecting AI — they simply cannot see how to begin in their own context.

Nor can the companies that have started rest easy. "The GenAI Divide: State of AI in Business 2025," published by MIT's NANDA initiative in August 2025, reported that only about 5% of corporate generative-AI pilots reach a clear impact on the bottom line. Gartner has likewise predicted that at least 30% of generative-AI projects will be abandoned after the PoC stage by the end of 2025. As the terms "PoC fatigue" and "PoC death" suggest, the structural difficulty of getting stuck at the experiment stage — never reaching production — has become a widely shared challenge.

Why Hands-On Consulting, and Why Now ​

The points where SMEs stumble with AI adoption come down to three questions.

• We don't know where to start: With too many tools, models, and too much information, companies cannot decide which of their operations to begin with. The very abundance of choice stalls the first step.
• We get stuck at the PoC: A demo may impress, yet whether it can withstand real operations goes unverified, and experiments repeat with vague objectives and evaluation criteria. The skills to build a PoC and the skills to run it in production are different things, and projects stall in the gap between them.
• We can't see the return, so we can't decide to invest: Without a picture of where it works and what return they can expect for the cost, management cannot commit to the investment decision.

None of these is solved by picking a tool in isolation. What divides success from failure is whether you have a partner who stands in your business and management context, judges the right order in which value appears, and helps you move forward by trying small and verifying as you go. That is precisely why hands-on consulting holds so much value for SMEs, who are the least likely to keep dedicated IT staff on hand.

What Outcomes You Can Expect ​

Walking alongside you, this service can deliver the following benefits.

• Management decisions move forward: By organizing candidates by cost-benefit and feasibility and visualizing the priorities and roadmap, management can finally make the "do or don't" and "where to start" investment calls.
• A small start minimizes the cost of failure: Because you start small, verify, and only then scale, you keep initial investment low and hold the inherently hit-or-miss risk of AI investment to a minimum.
• You concentrate where it actually pays off: By gathering resources into the operations that genuinely move the needle rather than the flashy themes, even limited staff and budget translate into reliable results.
• You gain a foothold toward in-house capability: Rather than handing the whole approach off to an outside party, walking the path together leaves judgment criteria and know-how inside your organization, building a base from which you can drive the next move yourself.

How We Make It Happen ​

Amatsukaze operates on the core principle of a low-risk "small start," working alongside you in stages from diagnosis through production rollout and in-house capability.

• Current-state interviews and operational inventory: We listen carefully to both your management challenges and your frontline operations, taking inventory of where effort, cost, and key-person dependency lie, and surface the operations where AI can have an effect.
• Use-case discovery, ROI assessment, and prioritization: We lay out candidate use cases, assess them by magnitude of impact, ease of realization, and cost-benefit, and organize the order of attack into a form management can actually decide on.
• Small-start PoC design and verification: We define a "minimum passing line" and evaluation criteria tied directly to operations (reduced work hours, fewer errors, and the like) up front, verify quickly in a small scope, and decide early whether to proceed to production or stand down.
• Roadmap for production and horizontal rollout: For the areas whose impact the validation confirmed, we map out the structure, cost, and sequencing needed for production operation, distilling it into a roadmap that anticipates rollout to other operations and departments.
• Transition to in-house operation, with ongoing partnership: While establishing the governance and evaluation mechanisms operation requires, we support the transition to a state where your organization can run on its own. Rather than "deploy and done," we work with you all the way through to operation that keeps generating value.

Why Amatsukaze Is the Right Partner ​

Building an AI adoption roadmap is not about lining up trendy tools; success hinges on whether you can tie operations, AI, and operations-in-production together in a grounded way and translate it into a design that works in production. Amatsukaze's strength is a structure that lets us work alongside you across this entire arc.

• Robust infrastructure operations expertise: We bring knowledge cultivated through the design of high-load, high-transaction systems and the construction and operation of robust infrastructure. We judge the requirements for sustained operation that lie between PoC and production from the standpoint of real operations, not theory on paper.
• Hands-on AI/LLM engineering: We have real implementation capability with the latest open-weight models, RAG, and agentic AI, so that use cases never end as "concepts on paper" but are realized as production-ready systems.
• End-to-end partnership from PoC to production: We support everything from current-state diagnosis and prioritization to small-start validation, production rollout, and the transition to in-house capability — all under one roof — staying alongside you so the plan never stalls at the seams between phases.