Q.What is an AI agent, and why does it matter now?
A.It is not a chatbot—it is AI that can execute work. It is becoming an important way to raise productivity and competitiveness.
Japan is projected to face a shortfall of roughly 3.4 million workers by 2030. Businesses that deploy AI agents can reduce repeat work and serve more customers with the people they already have. In an OECD survey of more than 5,000 SMEs, 65% of GenAI users reported better employee performance, 35% said it helped them scale, 29% said it helped them compete with larger businesses, and 26% reported higher revenue.12
Q.Is simply adopting an AI agent enough?
A.No. Unless the five challenges are addressed, costs can rise without producing results.
The companies that do not see results are rarely blocked by the model alone. They stop where work, data, and operations have not been prepared to let an agent act.23
Why AI fails to create value in the field
Workflow redesign
Only 21% of GenAI adopters have fundamentally redesigned their workflows, so people ultimately still have to complete the work.4
Disconnected data and systems
Because data and existing systems remain disconnected, AI cannot access the information it needs to complete a workflow.5
No operational owner
Because nobody owns day-to-day operation, the people and process improvements that let AI scale never take hold.3
Unclear authority and accountability
Because authority, security, and accountability are unclear, important work cannot be safely delegated to an agent.6
No measurement and improvement loop
Because results are not measured and improved, AI never becomes embedded in daily work and remains a pilot.4
Q.How can those issues be solved?
A.We provide a Data / AI Agent platform service designed to solve them.
Workflow-specific agent design
Our field team breaks down repeat work and defines the agent’s role, decision rules, execution scope, and escalation conditions for your company.
Data connectivity for real work
We connect more than 10 times the data formats handled by general-purpose AI tools, including the documents, spreadsheets, images, audio, and systems that make up a workflow.
Hands-on operating support
A field team centered on University of Tokyo students stays close to real usage and improves fit with the work after launch.
A trustworthy AI control layer
Senior engineers with experience implementing large-scale security systems design access rights, approval points, and exception handoffs so that people retain control.
Measured execution performance
We manage speed, accuracy, exceptions, and correction rates as operating metrics—translating up to 58-times faster processing and up to 3.2-times higher answer accuracy into business outcomes.