Japan's AI adoption remains more cautious than other APJ markets, but businesses are increasingly seeking a practical path from initial adoption to measurable outcomes. Infor's next-generation agentic architecture is built with the industry-specific context, governance and auditability that generic AI lacks.
Key Highlights
- Only 53% of Japanese enterprises feel confident they can manage AI implementation internally without disrupting daily operations, the lowest rate among the seven markets surveyed.
- Just 38% of Japanese enterprises say their data is mature and well-governed enough to support reliable AI, compared with 74% globally.
- AI governance remains a significant gap: 21% of Japanese enterprises say no one person owns AI governance, risk or compliance, the highest rate of any market surveyed.
- Japan has the lowest AI cost clarity of any market surveyed, with 45% saying they have a clear picture of what AI adoption costs, compared with 75% across APJ and 78% globally.
- Japan is the only market surveyed where standalone AI tools are preferred over an integrated, hybrid approach, at 24% compared with 11%.
- Investment momentum remains: 48% of Japanese enterprises plan to increase AI investment over the next 12 months, while 28% are not planning to integrate AI into the business.
TOKYO, Japan – October 7, 2026 – Infor, a leading enterprise provider of cloud software solutions specialized for how industries actually work, today unveiled its Infor Industry AI™ architecture and the next evolution of Infor Velocity Suite, which includes personalized adaptive user experiences, new governance models across customers’ entire enterprise, and more Industry AI agents.
This next phase of Infor's evolution responds to needs that generic ERP and AI cannot meet. Backed by the second edition of the Infor Enterprise AI Adoption Impact Index, proprietary research surveying more than 2,000 business decision-makers across seven markets, including 789 across Australia, Japan and Singapore, finds that Japanese enterprises remain cautious about scaling AI as gaps in operational capability, data readiness, governance ownership and cost clarity constrain execution.
Japan’s earlier stage of adoption also means the limitations of generic AI are less widely recognised. Forty-eight per cent of Japanese businesses say off-the-shelf AI falls short of their industry’s needs, compared with 75% in Singapore and 70% in Australia, while a further 23% have not yet formed a clear view.
Infor Industry AI reinforces Infor's commitment to developing industry-specific solutions built for the specific complexities and operational realities of a defined set of industries. The platform architecture is built to help close the value void, the gap between what technology can promise and what companies achieve, and power every business to become an agentic enterprise, where people and agents work as one coordinated team.
As AI deployment accelerates, businesses need expert agents they can trust to act, and trust only scales when those agents are coordinated across the enterprise rather than operating as isolated point solutions. Infor’s Industry AI agents are built with industry-specific context already in place, reducing the errors and guesswork that come with generic AI, using tokens efficiently, and shortening the path from deployment to value.
Infor Industry AI is organized around four platform pillars:
Precise Outcomes—An expanded suite of Industry AI agents with true micro-vertical AI expertise grounded in deep industry logic. Rather than reasoning from a generic, horizontal model, Infor's Industry AI agents draw on Industry CloudSuites, Industry Process Catalogs, and industry-specific domain language models built from decades of in-house expertise. Customers using this layer see shipments processed up to 60% faster. Paired with Industry AI Agents, the Infor GenAI Knowledge Hub provides customers with the depth of Infor’s application and industry knowledge to build custom AI Agents, now open to general availability.
Open & Connected—An interoperable architecture that extends across the customer's full ecosystem, not just Infor. Infor's modular, open platform connects to non-Infor applications and existing orchestration and analytics tools, so customers are not required to standardize on a single vendor's stack. Agents coordinate as one system through Infor IQ, the semantic layer that gives every agent a consistent understanding of the customer's business, with a catalog of more than 350 value-driven use cases available out of the box.
Easy to Use—Adaptive UX includes a personalized, AI-assembled experience that meets people in the tools they already work in. Infor's Adaptive UX pulls what a decision requires, such as the bill of materials, quoted price, and delivery date, into a single role-aware view instead of ten screens across multiple applications, so users review and act in one step. Customers can work through the Infor GenAI Assistant or through the AI assistants they have already adopted, with no requirement to standardize on one. Customers are seeing up to 90% time savings across procurement, supply chain, manufacturing, and sales workflows.
Governed—Enhanced Infor Governance, Risk, & Compliance capabilities bolster enterprise-grade security, governance, and auditability from the ground up. Human-approval workflows, agentic permission structures, and audit trails run throughout Infor's orchestration layer, enabling customers to have critical benefits like accountability and traceability natively built into the architecture. Every agent action runs through a governance, risk, and compliance layer built into the core of the Infor Industry Cloud Platform with explainable AI logic and verifiable, immutable logging of every action taken. Customers see up to a 90% reduction in auditing costs tied to access management.
Enterprise AI Adoption Impact Index: What Businesses Are Telling Us
Infor is also releasing the second edition of the Infor Enterprise AI Adoption Impact Index, surveying business decision-makers across seven markets, including Australia, Japan and Singapore. The data found that businesses’ investment in AI is outpacing efficiency gains, which Infor credits to the post-adoption gap often created by traditional AI and ERP solutions. Key findings include:
Finding 1: Japan has an opportunity to build stronger operational and data foundations for AI
Only 53% of Japanese enterprises feel confident they can manage AI implementation internally without disrupting daily operations, the lowest rate among the seven markets surveyed. Japanese organisations also report average efficiency gains of 29%, below the 33% global average, showing that the readiness gap is also reflected in realised outcomes.
Data readiness presents an even greater challenge: just 38% of Japanese enterprises say their data is mature and well-governed enough to support reliable AI, compared with 74% globally. Japan is also the only market where disagreement with this statement, at 50%, exceeds agreement.
Cost clarity remains another hurdle. Only 45% of Japanese enterprises say they have a clear understanding of AI adoption costs, compared with 75% across APJ and 78% globally, making Japan the least cost-confident market surveyed.
As AI moves from supporting work to executing critical processes, these foundations will become increasingly important. Now, globally more than half of leaders are comfortable with autonomous agents fully executing critical business processes without human input at every step. Just 11% of leaders prefer humans to make high-stakes decisions without any AI input. For Japan, establishing stronger operational, data and governance foundations now can provide a risk-mitigated path to greater AI responsibility over time.
Finding 2: Adoption maturity masks the limits of generic AI for Japan
When business leaders are asked why their AI initiatives have not delivered as expected, a familiar frustration emerges: the tool was not built for how their industry operates. This is no longer a fringe complaint. Across six of the seven markets surveyed, at least 2 in 3 businesses say off-the-shelf AI does not adequately address their industry's needs.
Japan’s earlier stage of AI adoption is reflected in lower recognition of the limitations of generic tools. Only 48% of Japanese enterprises say off-the-shelf AI does not adequately address their industry’s specific needs, compared with 68% globally, 75% in Singapore and 70% in Australia. A further 23% selected “don’t know”, indicating that many organisations have not yet formed a clear view of how generic AI performs against specialised workflows, regulatory requirements and industry data.
As adoption matures, Japanese businesses are likely to encounter these limitations more directly, making industry context an important foundation for moving from initial deployment to measurable operational value.
Finding 3: Japan has APJ’s widest governance ownership gap, while executive-level accountability remains uncommon everywhere
Even as adoption accelerates, businesses still face a fundamental question: who is accountable when AI gets something wrong? Most enterprises have assigned some responsibility for AI governance, risk or compliance, but dedicated executive leadership remains uncommon. Globally, only 10% have appointed a Chief AI Officer, and even in Singapore, the leading APJ market, just 13% have executive-level ownership of AI governance.
Japan has the widest AI governance ownership gap in the study, with 21% of Japanese enterprises saying no one person owns AI governance, risk or compliance. This compares with 10% globally, 4% in Singapore and 6% in Australia.
For Japanese organisations seeking to close adoption gaps, addressing governance early can provide a safer route to scale. Weaknesses in accountability often become visible only after deployment accelerates and the cost of missteps rises.
Finding 4: Investment appetite remains, but Japan is taking a more cautious path
Despite these challenges, investment appetite remains relatively strong, with nearly half (48%) of Japanese enterprises planning to increase AI investment over the next 12 months.
The findings nevertheless point to a divided market. While some organisations are accelerating investment, Japan also records the highest proportion of businesses with no plans to integrate AI, at 28%.
Together, the results point to a market that needs a lower-risk, practical path from initial adoption to measurable operational outcomes, with clearer costs, stronger governance and industry-specific AI that works within existing operations.
Quotes
“Everyone has the same AI models now. What matters is what those models know about your business," said Kevin Samuelson, CEO, Infor. "Customers keep telling us that general-purpose AI doesn't get the details of their world, like how a food manufacturer traces a bad lot back through its suppliers, or how a distributor has to reprice when freight costs jump. Our agents have access to our deep industry context to deliver precise and valuable outcomes.”
“What Japan needs is not to follow the same path as other markets, but to build the right foundation suited to its own local landscape. Companies need a practical path to AI that enables them to function within existing operations, demonstrate accountability, and prove value before seeking expansion,” said Yuka Kanemitsu, President and Representative Director, Japan, Infor. “The challenge then is not the willingness to embrace AI, but an actionable path forward. By working with partners that have the requisite understanding of the processes and unique requirements for each industry locally, businesses can move forward with greater confidence, control, and accountability.”
“AI only matters when it creates real value,” said Alicia Thompson, CTO, Team Air Distributing. “Infor has kept pace with our ambitions, pairing Infor Industry AI Agents with Forward Deployed Engineers who understand our industry and work as an extension of our team. Together, we’re reducing manual work and turning operational challenges into practical improvements, building trust one process at a time.”
“The next phase of enterprise AI will be defined not by access to models, but by how effectively organizations apply AI within the context of their industry and business processes,” said Shashi Bellamkonda, Principal Research Director at Info-Tech Research Group. “Infor’s focus on industry-specific intelligence, interoperability, and embedded governance addresses several of the practical barriers organizations face as they move from AI experimentation to trusted, measurable outcomes.”
Learn More:
- Learn more about Infor Velocity Suite
- Read the Enterprise AI Adoption Impact Index full report
- Register for the virtual event: AI That Moves Your Industry Forward
- Follow Infor on LinkedIn and Instagram
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Frequently Asked Questions
What is Infor Velocity Suite?
Infor Velocity Suite is an all-inclusive AI package built for your industry. It includes industry-specific AI agents, GenAI, process mining, automations – and a team of experts to implement it all for you. Infor Velocity Suite is the fastest path to real AI value and, ultimately, to becoming an agentic enterprise. Infor Velocity Suite is the single package through which customers access the capabilities announced today. It combines Infor Industry AI Agents, the Agentic Orchestrator, process mining, automation, prebuilt industry use cases, generative AI, and the implementation expertise to put them to work, all tied to a customer's Industry Process Catalog. Rather than stitching together separate tools and consumption models from multiple vendors, customers adopt a single offer with unlimited access within fair business use, so adopting faster doesn't mean a larger invoice.
What is the Infor Enterprise AI Adoption Impact Index?
It's Infor's proprietary research initiative tracking how enterprises are adopting, governing, and realizing value from AI over time. The October 2026 wave is the second in the series, surveying 2,111 business decision-makers across seven global markets, building on an initial April 2026 wave of 1,024 decision-makers across four markets.
What Was the Survey Methodology for the Infor Enterprise AI Adoption Impact Index Conducted?
The October 2026 wave was conducted in August 2026 and polled 2,111 business decision-makers across seven markets — the UK (254), US (550), Singapore (260), Japan (266), France (260), Australia (263), and Germany (258). Research was conducted by YouGov on behalf of Infor.
What does "off-the-shelf AI doesn't fit our industry" actually mean?
In the survey, respondents were asked whether generic AI solutions adequately address their industry's specific regulatory, workflow, and data requirements. Six of seven markets surveyed disagree by a clear majority — meaning most enterprises believe horizontal, one-size-fits-all AI tools fall short of what their industry actually requires, regardless of geography.
How does Infor's architecture address the gaps this research identifies?
Infor's architecture is built specifically around the two gaps the research surfaces most clearly. The industry-fit gap is addressed at the foundation: Infor's CloudSuites and underlying data models are purpose-built for a defined set of industries, rather than generalized across every vertical, and a semantic/ontology layer gives agents industry-specific context rather than generic data to reason from. The governance-ownership gap is addressed through built-in auditability and human-approval workflows across the orchestration layer, so accountability and traceability are part of the architecture rather than something a customer has to bolt on separately.
What does "industry-specific context" actually mean at a technical level?
Infor's agents draw on a shared semantic and knowledge layer — internally referred to during development as Infor IQ that gives every application in a CloudSuite a consistent understanding of core business concepts (what counts as a "location," an "item," a "customer") along with the process- and industry-specific nuance underneath them. For example, an agent handling a raw-material order for a food manufacturer needs to understand an industry-specific spec like a sugar shipment's Brix factor, while an agent handling an automotive parts order needs to understand a VIN number — two completely different kinds of precision that a generic, horizontal data model isn't built to carry. Because Infor works across a defined, finite set of industries rather than attempting to serve every industry on the planet, it can build and maintain that depth of context in a way a horizontal platform serving dozens of unrelated industries structurally cannot.
Why does industry-specific context matter for things like accuracy and cost?
Enterprise AI agents typically need to call many technical, granular APIs to complete one piece of business work, which increases both the chance of errors and the compute cost of getting a task done. Infor's architecture instead exposes business-level process APIs — the equivalent of "create a purchase order" rather than dozens of underlying technical calls — so agents can complete work in fewer steps. Combined with industry-specific context from the semantic layer, this is designed to reduce hallucination, improve reasoning accuracy, and lower the token cost of completing a given task relative to a generic AI approach working from generic data.
Does this replace a customer's existing AI or orchestration tools?
No. Infor's architecture is built to be open and composable — it's designed to plug into a customer's existing ecosystem, including third-party orchestration tools, rather than requiring a customer to replace what they already use. A single orchestration layer inside Infor coordinates work across Infor's own applications regardless of which front-end experience or outside orchestrator a customer chooses to use.
About Infor
Infor is a global leader in business cloud software specialized by industry. We develop complete solutions for our focus industries. Infor's mission-critical enterprise applications and services are designed to deliver sustainable operational advantages with security and faster time to value. Over 60,000 organizations in more than 175 countries rely on Infor's 17,000 employees to help achieve their business goals. As a Koch company, our financial strength, ownership structure, and long-term view empower us to foster enduring, mutually beneficial relationships with our customers. Visit www.infor.com.
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