Australia is translating strong AI foundations into real operational gains, but as adoption matures, 7 in 10 businesses say generic AI falls short of industry needs. Infor's next-generation agentic architecture is built with the industry-specific context, governance and auditability that generic AI lacks.
Key Highlights
- Australian enterprises are moving beyond experimentation: 42% have reached full-scale AI deployment, the third-highest rate of the seven markets surveyed.
- Australia leads APJ on low-friction automation: only 44% of AI output requires manual expert review, the lowest of any APJ market surveyed and 16 percentage points lower than Singapore at 60%.
- Australian businesses report average AI efficiency gains of 34%, above the 33% global average.
- Most Australian enterprises feel operationally ready for AI, with 85% confident they can manage implementation without disrupting daily operations and 82% saying their data is mature enough to support reliable outcomes.
- The limits of generic AI are already apparent: 70% of Australian enterprises say off-the-shelf AI does not adequately address their industry's specific needs.
- Investment appetite remains strong, with 68% of Australian enterprises planning to increase AI investment over the next 12 months. Australia also leads every market surveyed on AI cost clarity, at 91%.
SYDNEY, Australia – 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 Australian enterprises are converting AI into above-average efficiency gains while requiring less manual review than any other APJ market surveyed.
Australia nevertheless faces the same post-adoption challenge becoming visible among advanced AI adopters globally. Seven in 10 Australian businesses say generic AI falls short of their industry's needs, suggesting that as organisations operationalise AI, they more clearly encounter the limitations of horizontal tools across specialised workflows, regulatory requirements and industry data.
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: Australia leads APJ on low-friction AI automation as businesses become more comfortable handing critical processes to AI
Australia is a strong but measured AI market: 42% of enterprises have reached full-scale deployment, while 85% say they can manage AI implementation internally without disrupting daily operations.
This maturity is translating into practical outcomes. Only 44% of AI output requires manual expert review, the lowest of any APJ market surveyed and 16% lower than Singapore (60%). Australian enterprises also report average efficiency gains of 34%, above the global average (33%).
That advantage becomes more consequential as AI moves from supporting work to executing it. 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 Australia, the next challenge is ensuring governance and accountability keep pace as businesses give AI greater responsibility.
Finding 2: Governance will secure Australia’s lead on AI
Australia has one of the strongest AI governance foundations in the study, with just 6% of businesses reporting no owner for AI governance, risk or compliance, compared with 10% globally and 21% in Japan. As organisations move from experimentation to scaled deployment, maintaining that governance advantage will be critical to delivering AI responsibly and at speed.
Strong governance ownership does not, however, remove the need for executive-level accountability as AI assumes greater responsibility. Globally, only 10% of enterprises have appointed a Chief AI Officer, reinforcing that dedicated executive ownership remains uncommon even in more mature markets.
For Australian organisations moving quickly on AI, weaknesses in governance can become more consequential after deployment accelerates and the cost of missteps rises. Protecting Australia’s lead will require clear agent identities, permission structures, human-approval workflows and auditability to scale alongside adoption.
Finding 3: Australia's AI leaders are shifting their focus from adoption to value as generic AI falls short
Australia leads every market surveyed on AI cost clarity, with 91% saying they understand what AI adoption costs. Combined with 68% planning to increase investment over the next year, the findings suggest businesses are increasingly looking beyond AI adoption itself and focusing on where AI can deliver the greatest operational value.
That shift is making the limitations of generic AI more apparent. Seven in 10 Australian enterprises say off-the-shelf AI does not adequately address their industry's specific needs. As businesses operationalise AI, they more clearly encounter the ceilings horizontal tools impose on specialised workflows, regulatory requirements and industry data.
For Australian organisations, the next phase is not simply more AI. It is AI built around the industry context in which work happens, connected across the enterprise and governed without slowing the automation gains already being achieved.
Finding 4: Manufacturers and distributors feel the industry-fit problem most sharply
Pooled across all seven markets, 73% of manufacturing respondents say off-the-shelf AI does not meet their needs, showing how the complexity of production environments, from shop-floor processes to supply-chain requirements, exposes the limits of generic tools. Distribution feels the gap even more acutely, at 76%, while 67% of retail respondents report the same challenge.
Together, the results reveal a consistent pattern: the more specialised, variable and operationally complex the environment, the less effectively generic AI performs.
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.”
“Australia has reached the point where simply deploying more AI is no longer enough. The competitive advantage will come from applying AI to the processes that matter most, with the industry context to make the right decisions and the governance to give agents greater responsibility with confidence,” said Aidan Brecknell, Vice President and Managing Director, Pacific Region, Infor. “Australia already has strong foundations; the priority now is to protect that advantage by turning AI investment into faster, more precise and accountable outcomes.”
“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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