Current & Projected Use of AI in ERP Systems (2025 Report)

Written by Todd Rudin | Oct 7, 2025 7:11:10 PM

Research Highlights

85% of ERP vendors are incorporating AI features. (1)
82% of manufacturers plan to increase their AI budgets in 2025 to build “AI‑ready ERP” systems. (2)
The AI in ERP market was valued at $4.5 billion in 2023, and is projected to reach $46.5 billion by 2033. (3)
By 2027, at least 50 percent of ERP systems with AI-enabled features will be enabled through generative AI capabilities (4)
64% of businesses say AI already boosts productivity. (5)

What does “AI in ERP” really mean?

AI in ERP refers to embedding machine learning, natural language processing, predictive analytics and automation directly into ERP workflows, beyond just reporting tools. (6) It means the ERP system can:

Automate routine tasks (invoice matching, reconciliation, approvals)
Generate forecasts and detect anomalies
Provide smart assistants or chat interfaces
Continuously learn and optimize based on data

How many ERPs use AI now?

This is a common SEO question. The short answer: many, but adoption is still evolving.

85% of ERP vendors are working AI capabilities into their suites. (1)
40% of companies say AI is “important” in their ERP decisions, and 16% say embedded AI is a must‑have. (7)
Among manufacturers, 82% are increasing AI investment in relation to ERP. (2)

So: while not every live ERP system today runs AI features in production, the majority of vendors are enabling them, and a substantial portion of new ERP decisions factor AI in.

Artificial Intelligence In Oracle NetSuite

Oracle NetSuite is one of the leaders in AI adoption, with several recent innovations:

AI Connector Service – Lets users connect their own AI models (e.g. OpenAI, industry-specific LLMs) securely to NetSuite data using Oracle’s new Model Context Protocol.
Prompt-based search – Users can now analyse data and generate reports using plain-language prompts, removing the need for complex saved searches.
SuiteScript GenAI API – Developers can embed generative AI into custom fields and extensions for more intelligent workflows.
Intelligent Recommendations – AI suggests products based on customer behaviour and past purchases to improve sales performance.
Over 200 AI enhancements – Oracle continues to roll out AI features across NetSuite’s finance, supply chain, and operations modules.

For more information, check out our in depth blog post. Or if you're interested in exploring NetSuite for your business, use our calculator below to get an instant personalised license quote.

Why are organizations pushing AI in ERP now?

Organizations looking for ERPs are now more keen than ever to have AI features included. It's no longer just a "nice to have", it's becoming a requirement. But what’s driving this shift?

Decision fatigue and data overload: Businesses are handling more data than ever, and traditional ERP tools aren’t built to extract insights fast enough. AI helps process large datasets quickly, surfacing trends and anomalies that would otherwise be missed. As data volumes grow, ERP platforms that can interpret and act on that data with AI are becoming a competitive advantage (5) (6).
Pressure to reduce costs and do more with less: AI can automate manual ERP processes like invoice processing, stock replenishment, and reconciliation, freeing up teams and cutting overheads. This is especially important in industries facing margin pressure or staff shortages (8)
Faster decision-making: AI enables real-time forecasting, intelligent alerts, and predictive analytics, helping leaders act faster and more confidently. In volatile sectors like manufacturing, speed is essential.
Demand for smarter workflows: Businesses increasingly want ERPs that guide users, not just record transactions. AI delivers context-aware recommendations and intelligent search features (5).
Industry-specific use cases are maturing:
→ In manufacturing, AI is being embedded across production, inventory, and service modules. Over 77% of manufacturers now use AI in at least one ERP workflow (8).

AI isn’t just enhancing ERP, it’s changing expectations. Buyers increasingly want systems that think, not just store.

Which AI types are being added to ERP?

Predictive analytics & forecasting — for demand, cash flows, supply chain.
Automation / RPA / OCR — handling data capture, invoice processing, approvals. Some firms report up to 25% cost reduction in tasks like those (9).
Generative AI — expected to be standard in 50% of AI-enabled ERP systems by 2027.
Anomaly detection — flagging unusual transactions or exceptions.
Natural language interfaces — query via text, conversational agents.

What holds back full AI adoption?

Data quality & integration – fragmented systems make unified AI difficult.
Change management – reluctance, trust, skills gaps.
Explainability & governance – “black box” AI is risky in compliance contexts.
Scaling from pilot to enterprise – many AI projects stall before full deployment.

What’s Next for AI in ERP?

AI is no longer a future trend in ERP, it’s the direction of travel. But over the next few years, we’ll see it shift from experimental features to deeply embedded, standard functionality across most major platforms.

According to Microsoft, by 2027, at least 50% of ERP systems with AI capabilities will support generative AI, meaning users will be able to generate reports, surface insights, and automate tasks using nothing more than a prompt (9). This will dramatically reduce the learning curve for new users and speed up decision-making across departments.

We’re also likely to see a major shift from “black box” AI models embedded by vendors, to more configurable, bring-your-own-model approaches, like NetSuite’s new AI Connector. This gives businesses more control over which AI they use, how it’s trained, and what data it can access.

Another important factor will be AI governance. As adoption grows, so too will the pressure to ensure AI outputs are auditable, explainable, and compliant with regulations. Organisations will need robust frameworks for testing AI outcomes and managing risks.

Finally, expect more industry-specific AI use cases to emerge, with tailored functionality for manufacturers, financial services, and healthcare providers baked directly into ERP platforms.

In short: AI in ERP is moving from possibility to expectation. The platforms that deliver meaningful automation and usability, without sacrificing control, are likely to dominate the next phase of ERP innovation.

Sources:

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