Simplify your ERP by integrating conversational AI

ERP: rich but complex software

ERPs are major market applications offering essential multifunctional capabilities: managing orders, purchases, inventory, accounting and treasury from a single platform. That functional richness comes with a well-documented adoption cost. According to Panorama Consulting’s 2025 report, 68% of ERP projects fail to fully meet their objectives, and the three most-cited causes (inadequate change management, poor data migration, inexperienced teams) account for more than 75% of failures on their own. The problem rarely surfaces at technical deployment: it plays out in real user adoption, especially among the least trained.

Key challenges include:

• Dense functional hierarchies making navigation difficult
• Partial or occasional usage by untrained third parties (suppliers, clients, accountants)
• Abundant technical terminology that varies by company

Simplifying the experience through conversational AI

Conversational AI enables users to interact with ERP systems using natural language, both written and spoken, across multiple languages. Rather than being ERP experts, users simply ask their questions and receive instant, relevant answers without navigating complex menus or consulting manuals.

In a sales ERP, for example, a field sales rep might ask: “What’s the outstanding balance for client Dupont SAS, and when was their last payment?” Without a conversational agent, this would mean opening the accounting module, then cross-referencing the invoicing screen with the payments screen. With an agent connected to the ERP, the answer comes back in one sentence, and the rep can directly ask for a payment reminder to be sent, without leaving the conversation.

Three implementation approaches

Augmented search (RAG)

Users query the ERP’s documentation base (manuals, procedures, ticket history) in natural language and get the relevant passage directly, instead of navigating a tree of help menus.

Text generation

AI drafts business communications directly within the ERP interface: a payment reminder, a credit note, a supplier account summary, reusing data already present in the system.

Transactional AI

Users create or update a record in natural language (purchase order, invoice line, supplier record) without navigating to the corresponding form or knowing exactly where it lives in the ERP.

What this means for ERP publishers

This shift is already well underway on the market side: according to Gartner, the share of cloud ERP spending going to AI-enabled solutions is set to rise from 14% in 2024 to 62% in 2027. For organizations adopting AI assistants embedded in their cloud ERP, Gartner expects financial closes to run 30% faster by 2028.

For an ERP publisher, the concrete benefits play out on three levels:

• Adoption: a shorter learning curve, especially for occasional third parties (suppliers, external accountants) who were never trained on the tool.
• Operational efficiency: less time spent searching for information or navigating menus, more time on value-added tasks.
• Competitive advantage: in a market where, per Gartner, embedded AI is becoming a selection criterion for ERP publishers on par with functional coverage.

Key takeaways

• ERP complexity has a measurable cost: 68% of projects fail to meet their objectives, mainly for adoption and change-management reasons, not missing features.
• Conversational AI addresses that adoption problem directly: searching, drafting and creating records in natural language, without switching screens or vocabulary.
• The market confirms this shift: AI spending on cloud ERP is set to roughly quadruple as a share of total spend between 2024 and 2027, per Gartner.

For ERP publishers, the question is no longer whether conversational AI should be part of their product, but how fast it can bring down this adoption-driven failure rate.