Priority’s aiERP offers a practical demonstration of where AI integration in enterprise software is heading. After watching the ERP industry talk about AI for years, it’s worth examining what happens when embedded capability is genuinely baked into the architecture rather than added as a feature layer. The difference becomes apparent when you see how users interact with the system and, more importantly, what they can accomplish that was previously difficult or impossible.
The real test of any AI implementation isn’t the technology itself, it’s whether it changes how people work. Priority’s approach does this across several dimensions, from how users query data to how the system anticipates needs and surfaces insights.
Talking to Your ERP Like a Colleague
The conversational AI interface represents the most immediately visible change. Natural language queries replace traditional menu-only navigation. Instead of navigating through multiple menus, you simply write what you need: ‘Show me February’s open orders.’ The system understands, opens the required screens or runs a report. ‘Create a report of quarterly sales by product family’, and Priority generates the report. Want to automate workflows? Type ‘Email John about sales orders over £5,000’ and watch it happen. This reduces the learning curve significantly. Users can access functionality without memorising where it lives in the system architecture.
This functionality extends well beyond basic searches and information requests. You can create complex business rules through natural language: ‘Alert me when inventory is low.’ Priority aiERP translates that into an automated rule monitoring stock levels and notifying you when action is needed. The barrier between intent and implementation essentially disappears.
New in v26.0, Priority has introduced the aiERP Companion – a personal agent that handles complex operational tasks across finance, sales and supply chain modules. The companion analyses signals, validates data and executes tasks like creating journal entries, processing invoices, setting up vendors and products, and generating purchase orders.
Users ask questions, issue instructions and approve actions in natural language while the system assembles the relevant data, guidance and insights. This means completing tasks faster, with fewer errors and without wrestling the system’s underlying structure. Future releases will expand the agent ecosystem to detect anomalies, forecast collections, and trigger automated workflows – moving decision-making closer to real-time.
Extracting Meaning from Data
Priority Analytics lets you build reports without technical expertise, but the real value emerges when you run AI insights on the data. Rather than staring at spreadsheets, you ask Priority to analyse what the numbers mean – identifying trends, anomalies and patterns you might otherwise miss. This bridges the gap between raw information and actionable insight.
The agents perform inventory checks and counts – and can generate purchase orders based on existing forecasts. You can also run AI analysis on sales data, historical trends and inventory patterns to inform your own forecasting decisions – letting the system highlight what matters rather than requiring manual analysis.
Looking ahead, Priority is building more sophisticated predictive capabilities. Upcoming releases will add built-in advanced analytics to detect anomalies, forecast collections and trigger automated workflows – moving decision-making closer to real-time. The roadmap includes dedicated machine learning models for demand forecasting, cash flow prediction and churn risk scoring, enabling more proactive business management across supply chain, finance and sales.
Smarter Communication and Personalisation
The AI Writing Assistant handles routine communication tasks – grammar correction, tone adjustment and message formatting. You can toggle between AI-assisted and classic editors, create emails directly from business workflow systems, insert dynamic fields, and enhance messages with images and emojis when appropriate.
The personalisation capabilities demonstrate how thoroughly embedded AI is woven throughout the platform. Priority’s approach includes homepage shortcuts tailored to your role, organisation of actions based on your workflow, automatic hiding of unused functionality, autosaving your frequent searches, and a proactive to-do list widget that surfaces what needs your attention.
Rather than requiring manual configuration, the system learns usage patterns and adjusts the interface accordingly. This reduces time spent on repetitive navigation.
The Fundamental Difference
Traditional ERP processes data according to predefined rules. Priority’s implementation learns from usage patterns, anticipates requirements and surfaces insights proactively rather than waiting for specific queries.
This shift matters because the practical impact is measurable. Natural language interaction reduces training requirements. The ability to ask questions in plain language instead of navigating menus cuts onboarding and ongoing training time. Insights surface proactively rather than requiring manual analysis, enabling faster decisions with more confidence. When working with clients, the biggest challenge isn’t lack of data – it’s making sense of it.
Priority’s approach solves that, transforming complex data into actionable guidance.
Effective AI integration in ERP isn’t about feature lists. It’s about reducing friction and enabling decisions with less effort. Priority’s aiERP demonstrates what that looks like when executed well: accessible, actionable and genuinely useful. For businesses ready to move beyond traditional ERP limitations, this represents where enterprise software is heading.
Phil Abbott
Phil leads a team of specialists to efficiently implement IT systems, including ERP software, to a variety of client businesses across manufacturing, retail, and healthcare.
With over 25 years of experience in supplying IT solutions and analysis to optimise business operations and performance, he previously worked at LegalMentor, ECommerce Strategies Ltd, and Cazenove Capital Management.
Having worked in the IT industry for his entire career, with experience in portfolio management and ecommerce, Phil offers a unique perspective and understanding of cross-industry business and technology requirements combined with detailed integration know-how.
