Predictions 2026 – AI and ERP

1. What do you think the biggest challenge customers will be looking to solve using AI in 2026? 

One of the main challenges businesses will tackle with AI in 2026 is breaking down their data and process silos to unlock real value. Many organisations still struggle with fragmented data scattered across systems, which prevents AI from seeing the full picture. Integrating these silos and standardising business processes will be crucial to progress. A key step is building a clean, connected data foundation, which enables companies to make their data accessible and actionable across the organisation not just for isolated pilots. 

Another part of the challenge is ensuring trust and governance. Customers increasingly expect AI to be reliable and compliant by design, with explainability, auditability, and security built in. These requirements will drive how organisations select and implement AI solutions. 

2. Given mid-sized companies may not have significant resources to invest in AI how should they prioritise investments so that they can scale AI adoption? 

Mid-sized firms need to be pragmatic with their AI investments. The priority should be high-impact, achievable projects that align directly with business goals. Rather than starting with tools, they should start with strategy: identify a few areas where AI can deliver clear outcomes, such as automating repetitive tasks or improving forecasting accuracy. 

Given the hype around AI and their constrained resources, mid-sized organisations should focus on solutions that integrate with existing systems and address their specific needs. Cloud AI services or pre-trained models often provide faster returns than custom development. 

Building internal skills is equally important. Training employees to use AI tools effectively and creating a culture of experimentation paired with outcome tracking will help scale adoption sustainably. 

In short, mid-sized firms should focus on a small number of initiatives tied to core business priorities, strengthen their data foundations, and grow capabilities step by step. 

3. What breakthroughs in AI (in reasoning, autonomy, or multimodality) are most likely to reshape business operations in 2026? 

AI’s reasoning capabilities are improving rapidly. By 2026, we’ll see reasoning systems that can analyse complex scenarios and recommend actions. For example, reviewing financial data, spotting risks, and simulating different outcomes before decisions are made. 

Thanks to advances in agentic AI, we’ll also see autonomous agents managing end-to-end workflows. Imagine an AI agent that, given a new project, can create work orders, assign tasks, notify team members, and even prepare timesheets. Gartner estimates that 40% of enterprise applications will include embedded, task-specific AI agents by 2026 (up from less than 5% in 2025). This shift will free employees to focus on higher-value work, supported by strong governance and human oversight. 

Multimodal AI will also transform ERP systems. The ability to understand and connect text, images, and documents will make automation more context-aware. Tasks that once needed human review, like validating invoices, handling heavy contracts or reading purchase orders, will increasingly be handled by AI. 

4. What will be the biggest non-AI related development in ERP software in 2026? 

Beyond AI, the next big shift in ERP is user experience. Modern users expect their business software to feel like consumer apps: intuitive, conversational, and accessible on any device.  

By 2026, ERP systems will integrate natural-language queries and chat interfaces, allowing users to ask for data, approve workflows, or check KPIs in plain English. 

This simplicity drives adoption and reduces training needs. ERP software is becoming not only smarter but also lighter, more adaptable, and human-centric. 

5. Looking at all the technological change happening now what would be one piece of career advice you would offer someone seeking a similar career to you? 

My advice is to stay curious and adaptable. Technology evolves fast, and the best professionals are those who continuously learn and adjust. Treat every new tool or concept as an opportunity to expand your skill set. 

Invest in learning, from exploring AI APIs to understanding data and product principles and build a network of peers who share insights and challenges. Adaptability is the strongest form of career resilience.