As digital colleagues join the workforce, the platform-first model of enterprise IT is giving way to a protocol-based architecture that enables intelligence, agility, and coordination across human-AI teams.

Enterprise IT was built around the idea of standardisation. To scale efficiently, organisations invested in platforms that could centralise data, enforce process discipline, and act as the single source of truth. This logic shaped the rise of ERP, CRM and workflow tools - and created a generation of transformation programmes focused on digitising the past.

But that model is starting to collapse.

Building an on-premise AI infrastructure is an important task that requires careful planning, investing in the right technology, and following best practices. Unlike cloud-based solutions, an on-premise setup gives you more control over your data, better security, and the ability to customize the system to meet your specific needs. However, it also requires technical knowledge, resources, and regular maintenance to work effectively.

The rules of enterprise software are being rewritten. For decades, the strategy was clear: standardize processes to cut costs and streamline operations, paving the way for ERP, CRM, and other rigid systems to dominate. These legacy systems belong to an era of fixed processes and centralized control - a model designed for uniformity and efficiency that ultimately locked businesses into inflexible structures

Businesses are realizing that proving AI can work is no longer enough. To succeed, AI initiatives must deliver measurable value and remain adaptable to long-term needs. The shift from proof of concept (PoC) to proof of value (PoV) represents a fundamental change—one that emphasizes outcomes over feasibility and ensures AI solutions address real business challenges.

Perishable goods present unique challenges for supply chains. With short shelf lives, unpredictable demand, and the need for consistent cold chain management, the margin for error is slim. AI, and AI agents - new digital colleagues in supply chain teams - in particular, offers a way to address these complexities, providing advanced capabilities for improving forecasting accuracy, enhancing visibility, and building resilience.