Enterprise AI is moving beyond its early chapters. The first phase was experimentation. Organisations tested generative AI in isolated pilots: chat interfaces, search tools, content generation, coding assistants, and internal productivity use cases. The second phase was feature inflation. Every SaaS vendor attached copilots, assistants, summaries, or “AI-powered” labels to existing products. The third phase is beginning to emerge, unevenly, and in early form. It is not abou

The banking industry has spent the last twenty years digitising itself. Branches became mobile applications. Paper processes became digital workflows. Customer interactions migrated online. More recently, artificial intelligence was introduced to improve service, automate routine tasks and enhance decision-making. Yet the latest wave of AI may prove different. The emergence of autonomous or semi-autonomous AI agents raises a much more profound question than how banks use AI i

When SAP announced its expanded partnership with Anthropic at Sapphire 2026, the immediate reaction across the industry was predictable. Most observers interpreted the announcement as another example of generative AI being integrated into enterprise software platforms. But reducing the partnership to an “AI-enabled ERP” story misses the much larger structural transition now unfolding across the enterprise technology landscape. What SAP revealed is not simply the evolution of

For nearly three years, the AI race was framed primarily as a competition between models. Who had the best benchmark scores? Who released the most capable chatbot? Who raised the most capital? Who secured the largest GPU clusters? But the latest moves from OpenAI and Anthropic suggest something much deeper is now underway. The frontier AI battle is no longer only about models. It is becoming a battle for control of the enterprise operating layer. Recent reports indicate that

The dominant narrative surrounding technology layoffs is deceptively simple: AI is replacing workers. But reality may be more structurally complex. A growing number of signals suggest that some layoffs may not reflect successful AI-driven productivity gains at all. Instead, they may reflect a transitional economic shock caused by the enormous costs of deploying AI systems before organisations have fully learned how to extract measurable business value from them. That distinct

Digital Pulse - A digital news strategically decrypted for IT leaders by Eastern Legacy La Banque Postale announced a three-year strategic partnership with Mistral AI to deploy generative AI capabilities across the bank’s operations. The initiative is particularly notable because the AI models and associated infrastructure will be deployed in an on-premise and sovereign environment within the bank’s own infrastructure ecosystem rather than relying exclusively on external hype

Why most IT sourcing strategies fail, and what to do instead? By Eastern Legacy Advisory The uncomfortable truth about sourcing Most organisations still treat sourcing as a procurement exercise. Write the RFP. Run the process.Negotiate the contract. Select the vendor. Then hope it works. But in 2026, this model is no longer just outdated — it is structurally flawed. Because sourcing is no longer about choosing a supplier. It is about orchestrating a complex, multi-layered eco

For decades, the digital economy ran on certainty. Traditional software systems followed fixed rules: if X happens, do Y. Payroll systems calculated salaries. Banking platforms processed payments. ERP tools matched invoices. Behind the scenes, logic was deterministic, repeatable, and auditable. Now a new model is emerging. Artificial intelligence is shifting software development from the classic Software Development Life Cycle (SDLC) toward an AI Development Life Cycle (AIDLC