The SaaS Panic – When Agents Begin to Bypass the Interface
Something subtle but seismic is happening in enterprise software. For years, SaaS thrived on UX—well-crafted interfaces designed to guide humans through increasingly complex workflows.
Something subtle but seismic is happening in enterprise software. For years, SaaS thrived on UX—well-crafted interfaces designed to guide humans through increasingly complex workflows.
For decades, consulting thrived by delivering polished slide decks filled with frameworks and benchmarks.
Brands have long envied the troves of first‑party data sitting inside retailer systems. The average shopper enrols in roughly 13 loyalty programmes but stays active in barely half of them, so the “relationship” often stops at the cash register.
The Sales and Operations Planning (S&OP) process aims to align sales, operations, and finance departments around an integrated and feasible plan. More than a monthly agenda, S&OP is a continuous cycle that seeks to anticipate the future and prepare the organization to meet it efficiently. Today, Artificial Intelligence (AI) is already a reality in parts of this process — especially in demand planning. But its potential goes further: as we evolve in analytical maturity and in the integration between teams and data, AI can become a central gear for faster, more accurate decisions aligned with business reality.
As the future of advertising rapidly evolves, so too does the way we understand and reach consumers. Google is ushering in a new era of search metrics that deliver more granular, actionable insights for marketers. Two new metrics, User Searches and Ad Opportunities are at the forefront of this transformation, powered by advancements in AI and multimodal search capabilities.
The adoption of AI brings significant ethical considerations and governance challenges that must not be ignored. The way we develop, deploy, and manage AI technologies will fundamentally impact the future of our societies and economies.
The rapid ascent of Generative AI (GenAI), powered by sophisticated Large Language Models (LLMs), has captured global attention, demonstrating remarkable capabilities in content creation, summarization, and interaction. Businesses are actively exploring and integrating these tools to enhance productivity and unlock new avenues for communication. However, focusing solely on GenAI overlooks the next seismic shift in artificial intelligence: Agentic AI.
In today's relentlessly competitive business landscape, agility and informed decision-making are paramount. The ability to swiftly access and leverage an organization's collective intelligence can be the critical differentiator between thriving and merely surviving. Yet, beneath the surface of many enterprises lies a significant, often underestimated drain on productivity and innovation: the pervasive challenge of fragmented and inaccessible knowledge.
At the recent Artefact Data & AI Summit in Dubai, Vincent Luciani, Co-founder and Executive Chairman of Artefact, shared his insights on the evolving landscape of artificial intelligence. This article covers the main points from Vincent’s session, including the commoditization of AI, its impact on the workforce, the associated challenges and opportunities, and strategic recommendations for organizations.
