EN Archives - Page 3 of 66

Scaling Data Collaboration in the AI Era

Artefact’s new ebook, Scaling Data Collaboration in the AI Era, explores how organizations can unlock greater value by breaking down data silos and enabling seamless collaboration across teams. As AI adoption accelerates, success depends not just on technology, but on the ability to connect data, people, and processes effectively. The ebook highlights how modern approaches to data collaboration empower faster insights, stronger governance, and more impactful AI-driven outcomes, turning data into a true strategic asset.

Exploring the impacts of agentic AI on the relationship with HCPs

Artefact’s new white paper, Exploring the impacts of agentic AI on the relationship with HCPs, shines a light on the healthcare industry at a pivotal moment. Patients today are more digital, autonomous, and informed than ever before. Many consult online platforms and even AI tools before visiting a doctor. At the same time, healthcare professionals (HCPs) are overwhelmed by a flood of content, from scientific updates to promotional campaigns, and struggle to cut through the noise. Traditional engagement models centered on in-person visits and one-size-fits-all communication are no longer sufficient to maintain relevance.

People Analytics Beyond Turnover Prediction: Potential Applications of AI in HR

Human Resources is undergoing a fundamental shift from a reactive cost center to a proactive driver of value. Yet many organizations remain anchored in a minimalist approach to people analytics. While generative AI and autonomous agents are gaining traction across the enterprise, HR’s use of data is still often limited to basic turnover prediction.

The algorithmic evolution: Agentic systems & strategic grounding at Friends of Search 2026 – Part II

Friends of Search 2026 signals the end of rule-based PPC and the rise of AI-driven, conversation-focused search. Success now hinges on grounding AI outputs in high-quality data and embracing flexible, agentic systems. As Asics’ 108% presales lift shows, adaptability and enriched first-party data are the keys to winning in the new search era.

The Friends of Search 2026 manifesto: Navigating SEO in an AI-driven world – Part I

In this article, we break down the top 5 keynotes & insights from Friends of Search 2026, highlighting the most actionable takeaways for navigating the evolving SEO and AI-driven landscape.

From gut feel to algorithmic cities: How AI will decide what Britain builds and whether it works

For decades, placemaking in Britain has been governed as much by judgment as by methodology. Practitioners speak of "character", "vibrancy", and the elusive "feel" of a streetscape; qualities refined through experience, human use, and professional instinct rather than formalised metrics. The accomplished practitioner was often the one who had seen enough places to recognise what worked, even when the causal mechanisms remained partly intangible.

Navigating the new RICS AI standard: What it means for surveyors

AI is reshaping professional practice across the built environment, and the surveying profession is no exception. With the Royal Institution of Chartered Surveyors (RICS) having published its first Responsible Use of Artificial Intelligence in Surveying Practice professional standard (effective from 9 March 2026) the question for many firms is no longer whether to engage with AI, but how to do so in a way that is compliant, considered, and professionally defensible.

Leadership in the age of AI: Authenticity, inclusive tech and sponsorship

In the age of AI, the ultimate competitive advantage isn't technological fluency, it's human connection. Drawing from the recent Women@Artefact panel, this article explores how professionals can become "AI-proof" by leveraging inclusive tech like Fierté AI, freeing up time for strategic thinking, embracing authentic career journeys, and shifting from traditional mentoring to active sponsorship.

The Open-Source Paradox

Red Hat built a $34 billion business on Linux. IBM bought it. What the deal validated was a hypothesis that had held for four decades: that companies extracting enormous value from shared code would, in self-interest, keep funding the projects they depended on. That hypothesis is now under stress. Not because anyone decided to stop funding open source. Because the industry that funded it most — SaaS — is being dismantled by the industry that depends on it most — AI.