The rules of the financial industry are being rewritten thanks to AI and generative AI. In their conversation for The Bridge, Artefact’s Joffrey Martinez, Managing Partner & Global Lead for Financial Services, and Alexis Baufine-Ducrocq, Partner & Lead Financial Services, discuss the race to redefine financial performance with AI.
Private equity is entering a new era of accelerated transformation driven by AI. In this conversation for The Bridge, Elina Ashkinazi-Ildis, Partner & Lead Private Equity, and Jérôme Petit, Managing Partner, explore how AI is redefining portfolio value creation, fund operations, and investment strategies.
Artefact’s new ebook, The Agentic AI Advantage in Healthcare: Accelerating Pharma’s HCP-Centric Marketing from Insight to Outcome, demonstrates that agentic AI represents a major step forward in solving these challenges. While traditional generative AI focuses on creating content, agentic AI can take action. It receives goals and constraints, reasons strategically, and executes tasks autonomously within the guardrails of compliance and approved data sources. Agentic AI elevates AI from a productivity tool to a business performance engine.
Over the past decade, sustainability shifted from the periphery of corporate reputation to the core of business performance. Artefact’s new ebook, ESG in Action, How to convert Environmental, Social, and Governance (ESG) data into business intelligence, documents this transition through semi-structured interviews with C-suite leaders from global companies such as Accor, Legrand, Tarkett, Ardian, Heineken, Siplec and Schenker, as well as insights from the OECD and Artefact’s sustainability and data experts.
As enterprises rush to operationalize AI, most discover that their data infrastructure was never designed for autonomous reasoning. Today, up to 80% of AI implementation time is spent on data wrangling and schema alignment, a symptom of infrastructures built for storage, not understanding. Without a foundation that captures relationships and meaning, agents will remain powerful, but blind. With AI agents becoming active participants in enterprise workflows, the nature and scale of data querying are evolving.
Many marketing leaders face the same paradox: despite major investments in Generative AI, the expected impact on costs, speed, and performance isn’t materializing. Why? Because most AI only “thinks”, it doesn’t act. Agentic AI changes that.
For the last 18 months, 'Generative AI' has dominated every C-level strategy session. But what if that's already the old conversation? In the energy and industry sectors, the discussion is rapidly shifting from GenAI to Agentic AI. This isn't just an incremental update; it's a new paradigm, one that moves from simply augmenting tasks to completely reinventing core industrial processes.
When OpenAI announced Atlas, its new ChatGPT-powered browser, it didn’t just launch another product. It opened a door, one that leads into the next era of human-computer interaction, and, inevitably, into a new frontier for advertising.
Most companies are not ready to replace a dashboard era data stack with an AI stack. Salesforce's latest State of Data & Analytics indicates that 84% of data and analytics leaders say their strategies require a complete overhaul before AI ambitions can succeed. Leaders estimate that 26% of their data is untrustworthy, only 43% report formal data governance frameworks, and around 50% are not confident in their ability to generate and deliver timely insights. At the same time 70% believe the most valuable insights are locked in unstructured data. The conclusion is straightforward: the obstacle is not enthusiasm but foundation, and that foundation must change before agentic systems can scale.
