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The transformative potential of artificial intelligence (AI) in marketing is no longer a futuristic fantasy; it’s rapidly becoming a tangible reality. But while many organizations focus on AI’s cost-saving potential, true value lies in its ability to amplify the human element, creating a network effect that elevates both employee and customer experiences. This isn’t about replacing humans with machines. It’s about empowering teams to work smarter, faster, and with greater impact. In this article, we’ll explore how marketing leaders can leverage AI’s network effect to achieve not just one or two, but *all three* desirable outcomes: cheaper, faster, *and* better results. We’ll delve into the insights shared by Jay Pattisall, a leading voice in the MarTech space, to understand the practical implications of this powerful concept.
Agility requires us to constantly evaluate how technology like AI reshapes the relationships between brands and consumers—sometimes for better, sometimes for far more complex. The advertising landscape is shifting under our feet, with new rules, new tech, and frankly, a lot of new guesswork.
Today we’re going to talk about how Deep Learning and AI are impacting advertising effectiveness, personalization, and the future of advertising—with or without cookies.
To help me discuss this topic, I’d like to welcome Jaysen Gillespie, VP, Global Head of Analytics and Product Marketing at RTB House.
Marketing operations are evolving rapidly with the advent of Agentic AI. This article presents expert insights on how marketers can harness this technology to streamline processes and boost efficiency. From automating routine tasks to enhancing customer engagement, discover practical ways to integrate AI into your marketing strategy.
The era of generative AI has been explosive—but unpredictable. That’s fine for brainstorming or content creation. But when lives, money, or compliance are on the line, unpredictability becomes a liability. That’s why Peter van der Putten, Director of the AI Lab and Lead Scientist at Pega, is focused on a new frontier: predictable, governed AI agents that can innovate and stay within the lines.
UX has long been perceived as a deliberate craft—methodical research, slow testing, and incremental refinements. But now, AI is putting that timeline under pressure. As companies strive for faster, more efficient customer experiences, AI offers speed—but not necessarily strategy.
This recap of PegaWorld 2025 was originally published in CMSWire. From technical debt to guardrails, Pega aimed to show at its conference how to bring agentic AI into reality — not just theory. Here’s how they did.
Marketing teams are being stretched, restructured, and reimagined—all while trying to deliver more impact with fewer resources. And in a job market clouded by uncertainty, Sue Keith has become a consistent voice of clarity. As Corporate Vice President at Landrum Talent Solutions, Keith leads the firm’s national marketing recruiting practice and offers quarterly updates on how the landscape is shifting.
This article was written by Greg Kihlström for CustomerThink. Generative AI has generated plenty of attention and hype, though its ability to create
text, images, and software have primarily taken the spotlight, leaving
video as an afterthought.
We’ve spent the last five years feeding marketing algorithms every click, demographic, and behavioral data point available—and yet conversion rates remain stuck in the low single digits. Why? According to Joshua Goldberg, EVP of Strategy at Zenapse, it’s because most marketing artificial intelligence (AI) is training on the wrong thing. Behavior is useful. Demographics are fine. But emotion? That’s where the real leverage is.
When the founder of Reebok partners with the builder of an AI-powered shoe startup, it’s not just a branding story—it’s a signal that the industry is about to change. Again.
