Borderless Data – Acting Locally, Thinking Globally

In this contributed article, Alasdair Anderson, VP EMEA, Protegrity, discusses the challenges facing data and technology leaders and role automation plays in ensuring compliance. Giving organizations the speed and adaptability so vital in today’s digital economy.

Unleashing the Power of AI in Digital Advertising: A Data-Driven and Strategic Revolution

In this contributed article, Gruia Pitigoi-Aron, Senior Vice President of Product for The Trade Desk, discusses how in today’s rapidly evolving digital landscape, the effectiveness of advertising hinges on the ability to deliver relevant and impactful messages to the right audience at the right time. As the world becomes increasingly data-driven, harnessing the power of AI in digital advertising technology (ad tech) has emerged as a game-changer. The article focuses on the transformative capabilities of AI in digital advertising and how it’s revolutionizing the industry by enabling a more data-driven and strategic approach to media buying.

Three Considerations Before Adding Generative AI Capabilities to Your Security Stack 

In this contributed article, Ashley Leonard, president and CEO of Syxsense, reflects on some of the most pertinent issues affecting the adoption of generative AI in security. These include the question of who owns the AI output, how to conduct quality assurance to mitigate unwanted results, and companies’ overall preparedness to manage workforce displacement. The article also pulls real-life scenarios from across the industry and provide considerations to help businesses navigate generative AI adoption without missing out on the technology altogether.

Keeping a Level Head during AI Implementation

In this contributed article, Frank Laura, Chief Technology Officer at EngageSmart (NYSE: ESMT), discusses why CIOs and CTOs need to bring AI into businesses safely, securely, and legally. AI will enable CIOs and their teams to shift focus away from tactical and/or repetitive work towards creating innovative solutions for their teams and customers.

Seven Reasons why Data Security Needs AI

Today data holds the key to business success. Enterprises are embracing the power of data to improve marketing effectiveness, identify new revenue opportunities, personalize customer experiences, and improve operational efficiency.   However, the increasing complexity of the data landscape is making it a huge challenge to provide users and applications with fast access required, while ensuring regulatory compliance. In this contributed article, Noam Biran, Velotix VP Product, offers seven trends that suggest why more intelligent and automated solutions are needed to enable data governance.

Unleashing the Power of AI in Paid Search Marketing: Insights from Industry Expert

In this contributed article, Amy McClain, Group Director, Performance Media at BCM, delves into the ways AI is transforming paid search marketing, from automating manual tasks and improving targeting capabilities to optimizing bidding strategies for better performance. She also highlights the benefits of AI-powered paid search marketing, including increased cost savings, enhanced conversion rates, and more efficient campaign management.

The Three Greatest Areas of Impact for AI in Automation

In this contributed article, Jakob Freund, Co-Founder and CEO at Camunda, explores three different types of AI that he predicts will dominate industries as organizations work to ensure business processes are streamlined and working as intended. These three AI buckets include predictive decision-making, generative processes, and assistive tools.

How Enterprises Can Rise Above Data Gravity for a Better Life in the Cloud

In this contributed article, Jim Liddle, Chief Innovation Officer at Nasuni, describes how having file data stored in the cloud and workloads on-premises can result in serious performance issues because remote access and data consolidation don’t play well together. In fact, the combination can create “data gravity” that complicates and slows the movement of data, worsened by the latency that often accompanies remote access. The resulting lack of speed and flexibility presents significant issues when decisions must be made in seconds in order to prevent potential loss or generate revenue to the tune of millions of dollars.

Regulate the Use Cases—Not AI Itself

In this contributed article, CF Su, VP of ML, Hyperscience, agrees that regulation is needed, but as opposed to sweeping oversight, he supports regulating specific uses of AI, such as licensing the business applications of AI models rather than requiring licenses for creating them. This targeted, tactical government oversight will close the trust gap between the public and AI, which is his #1 concern currently facing the technology’s adoption.

Who’s to Blame for the Data Capability Wall?

In this contributed article, Cameron Benoit, Director of Solution Consulting, Adverity, explores why data technology solutions keep stalling before takeoff. With cloud innovation making it easier
than ever to amass vast collections of specialist tools, businesses theoretically shouldn’t be
short on any capabilities. The problem is, prioritizing enticing features over functionality is
creating data infrastructure that’s flawed at best or unfit for purpose at worst. To avoid
running into capability walls, careful tech selection and stack building is key.