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.

The Do’s and Don’ts of Data Monetization

In this contributed article, Dan Lynn, Senior Vice President of Product at Crux, believes as others have pointed out, data may be the new oil in the sense that it’s a valuable commodity that has fueled economic growth in the 21st century. But unlike dwindling oil stocks, the amount of data is only growing, and it’s reusable. So if you’re considering a data monetization program, keep these do’s and don’ts in mind and reuse your organization’s valuable data to generate even more value.

How ML is Used to Reveal Hidden Savings in Your Cloud Infra 

In this contributed article, Maxim Melamedov, CEO and co-founder of Zesty, explores the cost-savings potential behind leveraging AI/ML in the cloud. By implementing tools capable of real-time decision making and analysis, companies can truly unlock the promise of the cloud.

What Does Real-time Really Mean In Data Analytics?

In this contributed article, Paige Roberts, Open Source Relations Manager for Vertica by OpenText, works to demystify real-time data analytics: understanding definitions, categories, and strategies for unlocking value in the data-driven era.

Data Observability, Essential for your Modern Data Stack

In this contributed article, Mayank Mehra, head of product management at Modak, shares the importance of incorporating effective data observability practices to equip data and analytics leaders with essential insights into the health of their data stacks. Mayank also explains why this is becoming increasingly paramount, given the current trend towards modern, complex, and distributed data infrastructures.

Will Generative AI Change ‘The Way We Work’?

In this contributed article, Neelesh Kripalani, Chief Technology Officer, Clover Infotech, discusses how generative AI is rapidly transforming the way we live and work. It has already become a vital tool for many organizations, and its impact is expected to grow exponentially in the coming years. The article offers five predictions on how generative AI will change the way businesses work.

Empowering Agents, Delighting Customers: The Role of Smart Bots in Elevating Customer Support

In this contributed article, Nate MacLeitch, Founder and CEO of QuickBlox, discusses how businesses can use generative AI to enhance their customer service capabilities while working in tandem with human agents, rather than replacing them.