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New research from Confluent sees IT leaders share their biggest AI implementation challenges

12th September 2024 - Skills shortages are the #1 challenge facing IT leaders looking to implement artificial intelligence in 2024. That's according to research from Confluent, released ahead of this year's BigData LDN event. The research, which surveyed over 500 UK IT leaders, explores the top challenges facing IT departments when it comes to adopting and implementing AI.

How GenAI early adopters gain a competitive advantage in analytics

With generative AI, you have the opportunity to deliver a data strategy that helps business people answer their most pressing data questions—providing unprecedented value to your internal teams, partners, and customers. Hype around GenAI has overwhelmed people with too many use cases and too little focus on achievable value. That’s why we sponsored a first-of-its-kind survey with MIT SMR Connections, asking 1k global data and business leaders questions.

The Secret to Smarter Development with AI and Streamlined Shift Left

Shifting left to put more on developers? They you have to find the right balance between automation and simplicity. Otherwise, you'll end up with complexity that slows everything down instead of speeding it up. @David Morgenthaler says tools like static analysis and AI-driven tests are shaping the future of software quality: Watch the latest episode of Test Case Scenario to explore how automation can streamline processes without overcomplicating development. It’s working for @Indeed.

Data Actionability: Boost Productivity with Unravel's New DataOps AI Agent

Right now, 88% of companies surveyed are turning to AI to improve bug-fixing effectiveness. Why? Troubleshooting modern data stacks is typically a toilsome and manual process. The good news – data teams that use DataOps practices and tools will be 10 times more productive (Gartner). With this in mind, Unravel introduces the new DataOps AI Agent. Learn how this new AI agent enables teams to go beyond observing data pipelines and errors to taking immediate action with purpose-built AI and automation.

A New Dawn: Kong Unleashes API Technologies for the AI Era

The main fundamental question of every business today: Are you on the right side of AI? Many businesses and investors are facing the big question: will they get AI-fied and die slowly or will they be propelled by AI and grow faster? Kong API tools and the Konnect API platform will bring our customers on to the right side of AI. Every platform shift from mainframes onward has created demand for more APIs.

AI in Quality Assurance: How AI is Transforming Future of Quality Assurance

‍ ‍John McCarthy, an American computer scientist, stated this belief more than 40 years ago. Surely, his commitment to understanding the human mental process led him to ideate one of the most revolutionary ideas in computer science—artificial Intelligence (AI). Since then, AI has helped us develop software, utilize it to streamline our business offerings and maintain another essential aspect of digital ecosystems—quality assurance.

[WEBINAR] Automating Invoice Payments in Retail with AI-Powered Data Extraction

Join us in this engaging webinar as we examine the role of AI in automating invoice payments within the retail landscape. We will highlight the significance of data extraction technologies and their ability to enhance payment accuracy and speed. Learn about the challenges faced by retailers and how AI solutions can address these issues effectively.

How Developers Can Use Generative AI to Improve Data Quality

It sounds counterintuitive—using a technology that has trust issues to create more trustworthy data. But smart engineers can put generative AI to work to improve the quality of their data, allowing them to build more accurate and trustworthy AI-powered applications.

Enhancing AI Customer Experience: A Practical Guide

Organizations are harnessing the power of AI to revolutionize products and services across industries. But AI-powered solutions have been getting more sophisticated. We need to redesign and amend our approach to understanding how customers experience these solutions. Unlike traditional products, AI solutions are dynamic, continuously learning and adapting. Traditional metrics may fall short of capturing the nuances of how users interact with AI.