Systems | Development | Analytics | API | Testing

Uncertainty is the new norm for today’s brand advertisers and advertising agencies. Google has once again changed its stance on third-party cookies, keeping them for at least the time being. With the future of cookies still uncertain, many advertisers have already been preparing to use alternative targeting strategies, such as first-party data and contextual targeting.

By now, every organization, regardless of industry, has at least explored the use of AI, if not already embraced it. In today’s market, the AI imperative is firmly here, and failing to act quickly could mean getting left behind. But even as adoption soars, struggles remain, and scalability continues to be a major issue. Organizations are quick to adopt AI, but getting it established across the organization brings a unique set of challenges that come into play.

The relentless rise of ChatGPT and other Large Language Models has brought a major breakthrough in the world of artificial intelligence. With key industry players like Meta, Google, Nvidia and Microsoft competing fiercely to dominate this space, it’s likely we’ve only seen the start of the innovation. Several big companies have made their AI Models and platforms available for the public to use and build on.

Artificial intelligence (AI) is kind of a big deal. And when things are a big deal, they're ripe to be exploited. Fortunately, mounting concerns about AI security and privacy are met by plenty of guidance on best practices from the good folks in the open source world. The OWASP AI Security Project has emerged as a crucial initiative, offering developers clear, actionable guidance on designing, creating, testing, and procuring secure and privacy-preserving AI systems.

In 24.2, we introduced our enterprise copilot. Enterprise copilot allows you to upload business documents and collect them in knowledge sets. From there, you can ask questions about information in these documents and receive answers quickly. For instance, an organization with a heavy regulatory burden could upload legislative and operational documents. Then, these employees could get insights from Appian AI Copilot to ensure they adhere to compliance requirements.

Today, we are excited to announce the public preview of Snowflake Cortex Analyst. Cortex Analyst, built using Meta’s Llama and Mistral models, is a fully managed service that provides a conversational interface to interact with structured data in Snowflake. It streamlines the development of intuitive, self-serve analytics applications for business users, while providing industry-leading accuracy.

In today's fast-paced world of media publishing, keeping up with technological advancements and changing consumer preferences is no easy task. Tight budgets, fierce competition and evolving audience behaviors add to the pressure, creating what's often termed the "content crash" — a saturation of content that makes it hard for publishers to stand out. But amidst these challenges, there's a beacon of hope: generative AI.

Ready or not, AI workflow automation is poised to transform business operations from the shop floor to the C-suite in the AI economy. As organizations embrace digital-first initiatives, IT teams will be able to do much more with less. The situation is a byproduct of the generative AI boom. And yet, so many companies have hardly scratched the surface of AI automation’s full potential in their business operations.