Today, Artificial Intelligence (AI) is at the top of every technology leader’s mind. What technologies should you incorporate? Who should you partner with to get the most out of AI investments? How best to implement AI within the workplace? To answer these questions, we first need a better understanding of how we got here.

Interest in generative AI has skyrocketed since the release of tools like ChatGPT, Google Gemini, Microsoft Copilot and others. Along with the hype comes concerns about privacy, personal identifiable information (PII), security and accuracy. Organizations are treading cautiously with generative AI tools despite seeing them as a game changer. Many seek the “sweet spot” – enabling benefits right now while identifying more strategic future uses, all without compromising security.

Interest in generative AI has skyrocketed since the release of tools like ChatGPT, Google Gemini, Microsoft Copilot and others. Along with the hype comes concerns about privacy, personal identifiable information (PII), security and accuracy. Organizations are treading cautiously with generative AI tools despite seeing them as a game changer. Many seek the “sweet spot” – enabling benefits right now while identifying more strategic future uses, all without compromising security.

Would that make a difference? Of course it would!

Generative AI and Large Language Models (LLMs) are the new revolution of Artificial Intelligence, bringing the world capabilities that we could only dream about less than two years ago. Unlike previous milestones, such as Deep Learning, in the current AI revolution, everything is happening faster than ever before. Many feel that the train is about to leave the station, and since we are talking about bullet trains – every day matters.

Artificial intelligence (AI) is the next significant technological frontier, poised to revolutionize the tech sector, particularly through its massive impact on cloud infrastructures. By 2024, this transformation is expected to be as widespread as managed Kubernetes services, with an estimated 70% of organizations utilizing managed AI services in their cloud setups.

In the rapidly evolving landscape of cybersecurity, AI-powered attackers are becoming increasingly sophisticated. To counter these threats, organizations must adopt advanced security technologies that leverage AI technology as part of a multi-layered approach to security.

Unplanned downtime can cost large enterprises almost $1.5 million per hour, according to a recent survey by Enterprise Management Associates. AIOps offers a solution. With an effective AIOps platform in place, you can decrease the frequency and cost of outages by 30% and reduce their duration to under an hour. AIOps platforms apply AI and machine learning to complex IT data to enhance and automate IT operations.

Cisco AI Assistant has been integrated into Cisco AppDynamics allowing IT, DevOps, and SRE teams to streamline operations and decision-making processes via the power of intelligent, cross-domain guidance and actionable insights. Reading documentation is great. Having domain expertise, even better. But having an AI assistant to support you in completing your job efficiently and effectively is the best of all worlds.