The 25 disruptive technologies to watch on the Gartner, Inc. Hype Cycle for Emerging Technologies, 2024 fall into four key areas: autonomous AI, developer productivity, total experience, and human-centric security and privacy programs.

Gartner recommends that when developing GenAI-enabled products and services, you:

• Create a plan to deploy and test
• Focus first on the most prevalent use cases — those that are already delivering real value to users
• Draw an investment roadmap that prioritizes opportunities
• Strive to create a competitive edge
• Hold off on long-range future GenAI technology investments

Innovations in and around generative AI dominate and have transformative impact.

The 2023 Gartner Hype Cycle™ for Artificial Intelligence (AI) identifies innovations and techniques that offer significant and even transformational benefits while also addressing the limitations and risks of fallible systems. AI strategies should consider which offer the most credible cases for investment. 

“The AI Hype Cycle has many innovations that deserve particular attention within the two-to-five-year period to mainstream adoption that include generative AI and decision intelligence,” says Gartner Director Analyst Afraz Jaffri. “Early adoption of these innovations will lead to significant competitive advantage and ease the problems associated with utilizing AI models within business processes.”

Generative AI isn’t just a technology or a business case — it is a key part of a society in which people and machines work together.

Generative AI is a type of AI (such as ChatGPT) that can generate new forms of creative content, such as audio, code, images, text, simulations and videos.

Generative AI can learn from existing artifacts to generate new, realistic artifacts (at scale) that reflect the characteristics of the training data but don’t repeat it. It can produce a variety of novel content, such as images, video, music, speech, text, software code and product designs.  

Generative AI uses a number of techniques that continue to evolve. Foremost are AI foundation models, which are trained on a broad set of unlabeled data that can be used for different tasks, with additional fine-tuning. Complex math and enormous computing power are required to create these trained models, but they are, in essence, prediction algorithms.

CIOs: Have you started deploying AI technologies in your organization? Use these five points about AI to drive and deliver successful AI initiatives. 

Even before ChatGPT, one-third of CIOs say their organization had already deployed artificial intelligence (AI) technologies, and 15% more believe they will deploy AI within the next year, according to the 2023 Gartner CIO and Technology Executive Survey. But deciding how best to proceed means factoring AI into business value, risk, talent and investment priorities.