According to Gartner’s recent Hype Cycle for Artificial Intelligence 2021 report, users are clamoring for more than the technology can currently deliver—but that may be about to change. The firm found that today’s AI hype cycle is more fast-paced, with an above-average number of innovations poised to reach mainstream adoption within the next two to five years.

In addition, Gartner found more trends than usual in the “innovation trigger” phase, the first stage in which technological possibilities begin to take shape. Read on for more on these emerging trends and what they may mean for your business.

Composite AI

Composite AI combines various techniques to build AI solutions that require less data and energy to learn. By incorporating different technologies and approaches, the trend can expand knowledge representations and solve business problems more efficiently. According to Gartner, this approach is ideal for situations where there is not enough data for traditional analysis, but significant human expertise exists.

AI Orchestration and Automation Platform

Also known as AIOAP, companies use this technology to standardize DataOps, ModelOps, MLOps, and deployment pipelines, as well as to implement governance practices. In addition, AIOAP unifies development, delivery, and operational contexts, particularly around reusing components like feature and model stores, monitoring, experiment management, model performance, and lineage tracking.

AI Governance

As we’ve previously discussed here at the APEX of Innovation, there are a number of ethical concerns that come with more widespread AI adoption. As such, it’s no surprise that we are now seeing the emergence of AI governance, the practice of establishing accountability for AI-related risks. According to Gartner, governance efforts should address diversity, trust and transparency, ethics, fairness, and safety. To date, the technology has reached one to five percent of the target audience, but expect these figures to increase as more government regulations emerge to address AI accountability.

Generative AI

This technology applies what it has learned to create new content, including text, images, video, and audio files. Gartner predicts that this trend will disrupt software coding and could automate up to 70 percent of programming work when combined with automation. Key industries include life sciences, healthcare, manufacturing, material science, media, entertainment, automotive, and aerospace and defense.

Human-Centered AI

Also referred to as augmented intelligence, human-centered AI is an approach in which certain tasks are handled by an algorithm while others are done by humans. In some cases, employees may take over a process when the AI has reached the limit of its capabilities. As this technology matures, Gartner believes it can help organizations manage AI risks and be more ethical and efficient with automation.

For more on the above and other trends in the “innovation trigger” phase, check out this recent TechRepublic article.