In fact, Gartner expects that by 2023, all personnel hired for AI development and training work will have to demonstrate expertise in responsible AI.ĭata forms the foundation of successful AI initiatives. “Responsible AI helps achieve fairness, even though biases are baked into the data gain trust, although transparency and explainability methods are evolving and ensure regulatory compliance, while grappling with AI’s probabilistic nature.” “Increased trust, transparency, fairness and auditability of AI technologies continues to be of growing importance to a wide range of stakeholders,” said Svetlana Sicular, research vice president at Gartner. Here are the four trends that are driving AI innovation, according to Gartner: This indicates a market trend of end users seeking specific technology capabilities that are often beyond the capabilities of current AI tools.
The AI market remains in an evolutionary state, with a high percentage of AI innovations appearing on the upward-sloping Innovation Trigger (see Figure 1). “Innovations including edge AI, computer vision, decision intelligence and machine learning are all poised to have a transformational impact on the market in coming years.” “AI innovation is happening at a rapid pace, with an above-average number of technologies on the Hype Cycle reaching mainstream adoption within two to five years,” said Shubhangi Vashisth, senior principal research analyst at Gartner. These trends include responsible AI small and wide data approaches operationalization of AI platforms and efficient use of data, model and compute resources. Hype Cycle for Artificial Intelligence, 2021 are driving near-term artificial intelligence (AI) innovation.
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