Report: 5 key trends for AI’s future

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According to a new report from Gartner, Artificial Intelligence (AI) is a key catalyst for digital business. The last 10 years represent a progressive period in the development of AI, driven by the integration of factors including the rise of big data, advances in compute infrastructure, new machine learning technologies, the emergence of cloud computing and the vibrant open-source ecosystem.

To evaluate the trends that shape the future of AI in the enterprise, there are five trends that Gartner sees as the most significant. Technology leaders need to democratize these emerging AI trends and promote their responsible use, adapt to combined technologies, leverage AI for real-time analytics on the edge, and harness its generative powers.

Democratized AI will make AI accessible to a wider group of users. From unraveling unexpected opportunities by identifying trends hidden in large datasets, to supplementing and helping workers with their knowledge, democratized AI will touch every aspect of our lives.

Composite AI is the ability to deploy a variety of AI techniques aligned with appropriate use cases. It brings the power of AI to a wide range of use cases and users and is gaining popularity as it improves the versatility, functionality and adaptability of AI.

Edge AI will enable digital moments using AI for real-time analytics close to data sources. Gartner predicts that by 2025, more than 50% of all data analysis by Deep Neural Networks will be on the edge, down from 10% in 2021.

Responsible AI is an umbrella term for making the right business and ethical choices when adopting AI. It requires consideration of business and social values, risk, trust, transparency, fairness, bias, clarity, accountability, safety, privacy and regulatory compliance. Responsible AI is increasingly important amid growing regulatory oversight, consumer expectations and emerging sustainability goals.

Generative AI is the use of AI to create new artifacts and groundbreaking products. To date, Generative AI efforts have focused on creating media content such as photorealistic images of people and objects, but can also be used to create code generation, synthetic tabular data, and design content with pharmaceuticals and specific properties.

Read the full report by Gartner.

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