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Artificial intelligence (AI) is a foundational catalyst for digital business, according to a new report by Gartner. The last 10 years represent a breakthrough period in AI’s development, spurred by the convergence of factors including the rise of big data, advancements in compute infrastructure, new machine learning techniques, the emergence of cloud computing and the vibrant open-source ecosystem.
In evaluating the trends that will shape the future of AI in the enterprise, there are five trends that Gartner sees as being the most significant. Technology leaders must harness these emerging AI trends to democratize and foster its responsible use, adapt composite techniques, leverage AI for real-time analytics at the edge and exploit its generative powers.
Democratized AI will make AI accessible to a wide set of users. From uncovering unexpected opportunities by identifying trends hidden in large datasets, to augmenting and assisting workers in complementing 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 the right use cases. It brings the power of AI to a broader set of use cases and users, and it is gaining popularity because it improves AI’s versatility, efficiency and adaptability.
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Edge AI will enable digital moments by harnessing AI for real-time analytics closer to data sources. Gartner predicts that by 2025, more than 50% of all data analysis by deep neural networks will occur at the edge, up from less than 10% in 2021.
Responsible AI is an umbrella term for making appropriate business and ethical choices when adopting AI. It requires considering business and societal value, risk, trust, transparency, fairness, bias mitigation, explainability, accountability, safety, privacy and regulatory compliance. Responsible AI is increasingly important amidst growing regulatory oversight, consumer expectations and emerging sustainability goals.
Generative AI is the use of AI to generate new artifacts and create groundbreaking products. To date, generative AI efforts have focused on creating media content such as photorealistic images of people and things, but it can also be used for code generation, creating synthetic tabular data and designing pharmaceuticals and materials with specific properties.
Read the full report by Gartner.
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