According to a new report, artificial intelligence (AI) is a foundational force for digital business. The last 10 years are a breakthrough step in AIs development, driven by the convergence of factors, including the rise of massive data, advances in compute infrastructure, new machine learning techniques, the emergence of cloud computing, and the vibrant open-source ecosystem.
There are five factors Gartner considers to be the most significant in determining AI''s future future. Technology leaders must exploit these emerging AI trends in order to democratize and foster its responsible use, adapt composite methods, leverage AI for real-time analytics at the edge, and exploit its generative powers.
Democratized AI will make AI more accessible to a broad spectrum of users. From discovering unexpected opportunities by identifying hidden trends in large datasets to augmenting and assisting workers in their development, democratized AI will touch every aspect of our lives.
Composite AI is able to utilize a variety of AI techniques that meet your specific applications. It brings the power of AI to a wider set of use cases and users, thus it gain its following benefits: it increases their versatility, efficiency, and adaptability.
Edge AI will be able to process digital moments by harnessing AI for real-time analytics closer to data sources. Gartner predicts that by 2025, more than half of all data analysis by deep neural networks will be at the edge, up from less than 10% in 2021.
Responsible AI is an umbrella term for making appropriate business and ethical decisions when it comes to AI. It requires consideration of business and societal value, risk, trust, transparency, fairness, bias mitigation, explainability, accountability, safety, privacy, and regulatory compliance. Responsible AI is becoming increasingly important amidst growing regulatory oversight, consumer expectations, and emerging sustainability goals.
Generative AI is used in order to enliven new artifacts and to develop innovative services. Increasingly, generative AI has focused on producing media content such as photorealistic images of people and things, but it may also be used for code generation, using synthetic tabular data and designing pharmaceuticals and materials with specific properties.
Read the full report by Gartner.