AI / ML
for data analysis , process automation , and decision-making , these platforms are enabling organisations to become more efficient , innovative , and customercentric . As the technology continues to evolve , we can expect AI platforms to play an increasingly central role in shaping the future of business across all industries .
However , success with AI platforms requires more than just implementing the technology . It demands a strategic approach to data management , a commitment to ethical AI practices , and a willingness to reimagine business models and processes . Organisations that can navigate these challenges and harness the full potential of AI platforms will be well-positioned to thrive in the increasingly AI-driven business landscape of the future .
As AI technology continues to evolve , we can expect AI platforms to become even more sophisticated and integral to business operations . Dr . Kremer predicts : “ AI platforms will support faster prototyping , allowing businesses to quickly validate use cases without extensive training periods . Often , AI products are combinations of multiple AI models , and these platforms enable quick assembly of such solutions .”
Van der Putten , meanwhile , anticipates a convergence of different AI technologies : “ In future , we can expect that generative AI will be combined more with other forms of AI such as process mining and automated decisioning . An increased focus on actionability and scaling means AI and automation will converge more and more .”
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