By Vishal Muktewar - March 16, 2022 4 Mins Read
AI continues to gain traction as organizations, after demonstrating its benefits during the pandemic. As enterprises accelerated their digital transformation initiatives, they heavily invested in and integrated the technology across their platforms
It is no secret that Artificial Intelligence (AI) and Machine Learning (ML) are here to stay. With the rapid acceleration in digital transformation initiatives and gathering insights from complex data, industry experts predict that organizations will continue to invest heavily in AI and ML technology. As per a 2022 report from Statista, the global market is expected to grow exponentially in the coming years, reaching around US $126 billion by 2025.
Across different industries, organizations are rolling out successful proofs-of-concept and have been successful in deploying AI in production. That’s not all; some organizations have successfully operationalized their AI as well as machine learning strategies, with projects expanding across multiple industries with overall best practices as well as pipelines.
Given AI’s significant influence on today’s enterprise landscape, enterprise leaders should always keep up with the latest trends in AI.
In 2021, organizations came to the realization that they will fail to scale their AI projects if they do not begin to start including non-experts in the project. Hence, they have begun to enlist people from roles such as project management and leads, risk managers, subject matter experts (SMEs), hardcore data science, internal think tanks, and more. Also, with the increase in adoption and scale, business stakeholders demand more visibility into the initiatives and even review and sign-offs at key steps.
While there is no doubt that data scientists and other data teams play a critical role in organizational data and AI transformation, they are not enough to make a significant difference on their own. That’s why enlisting the help of analytics experts, business users and AI experts is critical for the success of the project.
Also Read: How AI Will Drive the Future of Work
Organizations, after succeeding with their initial proof of concept, advance towards building AI centers of excellence to operationalize the technology as well as develop expertise, talent, and best practices. But, some organizations begin to break down these even before they reach a certain level of maturity. This results in weakening the impact as well as lessening the ability of the organization to iterate as well as successfully duplicate projects across various business departments.
In 2022 and beyond, organizations should wait till their AI initiatives reach a certain level of maturity and are able to scale effectively before breaking up their centers of excellence and unifying AI strategies across various departments.
When organizations first begin to utilize their AI capabilities, they watch for individual steps in business processes where AI can have the most impact. They fragment the process into individual pieces, digitize each of them, and later introduce AI to make it efficient. However, what CIOs should understand is that at the end of the day, the process itself is the same. Each of its parts is made to be better, cheaper and faster. This does not mean that AI does not have any potential benefits. With the predictive powers available with AI, organizations have the ability to entirely restructure their processes. After applying AI, they can completely re-engineer their end-to-end value chain.
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Vishal Muktewar is a Senior Correspondent at On Dot Media. He reports news that focuses on the latest trends and innovations happening in the B2B industry. An IT engineer by profession, Vishal has worked at Insights Success before joining Ondot. His love for stories has driven him to take up a career in enterprise journalism. He effectively uses his knowledge of technology and flair for writing, for crafting features, articles and interactions for technology enterprise media platforms.
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