In recent years, artificial intelligence has gradually transformed from an emerging technology to a necessity. The focus has shifted to AI transformation to find solutions to larger enterprise problems. Although AI is a great enabler, time for scientific projects and proof-of-concepts is quickly running out. In 2022, AI businesses are expected to grow in size, strategic importance, and mission criticality, with an emphasis on long-term scalability. In a recent Institute of Electrical and Electronics Engineers study titled "The Most Important Technologies of 2022," 95% of chief information officers, chief technology officers, and technology leaders believed that artificial intelligence will be It is a major driver of innovation in almost every industry sector.
Most CIOs will find this difficult to handle. Outside of the tech giants, many commercial IT companies are still learning about artificial intelligence. Because AI has such broad applications, one of the main issues facing CIOs is ensuring that their investments are flowing toward use cases that will generate the highest return on investment.
Artificial Intelligence Trends Worth Watching
Against this backdrop, leaders should pay close attention to several trends in artificial intelligence this year. The details are as follows:
The battle for data is the primary issue
Most companies are still in the early stages of artificial intelligence development. These companies must build cutting-edge databases. Most AI models are consumers of massive amounts of data, so enterprises must develop adaptable databases that can scale to accommodate thousands of data sources.
Such models can integrate structured and unstructured data and deliver it to trusted and meaningful data scientists. For more scalable data, extraction, transformation, and loading of traditional data warehouse technologies and relational stores must be supplemented, and in many cases, data streaming must be provided for real-time processing.
Automated process discoveries facilitate the work of robotic process automation
The world will become a more orderly place. Using modern process discovery technology, business leaders may see automation potential within their enterprises. These technologies will provide process-related insights not available through other methods, even if they are not solely focused on the automation landscape. Process mining, task mining, and emerging conversation mining technologies facilitate lean development and provide companies with more autonomous ways to build robotic process automation pipelines. Future advances in these technologies will significantly increase the use of intelligent automation.
Artificial Intelligence Makes Effective Supply Chains Possible
In the future, smart supply chain applications should become the norm, not the exception. From supply and demand forecasting to digital manufacturing and logistics, supply chains need to constantly change, need AI support, and most importantly, be future-proof.
Talent shortage threatens progress
Given the rapid development of the artificial intelligence market, effective people management has become a key differentiator for commercial IT companies. This must include best-in-class recruitment and retention efforts to support a culture of inclusion and lifelong learning. The market has never been more competitive for those with AI skills, and this trend is expected to continue for several years. Therefore, strategic alliances are needed in all types of businesses and industries.
Artificial Intelligence Transforms IT Productivity
Future IT environments will be too powerful and complex for human technology professionals to handle alone. The management of contemporary systems created by CIOs will be another area where AI deployment will rise. People can't just run these systems. AI will enable the observability, intervention and in-depth analysis these systems require.
Given the growing interest in generative artificial intelligence, look forward to business help with application development. In 2022, CIOs will also assess the profound impact of AI on developer productivity within engineering departments. Despite significant recent progress, there has been a long history of research in this area.
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