AI automation to drive the next wave of digital innovation

Pressure is on IT operations to become more efficient at processing large volumes of data and complex infrastructures as digital transformation accelerates. AI, especially GenAI, will turn out to be one of core enablers in enhancing IT operations.

DQI Bureau
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Ritsuko Hidaka.

The convergence of cloud computing and artificial intelligence (AI) across the digital world pushes us into a new age of innovation. In the process of migration of infrastructure and applications to the cloud, companies are applying AI to automate processes, derive actionable insights, and set a new definition of operational efficiency. Statista survey projects that the AI market is expected to reach USD 305.90 billion by 2024 and USD 738.80 billion by 2030.


The pressure is on for IT operations to become more efficient at processing large volumes of data and increasingly complex infrastructures as digital transformation accelerates. AI, especially generative AI, will turn out to be one of the core enablers in enhancing IT operations. In a research conducted by ESG, 85% of organisations reported using AI or having plans to use it in a variety of functional areas, one of which are IT operations. AI-driven automation enables workforce efficiency by reducing manual effort and human error, thereby making real-time decisions possible.

AI in IT ops can be divided into three categories: Causal AI, for analysis of real-time data for precise issue prevention, root-cause analysis, and risk remediation. Generative AI, generates content from large datasets for reworked productivity and customer experiences, and third is Predictive AI, underlying analysis of patterns to anticipate future behaviours for operational foresight and decision-making. 

With increased AI in digital transformation, it is going to radically reshape business landscapes in the areas of hyper-personalisation, streamlined operations, pace in software development, enhanced collaboration, and eco-friendly solutions. 


Broader impact of AI on business processes

AI's potential goes beyond IT operations, process automation, data analytics, individual customer experience, and AI-powered customer support. Of late, Industry 4.0 is about evolving tools such as AI chatbots and computer vision, redefining customer engagement and operational workflows across industry verticals.

AI in production: According to the extensive ESG survey data, AI is becoming mainstream. First on the list is generative AI, as it happens to be the most popular and versatile—60% of organisations were reported to use generative AI in production. Growth was also indicated in causal and predictive AI. Even amidst benefits, the challenges most posed revolved around issues regarding security vulnerabilities and log management complexities. 


Generative AI in IT operations: Generative AI is also poised to revolutionise IT operations—34% of organisations forecast that IT metrics will significantly improve within two years. It automates tasks, and incident response optimisation, and organises resource allocation, hence, facilitating operational excellence across organisations.

Process automation: AI-driven RPA makes it possible with the help of bots that automate repetitive tasks and help reduce manual workload, enabling human resources to work on strategic initiatives. This shift enhances efficiency and reduces errors—for smoother, more productive operations.

Data analytics and customer experience: AI leverages large volumes of data, especially in the case of predictive analytics and recommendation engines that optimize customer experiences by harnessing structured and unstructured data. 


AI-driven customer support: AI chatbots, powered by natural language processing (NLP) and machine learning (ML), engage customers to increase support and satisfaction. Such intelligent assistants would deal with routine inquiries, relieving human agents of the same to handle more complex tasks.

Generative AI in content creation: Generative AI tools, such as ChatGPT, make content creation more productive and creative. Businesses can apply this in several ways, including auto-generation of content and conversation intelligence, thereby enabling them to drive their digital transformation more effectively.

Computer vision: The applications of AI-inclusive computer vision spans healthcare and financial institutions to BFSI among others. These technologies automate tasks related to visual perception, such as risk assessments and quality control, thereby enhancing accuracy and efficiency.


Looking ahead

Looking ahead, the potential for AI to drive digital transformation is unlimited, promising a world of enhanced efficiency, innovation, and success. The power mix of AI and cloud computing is unleashing digital innovation on never-before-seen levels, which can automate organisational process execution, provide insights, and enhance customer experiences. 

Companies that embrace these advancements will be able to navigate smoothly the complexities of digital transformation by setting new benchmarks in their industries, shaping the future of technology and business. The convergence of AI and the cloud is not a strategic advantage but a necessity if one wants to remain competitive and relevant in today's digital age.

---- Ritsuko Hidaka, Head of JDU, Fujitsu.

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