AI: improving the future of digital transformation Business News

Digital transformation is no longer an inner tactic used to reform an organization’s operations; it is now a necessary business sought after by CIOs and IT managers. Recent developments have pushed organizations to embrace digitization, causing the fourth industrial revolution to become widespread and technologies such as artificial intelligence.

Although, according to Gartner, only 53% of AI projects move from prototype to production, companies cannot ignore the benefits of successful AI implementation. Enhanced AI solutions like Artificial Intelligence of Objects (AIoT), Conversational AI and Machine Learning (ML) are improving the future of digital transformation and providing more innovative ways than ever to address challenges commercial.

AI: an end-to-end platform that drives your digital transformation

Today’s AI solutions can be customized to meet the unique challenges of a business. But are these abilities being used to their full advantage? To adopt AI at scale, organizations should consider implementing these five AI-powered tech trends that are shaping the future of digital transformation.

Business journalist Virtusa 1

Senthilkumar Ravindran, Executive Vice President and Head of Digital and Cloud Transformation – Virtusa EMEA

AIoT, an advanced hybrid of AI and the Internet of Things, is giving a new twist to the way we look at ML. AI and IoT offer niche capabilities that can both be leveraged when implemented together. The deployment of AIoT solutions requires expertise in both areas; therefore, companies must collaborate with agile partners to view once-separate solutions as a singular unit.

AIoT involves intelligent, optimized, real-time orchestration of physical and digital processes in process control systems (PCS), manufacturing execution systems (MES), enterprise resource planning (ERP) and other technologies to increase overall efficiency.

Some AIoT use cases include self-optimizing supply chain systems, cyber-physical systems, and automated regulatory inspections that leverage drone technologies.

Business Journalist – Virtusa video 2

Sanjeev Gulati, Executive Vice President and Head of Digital – Virtusa Americas

According to Markets and markets, the global conversational AI market size is expected to reach $ 15.7 billion (£ 11.3 billion) by 2025. The chatbot market is also expected to grow exponentially, withBusiness thread projecting it is expected to reach $ 5,638.64 million (£ 4,039.10 million) by 2023.

Interactive Voice Response (IVR) is an AI solution that helps drive market growth because it can work with large amounts of data. By leveraging conversational AI, businesses can improve user experience, IVR containment, and omnichannel collaboration to maximize cross-sell and up-sell opportunities. Conversational AI will also enable advancements in platform governance, microservices and application programming interfaces (APIs), natural language processing (NLP) optimization, and bot repositories.

Businesses now have full platform ownership with conversational AI solutions. This means that they can resolve issues that arise from a lack of context in a conversation. Conversational AI also creates communication between once disparate applications, leading to a streamlined escalation process by deciding what is automatable and what isn’t.

Low-code no-code in AI

The growing need for technologies to accelerate and democratize the data science process has paved the way for advanced AI applications.

Codeless AI creates democratization, giving business, management and operations teams advanced analytics capabilities without requiring specialized data science skills. Many of these codeless platforms are easy-to-use visual drag-and-drop tools. One of the challenges businesses face is that the complex workflows currently used by most AI / ML models will not allow them to implement solutions without code. If businesses want to benefit from these tools, they will need to migrate to a more sophisticated eAutoML platform that enables true end-to-end automation without code.

Machine learning (ML) and hyper-automation

Hyper-automation works in harmony with AI / ML technologies and takes advantage of digital process automation (DPA) and intelligent process automation (IPA). It can also automate rigid, unstructured processes that in the past were not automatable.

For hyper-automation initiatives to be successful, businesses cannot rely on static software. Automated business processes must therefore adapt and respond to changing circumstances. Almost all of the major process automation platforms are integrated with aspects of AI / ML to enable responsiveness. While the Covid-19 pandemic has resulted in an increased need for learning solutions, these enhanced capabilities will continue to be used and enhanced long after its end.

AI in the cloud

AI has become integrated into all aspects of human life. The next big opportunity in digital transformation is the integration of the cloud with artificial intelligence …

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This notice was published: 2021-07-01 15:21:32

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