AI: enhancing the future of digital transformation

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Digital transformation is no longer an inward tactic used to reform an organisation’s operations; it’s now a necessary undertaking sought out by CIOs and IT leaders. Recent developments have pushed organisations to embrace digitisation, causing the fourth industrial revolution and technologies such as artificial intelligence to go mainstream.

Even though, according to Gartner, only 53 per cent of AI projects make it from prototype into production, companies can’t ignore the benefits of successful AI implementation. Enhanced AI solutions such as the artificial intelligence of things (AIoT), conversational AI and machine learning (ML) are improving the future of digital transformation and offer more innovative ways than ever before to address business challenges.

AI: an end-to-end platform scaling your digital transformation

Today’s AI solutions can be customised to address a company’s unique set of challenges. But are these capabilities being used to their full advantage? To adopt AI at scale, organisations should consider implementing these five AI-powered tech trends that are shaping the future of digital transformation.

Business Reporter Virtusa 1

Senthilkumar Ravindran the Executive Vice President & Head of Digital & Cloud Transformation – Virtusa EMEA

AIoT, an advanced hybrid of AI and the internet of things, puts a new spin on the way we look at ML. AI and IoT offer niche capabilities that can both be leveraged once implemented together. Deploying AIoT solutions requires expertise in both areas; hence companies need to collaborate with agile partners to view the once separate solutions as a singular unit.

AIoT involves intelligent, optimised, and real-time orchestration of physical and digital processes across process control systems (PCSes), manufacturing execution systems (MESes), enterprise resource planning (ERP) and other technologies to increase overall efficiency.

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

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Sanjeev Gulati the Executive Vice President & Head of Digital – Virtusa Americas

According to Markets and Markets, conversational AI’s global market size is expected to grow to $15.7 billion (£11.3 billion) by 2025. The chatbot market is also likely to see exponential growth, withBusiness Wire projecting it to reach $5,638.64 million (£4039.10 million) by 2023.

Interactive voice response (IVR) is one AI solution offering to drive market growth, because it can work with copious amounts of data. Leveraging conversational AI, businesses can improve user experience, IVR containment and omnichannel collaboration to maximise cross-selling and upselling opportunities. Conversational AI will also enable advancements in platform governance, microservices and application programming interfaces (APIs), natural language processing (NLP) optimisation and bot repositories.

Businesses now have complete platform ownership with conversational AI solutions. This means they can address issues that arise from a lack of context in a conversation. Conversational AI also creates communication between once-disparate applications, leading to a simplified escalation process by deciding what is automatable and what is not.

Low-code no-code in AI

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

No-code AI creates democratisation, empowering line-of-business, management and operational teams with advanced analytical capabilities without requiring specialised data science skills. Many of these no-code platforms are easy-to-use, visual drag-and-drop tools. One challenge companies face is that the complex workflows currently in use by most AI/ML models won’t allow them to implement no-code solutions. If organisations want to benefit from these tools, they will need to migrate to a more sophisticated eAutoML platform that enables true no-code end-to-end automation.

Machine learning and hyper-automation

Hyper-automation works in harmony with AI/Machine Learning (ML) technologies and leverages digital process automation (DPA) and intelligent process automation (IPA). It also can automate inflexible and unstructured processes that in the past were non-automatable.

For hyper-automation initiatives to be successful, businesses cannot rely on static packaged software. Automated business processes thus must adapt and respond to changing circumstances. Almost all the leading process automation platforms are embedded with aspects of AI/ML to allow for responsiveness. While the Covid-19 pandemic caused an increased need for learnable solutions, these enhanced capabilities will continue to be used and improved long after it ends.

AI on the cloud

AI has become integrated into every aspect of human life. The next big opportunity in digital transformation is integrating the cloud with AI-powered devices to organise and retrieve data. This collaboration not only enhances the performance of AI-enabled devices but also allows unstructured data sources such as conversations to be collected, analysed and used to a company’s benefit.

Siri, Alexa, Google Home and others have already proven the multiple use-cases of AI in the cloud. With the adoption of hybrid cloud models increasing, businesses can capitalise on pre-trained and ready-to-use ML and deep learning models to strengthen their data analytics. Even companies facing capital constraints can leverage the capabilities of such models.

Merging AI and cloud to scale won’t be easy, but it’s inevitable. Companies need to think beyond implementing ML tools solely to enhance customer service and harness the power of the cloud to optimise the entire customer journey.

A promising future ahead

When deploying newly developed AI systems and ML models, businesses often struggle with system maintainability, scalability and governance. Thus, a robust AI engineering strategy is pivotal to running successful, integrated AI initiatives rather than a set of specialised and isolated projects.

Spending on cognitive and AI systems will reach $77.6 billion (£55.6 billion) in 2022, according to a recent update on the Worldwide Semi-annual Cognitive Artificial Intelligence Systems Spending Guide. One can say AI is ready for a business world marred with unprecedented disruptions and uncertainty. But the question remains, are businesses prepared to use AI to turn their goals into reality?

Brains and bots: Virtusa’s take on AI

Virtusa helps clients accelerate innovation through deep digital engineering across multiple industries. Since AI is at the forefront of the digital revolution, we have developed a suite of AI advisory, experimentation and engineering services to help clients get results faster.

At Virtusa, we help businesses leverage the benefits of next-gen technology such as AI. To find out more, click here

Originally published on Business Reporter

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