On the providers end, vendors are looking at artificial intelligence (AI) and machine learning (ML) as being key differentiator to their cloud services
By Rishu Sharma
Penetration of cloud in Indian organisations has been seamless, with most of them having begun their cloud journey in India. While virtually, none of the third platform technologies is possible in scaled-up implementation without having cloud as a basis, the recent developments in artificial intelligence (AI) aims to make technology adoption easier. The confluence of AI and cloud will fuel not only innovation but will also bring about change, with cloud providing the data needed for effective AI and information provided from AI can help robust the cloud.
As per IDC’s CloudView 2018 survey, over 80 per cent of organisations in India cite machine learning (ML) as very important to their organisation’s cloud strategy with plans to spend money on this over the next 12 months. Uncovering new insights, along with employee productivity and process automation are some of the key benefits that enterprises are seeking to derive from AI. Facial and pattern recognition are some of the early use cases for Indian organisations. Multiplied to a massive market like India, such use cases provide large data sets, both structured and unstructured. As against looking to AI as a new technology, enterprises expect AI to enhance their current business and technologies strategies.
Enabling personalised services to customers
With enormous storage capabilities for data along with processing and computational power, cloud is the underlying platform enabling AI. AI and ML is being implemented to provide hyper-personalised digital services to the end-customers. Auto insurance companies are providing enabling customers to seek claims by providing pictures online, which are scrutinised by intelligent systems without having the need to physically visit the site/vehicle. This is breaking barriers for rural markets with quicker, faster and efficient processing. While storage is provided by cloud, intelligent systems are enabling new ways of delivering personalised services to the end customers.
India is still warming up to AI. Most organisations have realised that AI is the way to go but are lacking faster adoption, as they still figure out embracing cloud for widespread deployment. Banking sector, for instance, are experimenting with chatbots that enable customers for making transactions related to payments, recharges and so on. Ease of implementation and ability to integrate with existing IT along with cost competitiveness is among the key asks when it comes to desired AI solution.
The adoption status of cognitive/AI correlates highly with the information Digital Transformation (DX) maturity of the organisations. Adoption of AI solutions will enable organisations to move towards the later stages of information DX maturity – repeatable, managed and optimised. Organisations must work on having an agile mindset to promote digital business innovation. This will require organisations to have clear measurement mechanics for the impact that AI technologies can bring in. While increased employee productivity and increased process automation are the most common expectations among organisations adopting or planning to adopt cognitive/AI solutions, the barriers related to shortage of skill sets, understanding of vendor solutions, governance and regulatory implications cannot be overlooked.
Some enterprises are still burdened with legacy infrastructure and top of it the concerns around cost, security, shortage of skilled resources and governance compliance deter the AI adoption. While organisations do realise that AI is the way forward, they still need to build algorithms and applications that would help them get these results.
Creating greater opportunities
Large and diverse data sets create new challenges. However, when combined with AI technologies and exponential computing power, they create greater and newer opportunities. On the providers end, vendors are looking at AI and ML as being key differentiator to their cloud services. Global scalability, local hosting and interoperability will be important for vendors in Indian market. Vertical-specific AI use cases on cloud will be able to provide much needed differentiator that the enterprises seek. Providers must also look into partnerships with other niche vendors to provide vertical-specific solutions like partnering with startups in healthcare enabled by AI. The solutions must be able to derive business value that exceeds the cost of investments with minimal human intervention.
In order to have a successful digital transformation, cloud is the underneath for delivering AI services. In fact, the growth for cloud is ultimately powered by data provided through AI. This symbiotic relation between cloud and AI requires all stakeholders across the ecosystem to come at a common agreement around the generation, usage as well as benefits derived along with the challenges bought in by such data influx and exchange. Cloud helps AI in two broad ways – one by being a data feeder and providing accessibility and the other by providing scaled up environment for such data-concentrated services at a reasonable charge. Not only that, cloud also lets the organisations, still in nascent stages of AI adoption, experiment with ML, predictive analytics, etc. with least amount of risk.
The future is a seamless convergence of cloud and AI. With the proliferation of devices and the amount of data being generated, cloud provides computing and storage, thus becoming a repository. AI, on the other hand, will not only be able to leverage this information, but be an additional data-source and provider to this repository. For organisations to move to matured levels in their cloud journey, AI will be among the key enablers. While AI intensity is mostly subjected to digital-native companies, leaders can nurture this development with right mix of vision, people, processes and technology.
Rishu Sharma is Research Manager – Cloud and IoT at IDC India.