AI Business recently caught up with Kalyan Kumar, who not only leads the Global Product and Technology Organization at HCL Technologies, but is also the CTO for IT&O and Digital Business and global leader of the HCL DRYiCE business unit.
DRYiCE is an open platform for Enterprise-wide Automation built for the Digital era. It is the first and only Enterprise IT Automation platform that combines traditional RPA with Autonomics (AI-enabled Automation) and Orchestration (Automation applied across multi-task and multi-step processes) that is delivered in an XAAS mode.
Under Kalyan’s leadership, DRYiCE NLP was awarded the AIconics Best Innovation award in the NLP category at The AI Summit in London, and ahead of The AI Summit in San Francisco, DRYiCE is a finalist across no less than four categories: Best AI Innovator, Best Startup Success Story, Best Intelligent Assistant and Best Innovation in NLP.
At the summit in San Francisco on 28-29 September, Kalyan will join fellow AI experts on the closing panel to discuss the pertinent topic of ‘Ethics, AI and employment’, so ahead of the event we spoke to him to hear more about DRYiCE’s current position in the enterprise and a bit about where it is heading in the future.
Kalyan Kumar of HCL and DRYiCE
As a broad business approach, Kalyan says that HCL has committed to infuse artificial intelligence across the technology landscape for its clients, and DRYiCE is their framework to do so. He explains the key proposition of DRYiCE:
“HCL DRYiCE comprises of Automation & Orchestration bonded as a single service which enables the 21st Century Enterprise to be ‘agile as a startup’ while delivering like a ‘lean enterprise’”.
“Made up of 40+ building blocks, DRYiCE consists of a well-proven Monitoring layer (MTaaS), Machine learning components (on proven supercomputing systems), Automation Modules, Cognitive intelligence, Orchestration components, Knowledge Management and a Reporting layer – all tied together in a real pragmatic IT4IT based framework. The modular structure of DRYiCE means that we can deploy the right modules depending on the process maturity and requirements of the customer, while ensuring that he pays for only what he needs. Also the layered architecture ensures that customers get the benefit of an end-to-end system – while the IT4IT binding ensures that the benefits of Artificial Intelligence and Automation are aligned with actual IT processes that businesses understand”.
So where exactly are we seeing DRYiCE impact the enterprise? Kalyan outlines several key use cases:
“A strong enterprise use case of DRYiCE platform is to embed the combination of Autonomics and Orchestration into genetics of businesses to realize the uprising of DevOps culture. Through this, DRYiCE enhances the end-user experience via VEUSA (Virtual End User Service Assistance) interface to recommend and assist on enterprise service requests and incidents. Also automating the execution or provisioning of service requests till end of the service lifecycle. On top of this, the platform tracks the anomalies in the environment and acts in autonomous or assisted modes to resolve the issues proactively. These automated resolutions are possible via machine learning capabilities within the platform to experience the pattern of resolution by humans and thus eliminating the human interventions once the actions are learnt. – thus providing the insights on performance and health of the environment”.
Kalyan outlines the key drivers for these use cases, breaking them down into six concise points:
Faster actions and decisions: AI and cognitive technologies help in making faster actions and decisions. Areas like automated fraud detection, planning and scheduling further demonstrate this benefit.
Better outcomes: AI-based technologies like computer vision help in achieving better outcomes through improved prediction. Areas like medical diagnosis, oil exploration and demand forecasting further demonstrate this benefit.
Greater efficiency: AI-based techniques help in extracting more useful work performed by resources like high-skilled people or expensive equipment when compared to a non-AI environment. This greatly improves efficiency.
Lower costs: AI and cognitive technologies like Speech Recognition help in reducing labour costs. For instance, automated telephone customer services like the Domino’s pizza ordering mobile application further demonstrate this benefit.
Greater scale: Various large-scale tasks which are impractical to perform manually are performed with ease using AI. This helps in achieving economies of scale.
Product and service innovation: Artificial Intelligence fosters product and service innovation by adding new features or enhancing already existing products (embedding AI) to creating entirely new class of products having their own market potential.
Kalyan tells us that HCL is focused on investing in new products and developing long-term plans with incremental milestones. And rather than targeting any particular industry verticals for their solutions, they are looking to implement across the entire enterprise landscape:
“Based on experience with clients and extensive research, we have identified multiple opportunities across verticals and service lines for innovative application of AI and cognitive computing, as well as examined how the technology might evolve in the future. There are multiple solutions that HCL is working on in the AI and cognitive computing space. These solutions cover areas around Next Generation Workplace Services, Next Generation Data Center Services, and Security Intelligence etc”.
Kalyan points out that while the progress of AI development has created new opportunities for organizations, these opportunities come with challenges and risks. He highlights key examples of the barriers to AI adoption in the enterprise and how HCL and DRYiCE is tackling them:
“The first challenge is the unpredictable costs and timelines: AI technologies are evolving rapidly. Highly customized or innovative applications, such as automating the screening of patients for clinical trials or the provision of financial advice, are closer to research projects than systems integration projects. These will involve unpredictable costs and timelines. This is not the case for all uses of AI technologies, though. Some packaged applications for purposes as diverse as forms processing, email marketing, sales forecasting, and customer service are embedding AI technologies, shielding organizations from their complexity while improving functionality and performance.
“Thereby DRYiCE focuses on the core, standardizing the efforts and reducing timelines of implementing the platform alongside leveraging the current smart investments done by organizations to reduce the overall lag or lead time”.
“A further, very different challenge is the scarcity of technical talent: Demand for expertise in some AI technologies, such as machine learning, computer vision, and natural language processing has been on the rise in recent years. Knowledge of rapidly changing landscape of cognitive technology vendors is likely to be in short supply. Organizations may struggle to staff teams with the talent required to pilot and build systems using these technologies.
“Here at HCL the core focus is to develop the required skill set to manage these latest technologies. Hence HCL believes on up-placement of resources to function along with DRYiCE genetics”.
“A third major barrier to AI implementation is managing staffing and organizational impact:
“Organizations may need to redesign tasks, jobs, management practices, and performance goals when they implement AI technologies. These technologies may be used to eliminate jobs or curtail growth in staffing levels. They may also be used to automate specific tasks, changing how workers allocate their time and require them to interact with systems in new ways. Workers may spend less time performing routine tasks, handling only exceptional cases and spending more time focusing on work that requires high-end involvement. For all these reasons, we believe AI technology deployments are different from traditional IT deployments and their impact on organizations requires greater thought.
“Enablement of AI attributes like Machine Learning, Natural language processing, Analytics, Contextualization, Automated execution and many more through DRYiCE will allow the end-process formulation and its execution to lay the foundation of an 21st Century enterprise.
DRYiCE has come a long way in a very short time, but how will we see it develop in the future? Kalyan says HCL has a “crystal clear roadmap for DRYiCE platform where the services will be delivered for two core themes i.e. Autonomics and Orchestration”. He shares the details of these themes:
“The DRYiCE Autonomics Platform delivers all Autonomics Modules consumed in a Multi-Tenant or Virtual Appliance Model (hosted on MTaaS Cloud) and delivered using a combination of MicroApps and MicroServices.
“The DRYiCE Orchestration Platform aggregates all services Digital, IOT, ITO, EFaaS, BPaaS and any future XaaS delivered as a SaaS Offering including full northbound/soundbound RESTful API and MicroServices”.
At The AI Summit in San Francisco on 28-29 September, Kalyan Kumar will join fellow AI experts on the closing panel to discuss ‘Ethics, AI and employment’.
He will be joined at the event by fellow CxOs from the world’s leading enterprises and the most exciting AI software developers, gathering to explore the huge opportunity that AI presents all industry verticals.
To find out more, and to register to attend the event, visit: theaisummit.com