AI Business spoke with Kalyan Kumar, Executive Vice President, and CTO – ITO and Digital at HCL Technologies and the global leader of the DRYiCE business unit, ahead of The AI Summit in San Francisco on September 28 and 29.
At The AI Summit, Kalyan was joined by fellow AI experts on the closing panel on ethics, AI, and employment.
Driven by Kalyan’s leadership, DRYiCE NLP won the AIconics Best Innovation award in the NLP category at The AI Summit in London. It was also the finalist in four categories at The AI Summit in San Francisco: Best AI Innovator, Best Start-up Success Story, Best Intelligent Assistant, and Best Innovation in NLP.
HCL will infuse AI across the technology landscape for its clients using DRYiCE as a framework as part of a broad business approach. What is the key proposition of DRYiCE?
Automation and orchestration are brought together to form a single service as part of HCL DRYiCE. This enables the 21st Century Enterprise to become as agile as a start-up while delivering as a lean enterprise. DRYiCE, which is made up of over 40 building blocks, 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 combined in a real, pragmatic IT4IT-based framework. DRYiCE’s modular structure means that HCL can deploy the right modules depending on the process maturity and requirements of a customer while ensuring that the customer pays for only what is needed. The layered architecture ensures that clients can harness the benefit of an end-to-end system.
What are DRYiCE’s (Autonomics & Orchestration’s) areas of impact for the enterprise?
A strong enterprise use case for the DRYiCE platform is to embed the combination of autonomics and orchestration into the genetics of businesses to realize the rise of a DevOps culture. Through this, DRYiCE enhances the end-user experience through the VEUSA (Virtual End User Service Assistance) interface to recommend and assist in enterprise service requests and incidents. Additionally, the platform tracks the anomalies in the environment and acts in autonomous or assisted modes to resolve the issues proactively.
The key drivers for these use cases include:
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.
AI-based technologies like computer vision help in achieving better outcomes through improved prediction.
AI-based techniques help in extracting more useful work performed by resources like a high-skilled workforce or expensive equipment when compared to a non-AI environment. This greatly improves efficiency.
AI and cognitive technologies like speech recognition help in reducing labor costs. For instance, automated telephone customer services like the Domino’s pizza ordering mobile application further demonstrates this benefit.
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
AI fosters product and service innovation by adding new features or enhancing already existing products (embedding AI) to create an entirely new class of products having their own market potential.
According to you, HCL is focused on investing in new products and developing long-term plans with incremental milestones. And rather than targeting any particular industry vertical for its solutions, HCL is looking to implement the same across the entire enterprise landscape.
We have identified multiple opportunities across verticals and service lines for innovative application of AI and cognitive technologies. There are multiple solutions that HCL is working on in the AI and cognitive technologies space. These solutions cover areas around Next Generation Workplace Services, Next Generation Data Center Services, and Security Intelligence, etc.
What are the key examples of the barriers to AI adoption in the enterprise and how does HCL tackle them?
Unpredictable costs and timelines
Highly customized or innovative applications are closer to research projects than system 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.
Scarcity of technical talent
Demand for expertise in some AI technologies has been on the rise. Knowledge of the rapidly changing landscape of cognitive technology vendors is likely to be in short supply.
At HCL, the core focus is to develop the required skill set to manage these latest technologies. Hence, HCL believes in up-placement of resources to function along with DRYiCE genetics.
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. Therefore, we believe AI technology deployments are different from traditional IT deployments and their impact on organizations requires greater thought.
Enabling AI attributes like machine learning, NLP, analytics, contextualization, automated execution, and much more through DRYiCE will allow the end process formulation and its execution to lay the foundation of a 21st Century Enterprise.
You’ve mentioned how HCL has a ‘crystal clear road map for DRYiCE platform where the services will be delivered for two core themes, i.e. autonomics and orchestration’. Could you share the details of these themes?
The DRYiCE Autonomics Platform delivers all autonomic computing modules consumed in a multi-tenant or virtual appliance model (hosted on MTaaS cloud) 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/southdbound RESTful API and MicroServices.