We secured an exclusive interview with Navin Sabharwal, Fellow and Chief Architect at HCL DRYiCE, and spoke to him about how they were involved in the AI-space today and how they will be in the future.

Navin Sabharwal is as an Innovator, Thought Leader, Author and Consultant in areas of AI and Machine Learning, Cloud Computing, Big Data Analytics, Software Product Development, Engineering and R&D. He’s responsible for IP Development & Service Delivery in the Areas of AI and Machine Learning, Automation products, Cloud Computing, Public Cloud AWS, Microsoft Azure, VMWare Private Cloud, Microsoft Private Cloud, Data Center Automation, Analytics for IT Operations, IT Service Management.

After the AI Summit London, we managed to secure an exclusive interview with Sabharwal, Fellow and Chief Architect at HCL DRYiCE, in which we asked him to outline how they were currently involved in the AI-space, the challenges of adopting AI to businesses and where he saw the company in relation to the adoption of AI in five years’ time.

We started off our conversation with Sabharwal by asking him to detail how DRYiCE is currently using AI. “DRYiCE is a way of thinking which focuses on leveraging automation driven by artificial intelligence principles (ergo named Autonomics) to accelerate outcome oriented organizational operations,” he started.

“Automation has been a core driver of our Infrastructure, Applications, Business Process and Engineering services for more than a decade. Since the maturing of key transformational technologies such as Artificial Intelligence, Machine Learning and Predictive Analytics. AI intrinsically forms core components of several offerings inside the DRYiCE framework, from monitoring in the sense and act layer to intelligent dashboards in visualize & insight layer. Inclusion of such can range from use of machine learning algorithms for prediction to deploying computer vision techniques for rapid triage document processing,” he explained.

He then outlined the four components of DRYiCE’s use of AI:

1. Lucy – convolutional networks based natural language processing
2. iAutomate – Automated Remediation, Recommender Systems & Information Retrieval Algorithms
3. MyXalytics – Statistical Inference & Regression
4. Partner Ecosystem – Leverages AI heavily in monitoring & prediction”

Sabharwal then highlighted which industries they are gaining more traction in relation to AI. “DRYiCE components are widely used to differentiate offerings across the horizon and has application in every industry be it manufacturing, retail, healthcare & life sciences, travel & logistics, financial services, energy & utilities and finally IT. It is an enabler and not a silver bullet in several ways, such as decision making, sensory information analysis, data compression, pattern recognition, classification, anomaly detection, predictive analytics etc,” Sabharwal told AI Business.

He continued, “Organizations which have amassed data over the years are poised to reap the rewards assuming ML is applied in the right context coupled with seeking goal driven insight.”

“‘Builders’ and ‘Consumers’ both would see advantages of implementing cognitive intelligent applications. Any area of IT operations, wherever the number of variables to be controlled are enormous, environment is complex and the need to work with massive datasets is inevitable, machine learning can have immense impact in terms of cost, accuracy, scale, optimisation, flexibility and ability to produce proactive response,” he outlined.

Sabharwal then went to offer some examples. “Particular examples can be use of ML based cognitive assistants which learn from extensive service desk experience, monitoring agents which provide alerts before applications or infrastructure components fail, fraud detection system, recommender systems, medical diagnosis, demand forecasting, sales planning etc. Application such as this would ultimately lead to operation cycle reduction, higher predictive accuracy and increased customer satisfaction,” he noted.

We then moved the conversation onto DRYiCE’s competitors in the AI-space. “HCL has thoroughly studied and analysed the growing unanimity among CEO’s, business leaders and CIO’s that the business competitive problem is immensely benefited due to the slow rate of technology adoption and Integration of new automation technology by businesses,” he began.

“Previously one of the major influences underlying this situation was the lack of an economic breakdown specifically aimed at estimating the profits of automation technology. HCL’s analysis technique is based upon the evidence of augmented probability of capturing the various market sectors through economies of scope. Automation is a reality in our industry. In those accounts where we offer managed services, DRYiCE enables a better customer experience and protects our revenues and margins,” Sabharwal said.

“Where engagements are dependent on human resources, Automation enables us to offset the resultant loss of “effort-based revenue” by “up-placing” knowledge workers to taken on higher, more valued tasks; potentially resulting in higher billing rates. The impact of DRYiCE also gives our customers the confidence in our commitment to the relationship and our capabilities in next-generation transformation; which enables further high-value business for HCL,” he offered.

“HCL acknowledges that whether it is creating differentiated and unifying Customer Experiences or Eliminating waste through A.I. – Technology is the foundation of the 21st Century Enterprise. This puts incredible pressure on the functions which are the technology bearers within an enterprise – whether it is “Information Technology” (I.T.), creators of customer facing technology or “Business Technology” (B.T.) or technology that runs the Enterprise or “Operations Technology” (O.T.). The onus is on them not only to run more efficiently and be aligned to customer experience – but also to eliminate waste, maintain a secure enterprise and power business growth,” concluded Sabharwal.

Yet businesses looking to adopt AI will face huge challenges, and Sabharwal was on hand to explain what they are and how companies can tackle them. “Recent and ongoing progress in the development and commercialization of AI & cognitive technologies is creating new opportunities for organizations. But these opportunities come with challenges and risks,” he answered.

Sabharwal then highlighted some examples for us, which we have highlighted below:

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.

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.”

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.”

“The DRYiCE Implementation philosophy is “Pragmatic”. More than a decade of Automation experience has been encapsulated a methodical approach to evaluating the “as-is” maturity state of the current IT systems and processes; and then creating a practical multi-year roadmap to introduce the right technology at the right time – to avoid over-investment and inflated expectations from business. For example, our A.I. centric modules are used to automate processes which deal with Digital/Stateless/Software Centric applications or infrastructure; while more traditional RPA modules are used for more legacy systems,” he finished.

We concluded our conversation with Sabharwal by asking him to outline where he sees DRYiCE in five years time in relation to the adoption of AI. “DRYiCE supports all verticals in HCL Technologies for adoption of AI and other related industry offerings & HCL IPs. We see it as change accelerator not only internally but beyond our organization as well by providing a robust and dynamic framework for maturing processes, tools & user interaction through artificial intelligence. We have entered into the world where machines and humans will augment each other to reach optimal solutions and this partnership is only going to flourish in the coming years, AI being the key driver of it. Forrester predicts that the investments in AI will triple in the year 2017, all the more reason for DRYiCE to proliferate,” Sabharwal replied.

“AI will dwell deep into the way organizations work. Cognitive computing, advanced analytics and machine learning will empower businesses with actionable insights at a level never experienced earlier. We can visualize the impact this will have on decision making in areas like marketing, ecommerce etc., and the intelligence level of decisions looks exponentially high,” he concluded.