Digital transformation using artificial intelligence (AI) and hybrid cloud has accelerated amid the pandemic and studies have shown that these technologies will play a big role in helping companies to reinvent the ways of working and gain competitive advantage. In a recent conversation with CXOToday, Viswanath Ramaswamy Vice President, Technology, IBM Technology Sales, IBM India / South Asia, explains how hybrid cloud has emerged as the fundamental enabler of digital transformation today and with the more recent innovations in AI, how enterprises can operate, respond, and emerge stronger post-pandemic. He also touched upon the significant skills gap that exists in the market and how companies can help bridge the same.
Hybrid cloud is today’s business imperative, but is India ready for a hybrid cloud future? What role is IBM playing in developing cloud innovation among Indian businesses?
A recent IBM Institute for Business Value (IBV) in cooperation with Oxford Economics study revealed that 99% of organizations in India are using varied combination of hybrid cloud architecture, an increase of 55% compared to 2019. The study also revealed that as hybrid cloud increasingly becomes the reality for any cloud journey, organizations need interoperability, avoid vendor lock-in, embed advanced data security and run governance and compliance tools across cloud environments. IBM is helping clients address these needs with an open hybrid cloud approach, industry-specific clouds and industry-leading security including Confidential Computing capabilities.
Our approach to cloud gives our clients the freedom to work across hybrid cloud and multi-cloud environments while focussing on accelerating open innovation.To address the changing business needs, IBM has developed multiple offerings. For instance we have transformed our Hybrid Cloud Software through IBM Cloud Paks. These are pre-integrated software capabilities which help clients to build once and run anywhere to manage their varied requirements such as security, data analytics, automation, modernization.
Earlier this year, we launched IBM Cloud Satellite, built on Red Hat OpenShift, which enables the data collected from billions of mobile devices and sensors to be processed where the data resides, delivering lower latency and greater efficiency. It integrates security across the breadth of an IT estate, and automates operations with management visibility. IBM Cloud Satellite represents the next frontier of cloud computing and enables our clients to modernize for the 5G and edge era.
How a hybrid or multi-cloud strategy will allow enterprises to build more robust security infrastructure?
Hybrid Cloud is at the center of enterprise digital transformation. Therefore, embracing a comprehensive security program covering different phases of the journey to cloud and cloud environments will help organizations to build a more robust and compliant security infrastructure.
According to the 2021 IBM Security X-Force Cloud Threat Landscape Report, 2 out of 3 breached cloud environments studied were caused by improperly configured APIs.To address rising security concerns, organizations need to change their security approach from a static, network-based perimeter to a dynamic perimeter-less world focusing on users, assets, & resources.Leveraging a zero trust approach enables organizations to protect their hybrid cloud while reimagining their security posture by modernizing operations to dynamically adapt to users, datasets and workloads. Thereby, helping organizations to consistently deploy security policies while providing centralized visibility, context and management for security teams to detect, investigate, and respond to threats faster.
Despite accelerating demand, there’s a major cloud skills gap in the market. What can companies do to bridge the skills gap in a post-pandemic world?
Organizations across the board are facing talent shortage, as half-life of skills continue to shrink, while the time to close the skills gap continues to increase. To stay ahead, organizations need to move beyond hiring and traditional training initiatives and commit to continuous, strategic exploration of new paths. To unlock the Hybrid/Multicloud value, enterprises should encourage employees to build/enhance skills across key areas like cloud-native development, automated multi-cloud orchestration and management, cloud platform engineering, cloud security, AI/ML on cloud and open source cloud computing.
Three key recommendations for organizations to close the skills gap are:
- Personalize at scale: To create a sustainable impact companies must uniquely tailor the employee’s career, skill and learning development journey to match their experiences, goals, and interests. Organizations can leverage AI to bridge the gap between employee and organization requirements while creating a personalized meaningful learning and career path.
- Increase transparency: Organizations can develop a skills based people strategy based on actionable insights generated by using advanced analytics, AI, machine learning and market-based skill data. This will help employees self-direct their journey based on organization and market driven demand for roles and skills.
- Leverage partnerships and platforms: Bridging the skills challenge can no longer be done in isolation. It requires partnerships across internal and external stakeholders. Internally organizations can align and embed future skills strategy throughout the employee lifecycle – from recruiting till retention to maintain the focus and momentum.In addition organizations can continue to collaborate with external partners to pilot innovative skills gap closure strategies,
How can organizations make the most of their data that are spread across an Hybrid environment?
The recent IBM IBV Study highlighted that 99% of organizations in India are using varied combinations of hybrid cloud architecture. This clearly indicates we have entered the Hybrid/Multi-cloud era. Businesses can further amplify the revenue impact of their cloud investments by orchestrating an end-to-end reinvention of the enterprise. This includes leveraging their Data as the fuel and AI as the accelerant.
In fact, IBM has developed IBM Cloud Pak for Data to help clients build a data fabric to connect and access siloed data on-premises or across multiple clouds without moving it. IBM Cloud Pak for Data is a cloud-native, fully integrated Data and AI platform which unifies market-leading services spanning the entire analytics lifecycle – From data management, DataOps, governance, business analytics and automated AI.
We are also seeing organizations are leveraging AI to gain insights from the data spread across volumes of PDFs, documents and charts. Our experts from the Research Labs are focusing on Natural Language Processing to help AI understand the language of business as well as recognize the nuances between words and context and provide literal and implied insights.
Increasingly businesses are leveraging Automation for enhancing business performance, employee productivity and even migrating their mission-critical workloads to cloud environments. Earlier this year, IBM introduced Mono2Micro in WebSphere Hybrid Edition which analyzes large enterprise applications and provides recommendations on how to best adapt them for the move to the cloud.
How can organizations leverage AI to help drive their Hybrid Cloud adoption?
Hybrid Cloud adoption is often done incrementally and is driven by the business value derived from each step in adoption. AI can add tremendous value and reduce the cost and risk by bringing automation into all the phases of the journey to Hybrid Cloud: Advise, Move, Build and Manage. For example, IBM’s Project CodeNet and natural language processing techniques can be applied to the source code of legacy applications to extract business meaning and automate the refactoring of that source code into a more business-aligned microservice architecture. Another example in the Manage phase is where AI techniques for conversation and log mining, and reinforcement learning can be used to train AI systems to automatically predict, detect and isolate faults in IT systems, perform root cause analysis and also execute remediation.
What are the key imperatives for AI adoption and where do you see India in the adoption curve? How is IBM helping its clients adopt AI technologies?
The new Global AI Adoption Index 2021, conducted by Morning Consult on behalf of IBM, revealed that while AI adoption was nearly flat over the last year, the momentum is shifting as the need for AI has been accelerated by changing business needs due to the global pandemic. As per the report, 62% of Indian IT professionals cite reasons such as driving great efficiencies in processes and tasks as considerations for using automation software or tools. Over half (54%) of Indian IT professionals cite that needing a better way to interact with customers influenced their decision to use automation software or tools as a result of the COVID-19 pandemic. Further, 53% of IT professionals reported that their company has accelerated its rollout of AI due to the pandemic and 95% of respondents shared that it is critical or very important to their business to trust that the output shared by AI is fair, safe and reliable.
These data points indicate that organizations are looking to infuse AI in the form of NLP, Automation with Trust & Security as a key foundation across various processes and business functions. Some of the use case scenarios that are prevalent: –
1) Embedding AI in digital journeys: This is to help offer a highly personalized customer experience and seamlessly integrate online and offline engagements.
2) Acceleration of Intelligent automation: Infusing AI into automation for driving innovation and efficiencies, and help save costs, by incorporating machine learning and natural language processing to streamline processes and generate actionable insights, and accelerate service delivery for improved experiences among customers, employees, and users, as well as help, improve bottom-line results.
3) AI in IT operations: IBM Cloud Pak for Watson AIOps uses AI to simplify IT operations management and accelerate and automate problem resolution in complex modern IT environments. It enables IT operations teams to respond more quickly—even proactively—to slow down and prevent outages, with a lot less effort.
Let me give you a few industry use case examples: IBM has been helping a leading university in India create a virtual tutor leveraging AI for their first-year electrical engineering students.
In the manufacturing sector, AI models are being used to predict how much wastage can be controlled by taking corrective measures in the production cycle, predictive maintenance of machines is another example wherein AI can keep a check on the vital statistics of the machine and detect possible failures. IBM believes in the next couple of years, every company will become an AI company, not because they can – but because they must.