Businesses around the world are looking to AI technologies to increase productivity, minimise risks, and, ultimately, gain a competitive advantage.
AI plays a key role in making what BMC Software calls an ADE (Autonomous Digital Enterprise). These cutting-edge businesses know how to wield the latest technologies to minimise manual tasks and maximise the use of uniquely human talents.
AI News joined Ram Chakravarti, CTO of BMC Software, to discuss autonomous digital enterprises and the growing demand for AIOps.
AI News: BMC coined the phrase “Autonomous Digital Enterprise” (ADE). What makes an ADE and what competitive benefits does it present?
Ram Chakravarti: An Autonomous Digital Enterprise (ADE) is made up of intelligent, interconnected, tech-enabled, value-creating systems that minimise manual effort to capitalise on human creativity, skills, and intellect across the enterprise. Transitioning to an ADE presents a variety of benefits for organisations, enabling them to rapidly evolve, and ultimately stay competitive through streamlined agility, customer centricity, and actionable insights.
One of the key benefits is automation, working as a business function alongside humans, to execute tasks faster and reduce the risk of errors. This means that employees are no longer burdened with manual tasks and can focus on higher-value activities. In addition, an ADE optimises costs, while significantly enhancing customer satisfaction. To support the evolution to an ADE, organisations need to embrace new approaches to talent management, evolve IT departments and optimise technology buying.
AN: Why do we need AIOps and what are its benefits?
RC: There are numerous benefits that come with implementing AIOps. For starters, AIOps provides organisations with insights into all layers of the IT environment. Monitoring and maintaining large complex systems is becoming too much for humans alone. As an example, the volume of operational metrics and log data being created is overwhelming, which can drastically slow repair times when a problem does arise. By applying machine learning techniques and training the models using historical data, AIOps can analyse reams of performance data to identify potential issues, allowing IT teams to take precautionary maintenance measures before a problem impacts customers. An intelligent AIOps solution essentially automates manual processes, meaning organisations will begin to see an increase in employee satisfaction, productivity and customer retention, while significantly saving time and resources.
AN: Around a decade ago, DevOps was a new and barely understood term that has since become somewhat critical to success. Do you think we’ll look back on AIOps in the same way by the end of this decade?
RC: By the end of the decade, we can expect to see the demand for AIOps continue to grow as intelligent automation is added to the mix to help fix problems without human involvement, which I refer to as actionability. Additionally, the intelligence and predictive analytics capabilities of AIOps can be applied beyond traditional IT data: Consider operational data that’s generated by wind turbines, cell towers, trucking fleets. All of that data can be analysed to help predict physical failures and improve maintenance schedules. Noisy datasets will be a barrier of the past as smarter strategies and centralised AIOps solutions help organisations improve the customer experience, deliver on modern application assurance and optimisation, and coupled with intelligent automation to help organisations thrive as ADEs.
AN: What data can be obtained from sources like IoT devices, customer engagement systems, and social media, and how can such huge amounts of data be converted into actionable insights?
RC: By 2025, we can expect data to be reaching unprecedented levels, meaning essentially every company will become a technology-driven business. As noted above, industrial IoT can be used for predictive maintenance and improve monitoring of physical systems. Customer engagement and social media data are all part of delivering a transcendent customer experience. The ability to quickly aggregate, scrub, and analyse your data is key. It paves the way for differentiated business data with key insights across your technology, tools, and employees which then make it possible to deliver a powerful, personalised customer experience.
AN: BMC is a sponsor of this year’s AI and Big Data Expo Global in London and will also be hosting a keynote at the event. What insights do you plan on sharing with the audience?
RC: At the AI and Big Data Expo our focus will be on how enterprises are continuing to amass data at exponential rates, why it’s becoming more imperative to unlock its value and how traditional approaches to data and analytics transformations have seen high failure rates. In my session, I look forward to sharing a recipe for success that rapidly turns new insights into fully operationalised production deliverables – all designed to unlock tangible business value from data.
Ram Chakravarti will be sharing his invaluable insights during a keynote on day two of AI and Big Data Expo Global, which runs from 6-7 September 2021. Find out more about the event and how to attend here.