One look around you and the realization dawns – we live in an autonomous era, with usage of autonomous technologyfast becoming a way of life.
Take driving as an example: in the coming age of Autonomous Vehicles (AV’s) the time currently invested behind the wheel will be freed for us to do anything we want – whether that’s reading the paper, catching up on social media or playing the latest video game against the kids or finishing that work presentation. What’s more, thanks to the analytics and IoT capabilities of AVs, cars will be able to ‘talk’ to each other to find the best route. That means fewer traffic jams and shorter journeys.
What’s true of cars will be as true for businesses. We’re fast approaching a new era of autonomy, where technology will empower businesses to‘drive’ themselves with time. Human workers will be free to focus on higher-value, more rewarding jobs, while the overall organisation will run much more efficiently – and with fewer bottlenecks – due to deep data insights and recommended next best actions. This is nothing less than an enterprise utopia, and one that every business will need to embrace to stay competitive.
The reason autonomous systems for enterprises are so important is because they solve many of the biggest challenges facing businesses today. Whether that’s digital disruption, cost efficiency, customer experience innovation or scalability for rapid growth, autonomous systems can provide powerful answers and help companies transition from being reactive entities to proactive innovation leaders. These capabilities are going to prove increasingly important as digital disruption accelerates, competition grows fiercer and growth becomes increasingly more difficult to secure.
Let’s take a more detailed look at what the future, AI-enabled self-driving enterprise could look like. Autonomous systems are based on AI, machine learning and cloud computing capabilities which allow them to operate with minimal human intervention.
In addition, because this is all cloud-based, the systems learn across, not just a single database, for instance, but across all the enabled databases running in the autonomous cloud. This means they can gain more insights and knowledge than would be possible from looking at the systems from within just one organisation, continuously giving them new and improved capabilities.
What does this mean in practice?
Let’s consider the example of an autonomous database, and how it can become a game changer for any business. First, powered by advanced machine learning, an autonomous cloud database is self-driving. Many mundane daily tasks like security is vastly improved. Second, security patches are applied automatically, and as soon as they are available. Meanwhile, advanced, analytics-based threat monitoring means that threats are picked up far quicker than would be possible if humans were looking for them, and remedied before they can be exploited. Third, it’s self-repairing. As maintenance can happen ‘on-the-fly’, downtime is cut to a matter of minutes each month. This improves productivity by optimising the availability of systems and by ensuring they’re running the most up-to-date and efficient software.
Efficiency improvements don’t stop there. With autonomous cloud, analytics moves up a level. If there’s one thing that computers can do much better than people, it’s number crunching. Through AI algorithms and machine learning capabilities combined with IoT and data integration technologies, an autonomous database will be able to pave the way for the business to take data from anywhere within the organization, in real-time, and analyse it for efficiency insights that even the most capable data scientist will have missed. What’s more, thanks to advances in natural language processing, the results of data analysis are presented in easy-to-read reports complete with suggestions for future action.
Of course, these insights don’t only apply to business efficiencies. This includes insights on customer behaviour that drive product, service and business model innovation. Moreover, with the ability to spin up autonomous data warehouses in seconds through the automatic and dynamic allocation of storage and compute capabilities, the time it takes to get from data to insight is greatly reduced, meaning that these businesses can get to market much faster than traditional organisations.
Then there’s the opportunity for employees in the IT function, such as the DBAs, to move up the ‘business of IT’ value chain. For example, with an autonomous database, DBAs will no longer have to spend time on boring and time-consuming tasks such as patching, updates and reporting. Instead, they can use this time for more creative and rewarding tasks that add more value, such as performance tuning and data acquisition.
These capabilities are all available today. They point to a future where the business becomes more AI-enabled to drive itself and employees can enjoy more enriching work lives. It’s time businesses bid goodbye to the old way of doing things: be it manually patching systems as security threats increase, shutting down systems to maintain them as productivity stifles, losing valuable team members bored in their work and tempted by offers from more rewarding competitors, and struggling to keep up with innovation due to slow business processes. Enterprises have a clear choice to make -find autonomous utopia, or get left behind by their more nimble peers.
(The authors are: Venkatakrishnan J, Managing Director, Managing Director at Huron Consulting Group and Sheela Nambiar, Senior Director, Oracle Digital)