Artificial Intelligence (AI) and Automation are buzzwords in most boardroom meetings, featuring in the discussions around the growth & strategy of the enterprise. The traditional approach of growing business has given way to a more data-centric approach, with conversations around intelligent analytics leveraging the organizational and customer data available.
Be it historical data or real-time data accruing from social media platforms, data plays an important role in real-time analytics to aid business decisions. With the significant increase in volumes of data generated, there has been a commensurate increase in the number of data and analytics tools, techniques, and algorithms, which can churn out business intelligence capabilities in real-time.
Modern businesses pride themselves on being “Digital” or “Data-Driven”. Although, the ongoing pandemic has highlighted that there is a long way ahead for businesses to fully mature as “truly” digital or “data-driven”. The shining light, however, is that we are departing from the tentative experimental days and upholding talks of digital applications at a large scale, in every industry possible. At the heart of this wave of business transformation is “Artificial Intelligence”. For all the CIOs (Chief Information Officers) and CDOs (Chief Development Officers) looking to accelerate their digitalization measures, starting from front desk operations to the big-business-decision-making board rooms, Artificial Intelligence is becoming indispensable.
A Gartner’s 2019 CIO Agenda survey states that organizations that have fruitfully deployed AI grew from 4% to 14% in the year 2018 to 2019. Investments in AI has seen a surge over the past decade. According to the recent IDC Spending Guide, the worldwide spending on Artificial Intelligence Systems will be nearly $98 Billion in 2023.
However, we are yet to realize the full potential of augmented reality, augmented intelligence, explainable AI, edge AI, data labeling, and a host of other technologies. As digital transformation for modern businesses starts to shape up for the future, the key focus areas for any CIO/CDO to garner engagement from their customers should be:
- Volume — The sheer ability to handle the volatility of modern ask, in a timely & cost-effective manner
- Scalability — The flexibility & scalability of businesses has been under the scanner in recent times, particularly in terms of their ability to scale services and support
- Agility — the unseen is still out there. The ability of a business to respond to the unseen demand, need, or taste of the customer without significant lag or compromise on the quality is also another factor.
Back in 1955 when computer scientist John McCarthy coined the term artificial intelligence (AI), little did he know that even after six decades, the term he devised to explore whether machines could learn and develop formal reasoning like humans, would still remain the hottest buzzword in modern boardrooms. So, as businesses start to gear-up to the changing technology sphere, let us see how we can accelerate this transformation leveraging AI.
Artificial Intelligence Vs Jobs
There has been fear and uncertainty associated with AI. It is not at all about “Robots rising and taking your jobs”. At least not any time soon.
Let us view AI for what it is, and that is basically, a tool that can fix a plethora of traditional IT service processes, that are either broken or are marred by human error. Modern businesses need tools to automate traditional IT desk processes and AI automation can make it happen. It will not only eradicate the error-prone nature of the tasks but also make them secure and efficient.
Expand Shadow IT
For the uninitiated, “Shadow IT” refers to activities that traditionally take place outside the realm of the enterprise IT department. Technologies such as Robotic Process Automation (RPA) have become mainstream across many modern enterprises, which is a good sign.
Businesses need to inculcate the culture of self-service analytics and data science to promote the expansion of shadow IT. It could lead to the deployment of tools like chatbots to automate several mundane processes.
Proliferation of AI into core areas of basic Human Needs
The intelligence revolution is not only transforming enterprises, its operations, and services, but AI and its cutting-edge applications have also made headway into some of the core areas of basic human needs. AI has given healthcare a new dimension and revolutionized the delivery of patient care with services such as e-Health, AI-enabled medical devices, telemedicine, and wearable medical gear.
Smart Cities are increasingly leveraging AI technology in making urbanization smarter and sustainable.
Technology is gaining prominence in most aspects of human life, whether it is through smart home devices, advanced surveillance mechanisms, or autonomous vehicles.
AI-Augmentation in critical areas of Global Issues
Artificial Intelligence has proven to be a powerful tool in the fight against the COVID-19 pandemic with its applications in medical diagnoses and patient treatment, drug development, and contact tracing. The academic world is experiencing a seismic shift with AI-enabled smart content, e-learning platforms, and personalized learning. Defence is turning to AI for ‘predictive counter-terrorism’ measures, and AI is making leaps in helping humankind make smarter decisions about global energy consumption and wildlife conservation.
Educate & Inculcate Best Practices to Scale Artificial Intelligence
For all its benefits & advancements, applications of AI and data analytics across all business practices will need a lot more than the advanced modelling techniques & latest technologies. There is no denying the fact that the challenges, known & unknown, in the path of adoption of AI will come from all fronts, be it economic, technical, or social. What modern enterprises need to focus on are the factors that will determine the extent and the pace of Automation or AI adoption in their organizations. We need to invest in both people and technology, including the skills required, the infrastructure necessary and the best practices to scale artificial intelligence.
- Rajesh Chandiramani, Senior Vice President and Global Business Head ESRM, AI & Data Analytics, Tech Mahindra