Artificial Intelligence and Machine Learning represent the mind of the artificial world, whereas the IoT represents the senses and actors.
In a short span of time, AI and ML have become quickly accessible via open source frameworks, models, and cloud-based libraries. On the contrary, although sensors and embedded systems were commoditized long time ago, their utility has been limited due to several applications and connectivity challenges related to volume, speed, security, and remote intelligence. AI and ML represent the mind of the artificial world, whereas the IoT represents the senses and actors.
These data (information) carriers (things) help enhance the understanding and perception of the world for these artificial minds by sending data from the real world as well as delivering actions to the real world. Data and carriers hold the potential of taking AI and ML to the next level of usefulness and intelligence.
2019 is poised to leverage the duo as the barriers of connectedness continue to crumble with the emergence of edge computing, IoT-focused platforms, communication protocols (low cost and power efficient), and lightweight cyber security.
Additionally, the year 2019, the technology duo of AI and ML along with IoT will play shifting roles in the digital transformation journey depending on the digital maturity and innovation quotient of the organization.
Organizations which are already leveraging IoT and data infrastructure in the cloud will move towards being more intelligent in using its resources for better operations, with increased EQ for better customer service.
Thanks to IoT, organizations will be more equipped and intelligent in tapping critical points in their supply chain and service delivery as well as proactively detect bottlenecks and address them using a combination of localized (real time) detection, such as – identify a potential failure of delivery truck and central (larger scale offline) or predict customer demand accurately using wider available data points from the centralized data housed in the cloud — leveraging structured data and unstructured data, such as audio, video, and text, to derive dimensions such as customer sentiments, fashion trends, compliance failures, and more.
Consequently, organizations will exhibit more EQ by anticipating customer expectations through better segmentation (personalization) in real time. This involves — giving them (customers) more precise product recommendations, along with more intelligent and faster query and issue resolution through chat-bots powered by voice and NLP processing. All this will help free up enterprises’ support services for more advanced customer service needs. These enterprises will enable decentralized, yet optimal and consistent decision making for its workforce through connected intelligence.
Organizations that have just started their digital transformation journeys or are responding to competitors’ move and customer demands are expected to go after low hanging fruits with isolated projects such as customer sentiment analysis, churn analytics, IoT-enabled tracking solutions, and data management solutions in preparation for their digital 2.0 transformation to leverage the duo for better decision making and execution in the future.
Concurrently, organizations that are in the middle of their transformation towards modern infrastructure will be looking for opportunities to recourse testing their digital foundations by moving investments to attack key decision areas/prediction problems for bottle-necked or troubled process flows with a view to embark on projects for better customer targeting and pricing-related areas.
The introduction of the Chief Digital Officer’s (CDO) role in last few years has enabled a tighter integration between business, marketing, and technology functions with more focus on outcome based small wins at the back of the existing infrastructure versus earth moving digital transformations.
It has also influenced partnership and vendor landscape for enterprises. There is a high possibility of start-ups and specialty vendors in areas of predictive, prescriptive, deep learning, IoT devices, and IoT ready platforms and services showing up in the enterprise list of partners alongside the large infrastructure and technology providers.
In 2019, many organizations will embark on their digital transformation journey after realizing the benefit of AI, ML, and IoT. Organizations who have absorbed the benefits are mostly the ones who have introduced the CDO role, and this is where CEOs will start playing larger role of setting up long term transformation goals.
The acceptance of AI and ML across business functions requires buy-in from people. This is where cohesive and clear communication, supply of platforms to decision makers, and an overall culture of trying and failing ideas become important. For organizations that have reached this level of maturity, the use of AI and ML becomes even more important; and CEOs will start playing a larger and deeper role in digital transformation. For all you know, CDOs may become succession plan for CEOs much faster than anticipated.