Increasing Growth Rate of AI and ML in the Current Scenario

Check on the growth rate of AI and ML in the realm of digital transformation

The COVID-19 upsurge caught everyone off-guard and no one knew how to stay in control of this new situation. Businesses experienced distress, if not shut down, people died, healthcare facilities were over-utilized and much more. Artificial Intelligence and Machine Learning came to the rescue in this pandemic. Though AI and ML have been around for long enough, the pandemic made AI & ML more important than ever.

Before the pandemic, remote work and working from home were a luxury. Now, remote work has become the new normal. Companies in the IT sector and other sectors are searching for ways to define procedures to make remote work as favorable & efficient as working from the office. AI & ML are helping remote teams to perform efficiently during the pandemic.

According to research by ABI, within the realm of the Internet of Things, Artificial Intelligence and Machine Learning services are estimated to grow about US$3.6 billion by 2026, increasing at a CAGR of nearly 40%.

The next wave of IoT analytics development will fully merge with the realm of big data, therefore the value in the technology hoard is expected to move beyond the hardware and middleware to analytics and value-added services.

According to ABI Research, COVID-19  did not have any negative impact on the IoT data analytics market while the newly emerging cloud-native data-enabled analytics vendors have cropped some benefits from the current pandemic.

Since industries are undergoing the transition of remoting everything, aspects like out-of-the-box solutions for remote monitoring, asset management, asset visibility, and predictive maintenance are in high demand. Vendors, such as DataRobot,  are now acquiring access to ML and AI toolsets via different application options at the edge, on-premises, and the cloud, and through consumption using Platform as a Service (PaaS), and Software as a Service (SaaS). The COVID-19 pandemic marked the importance of quick application solutions, such as hardware-agnostic SaaS.

Companies are doubling their AI and ML expenses because of the existing pandemic and for all the right reasons. AI & ML have been around for a long but their efficiency was not fully recognized by companies. The pandemic has made essential requirements of applying these technologies. Machine Learning technologies enable modern-day computers to imitate human intelligence on huge datasets, identify patterns, and predict the spread of this pandemic. Artificial Intelligence, on the other hand, is developing to carry out tasks that were earlier executed using traditional methods, more efficiently.

Companies like AWS, C3, and Google also have succeeded in advancing their products and analytics capabilities (toolsets and environment) by designing centralized repositories for COVID-19 data. Presently, these data lagoons are public and are not monetized. However, it is expected that those companies will strive to use the data lagoons to design products for sale to the healthcare market in the future.

From the perspective of technology, the data lagoons could be the first move for designing and testing data visibility and transmitting analytics services. COVID-19 has exhibited the public cloud's healthcare industry aspiration inflating into pharmaceutical, biomedicine, and telemedicine.

Big data and data analytics might not have a treatment for the virus, but IoT-data-enabled technologies proved their potential to reduce public anxiety, monitor patients, and prepare the infrastructure for the new upsurge.

During the pandemic, the usage of AI and ML has increased to an extended level. However, greenfield AI projects have seen a vital slowdown. The AI and ML in the IoT are at their early adoption stage; the lack of development of data-enabled infrastructure restrained the rapid adoption of machine learning on an operational level when COVID-19 began.