AI has broadened its applications, trying to make life easier and better. The biggest consumers of AI applications definitely belong to the business class, consisting of investors, marketers, IT and network engineers, product engineers, software developers, and a small but very important group of people belonging to the open-source developer. All of these are relying on advancing knowledge management platforms that focus on delivering relevant courses and certifications for the AI industry. In this article, we have tried to bring the true picture of top AI applications implemented in the business domains where professionals trained from applied courses contribute the largest number of projects.
#1 Using AI to Grow AI Everywhere Quickly
The rise of AI as a service has taken the very business by storm. Startups are developing smarter, more agile AI platforms compared to established product management companies, which has snapped the value chain involved with Quality checks and sustainability. Yet, AI startups are getting richer and more dominant in pushing their ideas to the wider world. These companies are using AI themselves, to grow their own AI line of products by embellishing better features, handy engineering, and user servicing benefits, resulting in a new age package of AI for all types of businesses and domestic consumption.
#2 Making Businesses “Future Proof”
Future-proofing is actually a big strategic step taken by companies to secure their assets and resources from unforeseeable uncertainties. COVID- related lockdowns and slowdowns showed how some companies, despite strong business sensibilities quickly lost their footing. Some who did manage to survive and grow are now feeling the struggle of their existence due to pressures of “The Great Resignation” and demands for 100% remote working. However, the positives of AI applications definitely highlight the 2 years of pandemic work where companies not just grew their businesses but also outperformed their pre COVID numbers in terms of revenue growth, market share, and employee base. And, there are countless examples from around the world that showcase that AI’s applied solutions actually created and saved more jobs than what pre-existing trends would reveal with respect to some saying “AI will take the jobs away in the 21st century!” At least that’s not going to happen now.
#3 AI budgeting is a real thing
Despite knowing the benefits of having an AI development team in the organization, companies are blatantly overlooking budgetary nuances. Some industries are more demanding in AI adoption compared to others that these results in clutter at the top of the value chain. What’s the reason?
Becoming an AI expert takes years of hard work, dedication, and expansive interaction with some of the leading brains in the data science industry. Evidently, despite knowing the rigor and complexity of the AI’s applied knowledge in the real business scenario, organizations seem to be missing the shot with their sustainability goals. According to a recent report on how organizations prefer to adopt and use AI and machine learning in their operations, 43 percent of the respondents stated that they are already doing a lot more with these capabilities than they ever hoped to do two to three years ago. However, only 20% of the organizations actually garnered the kind of results they wished they would see knowing the kind of budgets they have spared for their AI adoption in IT and analytics teams. During the COVID months, a majority of the organizations definitely enhanced their AI adoption, accelerating their business goals to drive higher revenues and generate a sustainable growth chart.
How to make an impact on the AI world?
If you are into AI, data, and machine learning courses, you will realize that there is a sea of opportunity arising in the Cloud Management and IT analysis markets, where trillions of dollars are being invested to make data more secure and easy to access. Similar AI applications are being channeled to grow and scale the scope of new-age capabilities related to the Internet of Things (IoT), Mobile technology, Sensors and computer vision, Video intelligence, and so on.
We are seeing 10x more admissions to leading courses for data science professionals, particularly those associated with Artificial Intelligence, Big Data, Machine Learning development, Cloud computing, and Robotics. Business analysis and business intelligence courses using AI are also quite popular because of their direct involvement in offering a future-proof world for growing and emerging organizations that are yet to taste tangible success with the adoption of Applied AI sciences and machine learning.