According to a recent Gartner report, by 2025, the 10% of businesses that develop best practices for machine learning (ML) or artificial intelligence (AI) engineering will generate at least three times more value from these initiatives than the 90% of businesses that don’t.
Given the substantial value predicted to be obtained solely from the implementation of ML/AI practices, it is difficult to disagree that the future of businesses is heavily reliant on AI and ML technologies, as well as other digital technologies.
The pandemic revealed a world that accepted technology at a rate that would have otherwise taken a very long time to evolve. Enterprises have been able to overcome these difficulties thanks to the widespread adoption of new technology brought on by the pandemic. For organizations, cutting-edge technologies like AI and ML are opening up a whole new universe of possibilities.
Taking advantage of the early-mover advantage can assist organizations in making more intelligent and intuitive business decisions. Outdated techniques such as rigid, monolithic systems, limited adaptability, and manual procedures hampered innovation.
Every day, modern technologies become more and more useful. Marketers are beginning to use ML-based solutions to personalize offers to their clients and gauge their satisfaction levels after successfully integrating ML algorithms into their processes.
These are just a few examples of how AI/ML algorithms are assisting businesses in operating profitably and wisely.Businesses are also seeing the benefits of ML and AI-integrated cloud apps and infrastructure.
They enable businesses to focus on high-value tasks that generate profit rather than manual labor and management. As a result of ML, enterprise IT workloads may become more efficient, lowering the overall cost of IT infrastructure.
This is especially true in India, where consulting firm Accenture estimates that the use of AI could boost the country’s GDP by $957 billion by 2035 if the “appropriate investments” in cutting-edge technology are made.
India has a huge potential to unlock the actual potential of AI because of its entrepreneurial drive, the wealth of talent, and access to the necessary educational resources. However, they need the right partner.
The largest drawback of employing AI is that businesses frequently experience implementation problems, which can range from a lack of data science skills to a platform’s inability to operate in real time. As a result, there is some hesitation among organizations to accept AI, which is having an adverse effect on consistency and effectiveness.
However, India’s full potential can be realized with the proper partner. We must lead the shift as we transition to an AI/ML-driven future by developing the necessary skills.
Building smaller, more specialized “MLOps” teams, similar to DevOps teams in application development, is a more practical alternative to marshaling an army of data science PhDs, which many businesses lack.
Such teams might include not only data scientists but also developers and other IT engineers, with the goal of deploying, maintaining, and continuously enhancing AI/ML models in a production setting.
While enterprises must coordinate resources to support the development of an AI/ML-led ecosystem in India, IT professionals bear a significant portion of the responsibility.
AI and machine learning will eventually become the competitive advantage that organizations must employ in order to survive and grow.
According to Forrester, one in five organizations will increase their investment in “AI within,” or AI and ML integrated into their systems and operational procedures.
The use of AI and ML, two potent technological tools, is essential to helping a company achieve its objectives for digital transformation.
