A recent study by Gartner indicates that by 2025 the 10% of enterprises that establish Machine Learning (ML) or Artificial Intelligence (AI) engineering best practices will generate at least three times more value from their AI and ML efforts than the 90% of enterprises that don't.
With such a high value estimated to be derived only from the adoption of ML/AI practices, it is difficult to not agree that the future of enterprises rests heavily on AI and ML technologies with other digital technologies.
The pandemic has unveiled a world that embraced technology at a pace that would have otherwise taken ages to evolve.
Traditional practices that saw monolithic systems, lack of flexibility and manual processes were all blocking innovation.
However, mass new-age technology acceptance induced by the pandemic has helped enterprises overcome these challenges. Modern technologies like AI and ML are opening a new world of possibilities for organisations.
Seizing the early-mover advantage will particularly benefit organisations in taking important business decisions in a more informed, intuitive way.
The applicability of new-age technologies is growing every day. For example, marketers are starting to use ML-based tools to personalise offers to their customers and further measure their satisfaction levels through the successful implementation of ML algorithms into their operations.
This and there are more examples of how AI/ML algorithms are enabling organisations run their businesses smartly and make them profitable.
Additionally, enterprises are recognising the benefits of cloud infrastructure and applications with ML and AI algorithms built in.
They allow companies to spend less time on manual work and management and instead focus on high-value jobs that drive business results. ML can result in efficiencies in workloads of enterprise IT and ultimately reduce IT infrastructure costs.
This stands especially true in India, where consulting firm Accenture estimates in one of its reports that the use of AI could add $957 billion to the Indian economy in 2035 provided the "right investments" are made in new-age technology.
India, with its entrepreneurial spirit, abundance of talent and the right sources of education has mega potential to unleash AI's true capabilities - but they need the right partner.
The biggest limitation in using AI is that companies often run into implementation issues which could be anything from scarcity of data science expertise to making the platform perform in real-time.
As a result, there is slight reluctance in accepting AI among organisations, and this, in turn, is leading to inconsistencies and lack of results.
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However, with the right partner, India's true potential can be harnessed. As we move into an AI/ML led world, we need to lead the change by building the requisite skills.
While many companies don't have enough resources to marshal an army of data science PhDs, a more practical alternative is to build smaller and more focused "MLOps" teams - much like DevOps teams in application development.
Such teams could consist of not just data scientists, but also developers and other IT engineers whose mission would be to deploy, maintain, and constantly improve AI/ML models in a production environment.
While there is a huge responsibility lying on IT professionals to develop an AI/ML led ecosystem in India, companies must also align resources to help them be successful.
In due course, AI/ML will be the competitive advantage that companies will need to adopt in order to stay relevant and sustain businesses.
Forrester predicts that one in five organisations will double down on "AI inside" - which is AI and ML embedded in their systems and operational practices.
AI and ML are powerful technology tools that hold the key to achieving an organization's digital transformation goals.
(The author is Head-Technology Cloud, Oracle India.)
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