What is Adaptive Intelligence and how is it making a difference?

All of us have heard about Artificial Intelligence but have you ever heard of Adaptive Intelligence and what is it?

Adaptive intelligence is a subset of artificial intelligence that goes beyond just converting inputs into insights to enable action. It helps in delivering the most contextually relevant output whenever required, by training. Adaptive intelligence, while eliminating all the limitations that come with human-driven decision-making, incorporate certain cardinal elements that can only be achieved by virtue of human involvement.

The three primary precepts of Adaptive AI are robustness, efficiency, and agility. Robustness is the capacity to accomplish high algorithmic precision. Efficiency is the capability to accomplish low resource usage. Agility manages the capacity to adjust operational conditions dependent on current needs.

Together, these three precepts of Adaptive AI plan the key measurements toward super proficient AI inference for edge devices.

While big data has been around for a while now, applications of the technology, until recently, failed to make the impact they were expected to upon their emergence. In fact, it was estimated that 85% of big data initiatives had failed to deliver their expected results. While the reasons for the underwhelming impact of big data initiatives are numerous, not having the right tools and people to clean, analyze, and solve problems.

In recent years, the use of AI to clean — and solve problems using — the enormous body of data collected is making applications of data analytics more effective. However, when it comes to making decisions, there is still a large dependence on humans. Among the numerous ways that AI is enabling the effective utilization of big data by minimizing the role of humans, one way is through the recently emerged concept of adaptive intelligence.

Adaptive intelligence, just like business analytics, helps businesses make better decisions. But, it makes the process of decision-making faster, more adapted to individual cases, and with minimal effort from the decision-maker.

While business analytics focuses on data analysis and delivery of insights, adaptive intelligence adds the focus on context and relevance. . This makes every instance of data analysis and decision-making faster and simpler for the stakeholders which culminates in the enterprise benefiting massively in terms of productivity, effective responsiveness, and, consequently, financial profitability.

The concept of adaptive intelligence is already gaining traction among business and tech leaders as an upgrade on business analytics. It can be used by businesses to make the process of sharing information across the enterprise easier. Thus regardless of where information is needed in an organization, be it in the accounting department or the customer service vertical, adaptive intelligence can deliver the requisite insights proactively by sensing the context.

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The penetration of adaptive intelligence will only increase with time as AI becomes smarter and technologies like the Internet of Things (IoT) become widely within organizations and across industries. Using IoT’s sensory and actuating end-points, adaptive intelligence can become more responsive through greater accuracy in data analysis and greater control over outcomes. Industries like healthcare can greatly benefit from adaptive intelligence as information sharing, accurate data analysis, and prompt response to situations  are vital to its operations.

Adaptive intelligence-based health technology is already being developed and tested to the benefit of all stakeholders in the healthcare industry. Eventually, adaptive intelligence may completely eclipse and replace business analytics applications in all industries.

It would be hardly surprising, given its obvious benefits over traditional analytics. As the modern-day enterprise transitions further towards end-to-end integration, the adoption of adaptive intelligence will definitely prove to be a key catalyst in achieving that.


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