Artificial intelligence that adapts to changing data and environments is what adaptive AI is about. Adaptive AI systems can modify their behavior based on their experiences, without human intervention. Embracing AI engineering practices for building and managing adaptive AI systems will enable enterprises to outperform their peers in terms of operationalizing artificial intelligence models by at least 25% by 2026, according to Gartner.[1] This enables AI to deliver better outcomes faster while aligning with enterprise goals and values.
On the one hand, business systems need to be efficient and productive, following set processes and procedures that can ensure quality and profitability. On the other hand, business systems need to be innovative and creative, generating new ideas and solutions that can create value and differentiation. Traditional AI systems tend to favor efficiency over innovation, following fixed processes and procedures that can become rigid or obsolete when faced with new challenges or opportunities. This can lead to missed opportunities, reduced customer satisfaction, and lower competitiveness.
Equifax is a global data, analytics and technology company that provides solutions for fraud, risk and marketing across various industries such as banking, lending, telecommunications and insurance. A Equifax customer, who has been a deep-subprime lender for many years, wanted to replace its core model. Working with a deep subprime audience can be challenging when trying to differentiate risk accurately. Therefore, it was interested in leveraging artificial intelligence. The traditional modeling techniques can simplify risk criteria to the point where they are not useful when dealing with deep subprime loans. To address this issue, Equifax was asked to construct a new risk model using Equifax data and attributes. With Equifax’s help, the lender was able to better segment risk levels among its deep subprime customers. The lender approved 92,000 more accounts while reducing losses by using fresh, new data sources within a machine learning model. They also delivered $13.7 million in annual loss savings, a 92 percent lift in KS and a 7 percent lift in the retailer’s scoreable rate.[2]
Adaptive AI is aiding businesses to pioneer acceleration by enabling them to leverage data and insights in real time and dynamically adjust their strategies and actions. Adaptive AI can help businesses optimize their processes, products, and services, as well as anticipate and respond to changing customer needs and market conditions. By using adaptive AI, businesses can gain a competitive edge and achieve higher levels of efficiency, innovation, and customer satisfaction. Adaptive AI is the future of business intelligence and decision-making. Adaptive AI systems seek to balance efficiency and innovation, modifying processes and procedures based on their insights without human intervention.
Market leaders are leveraging the power of adaptive AI to create value and differentiation for their customers, partners, and stakeholders. Adaptive AI is a valuable tool for market leaders who want to enhance their operations and stay ahead in a fast-paced and constantly evolving business environment. By leveraging technology for customer service, supply chain management, and predictive analytics, businesses can improve efficiency, productivity, and profitability. They can also adjust their processes and procedures based on their insights to respond faster and more effectively to changes in the market and customer expectations.
