Adaptive AI combines the aspects of AI techniques (i.e., reinforcement learning) and methods (i.e., agent-based design) to create systems that are able to adjust their learning behaviours in real-time.
This type of AI is beneficial because it allows for systems to be much more flexible and dynamic in their learning, which can be useful in a number of different contexts.
“Flexibility and adaptability are now vital, as many businesses have learned during recent health and climate crises,” explains Gartner Distinguished VP Analyst, Erick Brethenoux in an article titled ‘Why Adaptive AI Should Matter To Your Business.
“Adaptive AI systems aim to continuously retrain models or apply other mechanisms to adapt and learn within runtime and development environments — making them more adaptive and resilient to change.”
Gartner cites an example via the U.S. Army and U.S. Air Force, who have built a system capable of tailoring its lessons to learners as they progress through an educational program. It acts as an individual tutor of sorts, actively adapting material based on users’ strengths and weaknesses.
Businesses in particular also stand to reap a great benefit from this technology, Gartner continues. In a world where flexibility and adaptability are essential to simply staying afloat, adaptive AI is giving organizations the capacity to remain nimble in the face of the unexpected and grow through means of resilience.
Experts believe that adaptive systems will enable new ways of operating a modern business, breaking down decision silos and ultimately opening the door to new product, service and sales channel opportunities.
In fact, Gartner predicts that by 2026, enterprises that have done so through AI engineering practices will outperform their peers in both the number of and time it takes to operationalize AI models by at least 25%.
But implementation won’t be straightforward.
A great deal of reengineering and rethinking will be necessary to fully adopt the benefits of adaptive AI. Decision making processes and architectures require business stakeholders to take a thorough approach to everything from regulations to compliance. Identifying use cases, understanding sourcing impacts and properly engaging new technology are another three areas that need to be tackled. Really, what introducing adaptive AI will require is an unprecedented degree of collaboration among representatives from business, IT and support functions, not to mention a whole lot of engineering strategy.
This can look like a lot of things in practice, but comes down to these steps:
1. Creating foundations for adaptive AI systems by complemented current implementations with event-stream capabilities and continuous design patterns.
2. Progressively moving towards agent-based methods to give systems components more autonomy.
3. Making it easier for users to adopt AI and contribute to adaptive systems through the incorporation of explicit business indicators and trust-based decisioning frameworks.
Adaptive AI is still very much in its early stages, with a lot of development yet to be done. But as the technology continues to mature, it has the potential to revolutionize how businesses operate – and those that are able to embrace it will be well-positioned to succeed.
