One of the key benefits that company leaders expect from investment in AI is the streamlining of in-house processes. The automation of routine tasks, such as the extrication of information from tax forms and invoices, can help companies operate more efficiently and make significant savings.
As AI usage continues to grow, so do public fears about the technology in applications such as facial recognition. That means risk management is becoming more critical. Yet not all companies have centralized governance around AI, and that could increase cybersecurity threats, by making the technology harder to manage and secure.
Developing AI models requires a ‘test and learn’ approach, in which the algorithms are continually learning and the data is being refined. That is very different from the way that software is developed, and a different set of tools are needed. Machines learn through the input of data, and more – and better quality – data is key to the rollout of AI.
Some of AI’s most valuable uses come when it works 24/7 as part of broader operational systems, such as marketing or finance. That’s why leaders in the field are employing it across multiple functions and business units, and fully integrating it with broader automation initiatives and data analytics.
The World Economic Forum was the first to draw the world’s attention to the Fourth Industrial Revolution, the current period of unprecedented change driven by rapid technological advances. Policies, norms and regulations have not been able to keep up with the pace of innovation, creating a growing need to fill this gap.
It’s worth remembering that despite AI’s growing importance, it is still just one weapon in the business armoury. Its benefit could come through its use as part of a broader automation or business strategy.
This content was originally published here.