The involvement of AI technology into businesses is not as easy as it sounds. There are still a lot of companies which add AI models like single task bots, NLP or vision technology to their business but there processing is still done through conventional non-AI ways. In such procedures, human intelligence is still required.
As per the McKinsey report, AI, ML and other disruptive technologies are venturing into the business procedures via RPA (Robotic Process Automation). The new blend of RPA and AI sums up to the formation of Intelligence Process Automation (IPA). Like RPA and ML algorithms, IPA too, includes process management software, NLP and bots which are considered as cognitive agents.
IPA can add around 20-35% improvement in business efficiency, 50-60% reduction in processing time and also it multiplies the returns on investment, says McKinsey. However, most of the companies are in the early stage of development and tend to operate on an individual unit of AI rather than adopting IPA.
Gartner Analyst Moutusi Sau, talking about the RPA application in the finance sector, quoted, “There are no use cases which will go all the way across yet. There have been some chatbot engines out there, and AI decisioning tools, but you cannot build momentum on one particular solution. Banks want to do more than one thing.”
A German company ZF group which is an automotive supplier started off with the employment of intelligence to its business one year back. The company created a bot to answer repetitive questions received by the company on a daily basis.
In the corporate communication area of ZF group, the company has a bulk of repetitive tasks. It receives a huge number of mails in their inboxes with repetitive questions. But once the task is done the technology can be further utilized for intelligent purposes.
Notably, the company is heading towards a future of automating the whole process rather than just focusing on bots. ZF Group has been looking forward to adopting an integrated platform where these technologies can be deployed with intelligence.
Additionally, businesses can also include intelligent solutions in their conventional methods. In the traditional email process, RPA can be leveraged with ML components which further decides the place where email need to be routed. In most of the cases, the traditional methods of RPA can drive to a better conclusion which simple automation fails to perform. Some organizations are also looking at employing AI for process mining to automate process discovery.
With the evolution of businesses, intelligent means can update the processes and spot abnormal behavior in real time.
Overall, Intelligent Automation Systems operates over a large set of information and is able to automate the entire workflow with self-learning and self-adaptation.