There are few things that are as intriguing to companies as artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT). These new technologies can potentially enable new business models and predictive maintenance, optimize and automate processes, and save costs.
For example, IoT already enables availability of information in near real time through sensors and connectivity; consequently, it is driving the digitalization of many processes.
Furthermore, IoT and AI (and as part of it, ML) are more connected than ever before.
AI as accelerator
Up until now, only damages that lead to downtimes and delays were of interest. Now, modern sensors, intelligent data analytics, and digital networks enable companies to prevent downtimes and delays altogether.
IoT sensors send signals to AI solutions which then can predict damages and defects before they happen. Consequently, AI solutions can then optimize maintenance and improve logistics and manufacturing processes.
AI and ML are especially useful for analyzing massive data volumes. Using past business data, IT systems can then independently recognize repeating patterns.
Many companies already use AI and ML in daily operations. However, especially smaller companies are having difficulties implementing suitable machine learning models or algorithms. Most of them need external IT specialists to support them because they lack resources and know-how.
Furthermore, the entire IT landscape of a company is becoming ever more complex. Which programs to keep, which ones to toss? Companies also need professional help with these decisions.
Support is badly needed
However, this is not a one-man job. Companies need a team of experts. Many smaller businesses simply cannot afford that. This increases the risk of them being left behind in the market because they cannot keep up with the changing times anymore.
External AI and ML specialists ensure the successful implementation of AI systems in existing processes and IT structures. Some require special applications or sensitive data in a separate cloud.
Which brings us to the topic of data protection. IT consultants can provide support in this area as well. That’s because the quality of an AI application is largely tied to the quality of the data it receives, making the question of data security essential.
This sounds like a lot of effort, but it will pay off in the long run.
However, companies need to keep in mind that the implementation of AI is not easy. Because of the high technological effort, it’s expensive and time-consuming; not to mention the change in corporate culture and the need for change management.
Some cost savings can be achieved rather quickly. However, many benefits of AI only become clear in the long term. The sooner companies start implementing AI and ML, the better. Because one thing is for certain: AI is the future.
Companies who recognize this will win in the market, but companies who fail to do so will be left behind.