Recent research shows that AI-based tools are capable of boosting organizational productivity in a variety of ways, from slashing the time necessary to complete projects to predicting the best ways to optimize procedures. AI-based task management tools are no exception. 

New task management software that leverages machine learning is revolutionizing the entire global supply chain. There’s a fantastic opportunity to use these next-generation solutions to help businesses throughout the supply chain become more agile and competitive. 

The Magic of AI-Based Task Management 

First, AI-based task management software can do much more than simply automate routine tasks; it can automate more and more functions as it gains experience working with an organization. 

It makes the most sense to focus first on automating clear-cut, low-level chores that do not require discretion, such as moving files to different places when their status is updated, or deleting copies of information that has become redundant or outdated. Automatically generating reports when certain conditions are met is another common use. Whatever simple administrative tasks an organization’s team members need to do on a routine basis are good candidates for getting started. 

However, the magic of machine learning algorithms is that they can gain competence in a business’s operational procedures over time. For instance, if the AI senses that a particular employee routinely structures their work according to certain priorities, it can automatically begin placing new assignments in the right order as they come in. 

Moreover, as these algorithms increasingly gather and analyze complex data sets, they can run simulations and predict strategies for reducing costs, utilizing resources better, and improving processes overall. For example, the software can analyze historical data and identify significant patterns in demand, allowing businesses to better manage inventory, reduce lead times and minimize stockouts. Likewise, the system can scrutinize production scheduling and equipment usage, proposing ways to make them more efficient.  

How Next-Generation Task Management Improves Transit Times

When coupled with Radio Frequency Identification (RFID), Industrial Internet of Things (IIoT) sensors, or other technologies, next-generation task management systems can also identify transportation bottlenecks and propose new, more advantageous routes. For instance, if a traffic jam develops along one major artery, the system can automatically flag the problem and suggest alternative routes all in real time, allowing companies to respond to on-the-ground changes as soon as they occur. 

Similarly, this technology can warn operators about anomalous conditions and even potential threats to the supply chain. Consider the recent Baltimore bridge disaster — with next-generation solutions, route drivers or cargo ships would immediately receive guidance to help steer them away from the scene, and point them toward the best new path to their destination. 

Next-generation task management software can even ensure shipments are stored in optimal configurations. Some goods might be heavy or require refrigeration, for example, while others might be slated to ship to a new location soon, which means they should be placed on top for ready handling. AI-based systems can analyze organizations’ capacity, and crunch the numbers to ensure space is always used best and labor will be minimized. 

Transparent Task Management Across the Supply Chain 

At the same time, next-generation task management technology can facilitate end-to-end visibility across the supply chain. When combined with RFID and IIoT, the software can track the movement of raw materials and goods, giving retailers a solid provenance, in order to show their customers. This transparency can be used to demonstrate the legal and ethical sourcing of items. 

In addition, one of the most important advantages of these solutions is that they empower widely dispersed teams to collaborate in real time. Cloud-based computing, automated status updates and intelligent alerts are examples that can enhance communication within organizations and among business partners.  

Speaking of communication, today’s AI-based systems are becoming better communicators. They are not only trained in identifying human emotions and responding to them effectively, but can also accept feedback and adapt over time to learn the proclivities of individual team members.

Best Practices For Adopting New Task Management Tools 

Many businesses that would benefit from these cutting-edge technologies fail to take advantage of them, however. Their leadership may feel attached to legacy systems, or despair that their operations are too complex to be updated. But with careful planning, collaboration and a phased approach, successfully integrating these tools is easier than many fear. 

In terms of planning, the first step is for an organization to assess its current systems and processes in as comprehensive a manner as possible, including an understanding of the legacy system’s strengths and weaknesses. In particular, businesses should look for areas where the new AI-based systems can bring the most value. 

Next, collaborating with IT experts and users is key, so companies should engage with stakeholders of all kinds during the planning process. This empowers them not only to share their insights and concerns, but also to take ownership of the transition’s success themselves. 

Taking a phased approach is also more advisable than attempting to change everything all at once. Break down the integration into manageable phases, each with its own clearly defined goals and benchmarks. This will allow for thorough testing, enabling businesses to address any problems that emerge along the way and minimizing potential disruptions to ongoing operations. 

Software That Matures 

Unlike conventional software, which becomes outdated as time passes, newer AI-driven machine-learning systems become increasingly sophisticated with age because their value increases as they learn, adapt, and mature. That’s why business leaders should consider transitioning to next-generation tools without delay.

Brianna Van Zanten is customer success manager at InCheq.