A McKinsey & Company report has found that, due to machine learning and AI-based systems, “leading organizations are increasing process efficiency by 30 percent or more while also increasing revenues by 5 to 10 percent.”
According to Brianna Van Zanten, Customer Success Manager at technology company InCheq, today’s sophisticated machine learning and AI can do wonders for business operations if applied correctly. “When businesses wed task management with smart automations, they can reap the rewards of next-generation technology today,” she says.
Yet many organizations have been slow to adapt to the era of AI because the technology is still largely uncharted, and finding its true value is tied to individual use cases.
AI and machine learning are underutilized
Another McKinsey survey shows that, while many businesses have incorporated some form of AI or machine learning into at least one aspect of their operations, only about 15 percent have leveraged these advantages across multiple aspects. The overwhelming majority of survey participants also characterized their algorithms as still in the pilot stage. Only 36 percent said their machines had advanced beyond this level.
In particular, many businesses still struggle to incorporate the benefits of automation into their task management systems. For Van Zanten, this means the present is a moment of great opportunity. “Bridging this gap can launch businesses to the forefront of their entire industries,” she says.
Anything routine can be automated
Too many businesses neglect to tap into the benefits of implementing automated systems across their organization.
“Any repetitive task that any of your staff members need to do on a routine basis can probably be taken over by machine learning or AI,” she explains. “Think data entry. Think handling common questions from customers. Think inventory management. Think generating daily reports — or monthly or quarterly ones, for that matter. Today’s automation platforms can be taught the steps to follow and start doing this kind of work independently.”
Consequently, human staff no longer needs to get bogged down in this tedium. “The important thing is to conduct oversight, especially at the beginning, to ensure the system is doing the task correctly,” Van Zanten cautions. “Once it has a full grasp of the activity and timeline, however, it can take over and handle what needs to get done. This frees people up to concentrate on the more advanced and nuanced aspects of their roles.”
According to Van Zanten, present-day machine learning and AI-based systems can handle sophisticated activities if and when clean data is introduced.
Today’s machine learning and AI can handle sophisticated activities
Sick of spending hours on scheduling? Van Zanten has good news for you.
“Nobody should have to get a headache while trying to assign people to the right shifts anymore,” she says. “The great thing about modern systems is that they can hold an enormous amount of data in their attention and analyze it to find the correct solutions in less than a second.”
The same goes for the optimization of the business’s other resources. “Businesses don’t make money when their equipment isn’t being used,” Van Zanten points out. “Downtime is not profitable. Automated driven task management systems can be programmed to make sure every asset is humming away at its highest possible level.”
Systems can even help ensure the safety and security of your facilities. “If you couple your machine learning or AI platform with sensors through the Internet of Things (IoT), then you can give it the ability to conduct continual surveillance,” Van Zanten says. “If a problem occurs — let’s say a refrigerated area’s temperature drops and begins to degrade — then it can alert you immediately. Let’s say someone breaks in at night; that same system can alert you. The system never sleeps, so it raises the alarm right away and mobilizes your security guards. These are just a few examples, but the important thing is that these systems protect your facilities and make them safer.”
Moreover, automations can be yoked together, with the completion of one task unleashing the next in a cascade. “Let’s say a worker finishes a file that needs the client’s review — the system can immediately send an email to the client with a link to the document, asking them to look it over,” Van Zanten says. “Again, this is just one potential application. The use cases are only limited to what you can imagine.”
Since automated systems can complete functions in milliseconds, all relevant staff members can keep tabs on the situation live. “This means your team can collaborate in real time, no matter what continent they might be on,” Van Zanten explains. “It also facilitates instantaneous communications with your clients, vendors, or other stakeholders.”
Believe it or not, however, these capacities are just the beginning.
Enabling predictive analytics
“Machine learning and AI have the ability to scour data warehouses and come up with performance metrics that allow you to know exactly what’s going on in real time,” Van Zanten explains. “This means you can make the best decisions, which result in better outcomes in the future.”
Next-generation task-management systems not only leverage the vast power of machine learning and AI to improve efficiency, but also to foresee the future (in essence). These systems can construct and run simulations that enable business leaders to understand the ramifications of different possible choices. Again, it is all contingent on clean data going in.
“This is called predictive analytics,” Van Zanten explains. “If someone has a hunch, then you can play it out virtually and see what the likely results would be. It’s a great way to avoid bad decisions. At the same time, it can also provide evidence in support of beneficial moves.”
Embrace machine learning and AI to level up
We are poised to revolutionize business to a similar extent as industrialization in the 19th century. Indeed, these algorithms have already improved by leaps and bounds in only a few short years. The future is closer than many business leaders understand.
“Machine learning and AI offer powerful tools businesses can leverage to enhance efficiency and decision-making,” Van Zanten says. “It’s not about replacing human expertise but about integrating technology strategically to maximize productivity and innovation.”