Implementing organizational change requires buy-in across all departments. Without advocates, even the most necessary changes are at risk of failing. No tool exemplifies this intersection between essential and nerve-wracking quite like AI (Artificial Intelligence). Every company has both avid adopters and hesitant detractors. 

While AI is certainly not a simple tool to implement, many of the most common reservations surrounding it often come down to misunderstandings about its capabilities. To ensure that companies are evaluating AI solutions the right way, we’ve identified four common misconceptions about AI to debunk. Armed with this new understanding, your departments will show much more enthusiasm about integrating AI into their daily workflow.  

Misconception #1: AI will take human jobs 

The top concern felt across industries is how AI will impact the jobs of the existing workforce. Warehouse workers across the U.S are expressing a concern that “robots” will “steal” their jobs. 

AI can, and should, alleviate some responsibilities from jobs throughout the supply chain. Tasks that take too long without the power of machine learning, those that are too monotonous or dangerous to leave to valuable people. All these are perfect for AI. 

The fear that AI will take over meaningful work that people enjoy comes from watching companies implement AI without a thoughtful strategy. Like every solution, AI must have a purpose and a reason. Manufacturing companies, for example, need AI to highlight insights from infinite data sources. But the final decision should include the perspective and expertise of the people who work in those warehouses. 

Misconception #2: data quality and management is a nightmare 

Another common refrain throughout the AI conversation is “garbage in, garbage out.” The warning describes the data used to power various AI solutions. If the data that is used in the various algorithms isn’t accurate, up-to-date, and relevant, the results it suggests won’t be either. 

Just thinking about cleaning and managing the volume of data required to get valuable insights from AI makes executives and employees alike nervous. While we can’t say this fear is completely unfounded, data cleanliness is not an insurmountable obstacle. 

If data management is a primary reservation stopping your organization from adopting AI solutions, consider the platforms you partner with. The experts who build the AI tools and the professionals who train your team should give you confidence to use AI effectively. Choose solutions that foster ongoing relationships so data management is easier from day one. 

Misconception #3: not enough internal expertise to take full advantage of AI 

Along similar lines, a third common reason companies resist adopting AI tools is because they lack internal expertise. AI is a powerful tool that many people don’t understand. The concern is businesses will invest heavily in a tool that employees abandon in frustration. 

Much like a new language, learning AI is a never-ending process. Today’s experts encounter new information all the time. Your employees will be no different. But, if we allowed ourselves to ignore anything that wasn’t immediately understood, the supply chain itself likely wouldn’t exist. Definitely not in its modern form. 

Worrying that your organization doesn’t have enough internal expertise is the most reasonable fear. But it is also the best reason to get started. AI capabilities will only get more complex as time goes on. The best strategy for staying competitive is to start learning everything you can right now. 

Misconception #4: AI tools open companies to security risks 

Finally, companies hesitate to adopt AI tools because of data security concerns. 

Any company dealing with any amount of data should use best practices for data privacy and security. Building a foundation of trust is a non-negotiable for companies and customers alike. But to upgrade best practices to a proactive approach, AI is the very thing that can help a business stay secure. 

AI tools can automate threat detection and prevention. It can suggest actions for IT teams to take to build better security measures. 

Learn more about AI and machine learning for the supply chain 

To learn more about AI, machine learning, and how all of it impacts the supply chain, read our e-book “Demystifying AI.” Download your copy today.