Some technology trends make sense for broad business adoption, and others turn out to be more like a Mike Tyson-Jake Paul boxing match: nothing but hype, leaving you disappointed and wishing you had spent your time doing something else. We are convinced that AI is the former and is already transforming the way organizations do business.
The LRS AI & Analytics team has had conversations with dozens of customers who are at all stages of AI adoption. These are some of the most common questions we receive, and we hope that no matter where you are on your AI journey, these insights help you progress and become an organization where AI and automation permeates your business
1. AI is a huge buzzword, but what tangible role does AI play in innovation and competitiveness?
The role AI plays in your transformation depends on the kind of business problems you need to solve. In broadest terms, AI can help you get better in the areas of prediction (forecast at the micro- or macro-level), automation (letting technology carry out tedious, manual tasks), and optimization (e.g., routing or cloud resource management).
2. What does data readiness mean for companies looking to implement AI applications?
A common thought is that you can’t have AI without an IA, or information architecture. Data readiness means unifying the collection, organization, and analysis of all your data. This includes legacy and unstructured data, no matter where it lives in your hybrid data landscape. Even if you are not ready to roll out AI models now, having your data in a trusted information architecture will help you with traditional analytics and visualization and will accelerate the AI journey when the appropriate use cases present themselves.
3. What are some exciting things that LRS customers are doing with AI?
Customer service and employee experience are common starting points for our customers when it comes to AI. This includes using intelligent agents to answer commonly asked questions, such as “how do I reset my password” or even searching through digital documentation to help shop floor technicians understand the troubleshooting process for a particular machine. Freeing up workers from manual and tedious processes by automating processes, such as matching invoices and purchase orders, is another great place to start and gives them time back to focus on more strategic activities.
4. Generative AI has made waves in content creation and automation, but what ethical considerations should companies keep in mind when using these tools?
Companies need to uphold their reputations and protect themselves from AI models that output answers that contain hateful, biased, or unethical behavior. Regulations at all levels of government are now enforceable and more are coming as AI becomes more prevalent. Organizations should work with AI partners committed to protecting their customers from biased decisions as well as indemnifying them from controversies stemming from intellectual property improperly used in training data.
5. How do you manage employee resistance or fears of job displacement when implementing AI-driven automation?
AI is rapidly changing the way we all work. AI agents can find insights in the massive amounts of data in your information architecture faster than workers using old school methods, such as wrangling and munging pivot tables. We believe many of today’s workers will NOT be replaced by AI, rather they will become citizen data scientists, stepping in to correct their AI coworkers when answers are not what was expected and to train the digital coworker on new data.
We hope these answers help you feel more comfortable as you consider how to best use AI in your organization.
Do you have more AI questions or want to explore AI for your business? Please contact us to request a meeting. Don’t have an information architecture for AI that you trust yet? LRS can also help you collect, organize, and analyze your data so that it is business-ready.