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4 considerations for your approach to artificial intelligence

AI for Small Businesses

Webinar On-Demand “Artificial Intelligence: Implications for Small and Midsize Businesses”

Want to bring Artificial Intelligence (AI) into your business? You don’t need a huge budget — or a team of data scientists — to make it happen. AI is already built into a lot of routine business applications, like QuickBooks. It’s also integrated into new instruments that manufacturers can use to upgrade old equipment.

That doesn’t mean, however, that every company should rush into the latest in technology. Instead, experts advise companies to first consider the following issues in strategy, data, technology and expertise:

Report: Artificial Intelligence for small and midsize businesses
Download report: Artificial Intelligence for small and midsize businesses


  • Consider your strategy first. Instead of looking for ways to bring AI into your business, look for ways to use it to execute on your business strategy.
  • Identify the yes/no questions that are important to your business. Find the questions that matter most to your business and that you would like to predict going forward.


  • Look for an area where you have a lot of data already. Without the right amount of data, artificial intelligence isn’t going to work for your business.
  • Clean up your data. If you aren’t already using a CRM system, your data is probably scattered across spreadsheets, emails, marketing systems and more. You’ve got to clean up this data and get it organized in order to be ready for AI.
  • Treat data as your most valuable resource. Establish a system that effectively collects the data that you care about. Focus on the data that will inform your decision-making, especially if you work in manufacturing.


  • Look for AI in your applications. Check to see if the applications or systems that you’re currently using — or considering investing in — have already incorporated artificial intelligence. See whether they can help you identify trends and opportunities.
  • Identify repetitive tasks that you can automate. These would be low-value functions that people do every day and spend a lot of time doing. Think about whether an application could take the time and aggravation out of completing those tasks by performing them automatically.
  • Consider upgrading your old equipment with new sensors that can gather data analytics. But recognize that this process involves a certain level of customization.


  • Don’t try to manually implement artificial intelligence. Companies that manually implement AI have a very high failure rate.
  • Consider engaging an expert. This is especially true if you want to use machine learning algorithms to inform your company’s decision-making processes.
  • Expect to make continual adjustments. Most models that you run will only be about 25% successful the first time.


Read the report, Artificial intelligence for small and midsize companies, to gain more expert insights on getting started with AI.

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