Overcoming AI adoption challenges
Implementing AI in a business setting comes with potential hurdles. Here are five of the most common ones:
Know-how: Most of us aren't AI experts, so for smooth integration, take the time to train on your freshly chosen tools—this includes explaining benefits and limitations to your team upfront.
Data security and privacy: Ongoing commitments include transparency, employee training, and removing/modifying personal identifiers in your data. However, selecting appropriate AI tools can alleviate a lot of potential headaches.
Resistance to change: It’s natural for people to fear the unknown. Do your best to introduce AI thoughtfully—addressing staff and consumer concerns and emphasizing long-term benefits.
Legal and ethical concerns: Navigate uncharted legal waters by monitoring tools, training employees, and staying updated on regulations. Thoroughly research tools and consult with your legal expert or team when handling sensitive data.
Leading companies that already augment with AI
Plenty of companies have overcome the hurdles and successfully integrated AI into their daily business practices.
As the giant relationship management brand puts it, “AI + Data + CRM = Customer Magic.” They recently built AI into their service offering by creating Salesforce Einstein, boasting the ability to bring predictive and genAI into any facet of business.
Need to write email campaigns or other conversion copy? CopyAI is a powerful writing generator.
Turbo-charged by AI, Canva is a highly usable tool (especially by non-designers).
If you’ve ever electronically signed a contract, you’ve probably used DocuSign. The company added AI to power its first-pass review assist (FPRA). It uses color-coded risk assessment to identify low-, medium-, and high-level risks within a contract document.
Netflix has been at the forefront of using AI to engage and retain its customers. By leveraging AI, their team developed an algorithm to personalize show and movie recommendations based on its users' viewing habits and preferences (by analyzing the vast amount of user data generated from their ratings of shows and movies).