AI use in business reached a fever pitch this year. Gartner's latest Hype Cycle for Artificial Intelligence said that 14% of enterprises deployed AI in 2019. That's up from a mere 4% the year before.
Still, it's not all good news. Further research found that using artificial intelligence in business failed to meet CIOs' expectations: Only one in five CIOs in 2018 who expected to use AI by 2019 achieved their goal. When asked what stalled their progress, these CIOs cited three barriers:
Challenges training and deploying staff
Not having enough high-quality data to train AI models
Lack of knowledge about how AI can create business value
At GetApp, these results don't surprise us. Earlier this year, we asked small business leaders working in five industries how they use data to make business decisions.
35% of marketers and 42% of sales leaders said they don't feel confident in their processes for ensuring/controlling data quality and integrity. And although the healthcare sector uses the most data, they also had the lowest confidence levels when it comes to making data-based decisions.
With 2020 planning upon us, these numbers might tempt you to steer clear of AI. In fact, you should do the opposite. You can gain deep business value from using AI—if you take a counterintuitive approach.
Too much of the conversation about AI centers on automation—specifically, the amount of jobs that machines will replace. This holds some merit: Any rules-based, repetitive task is at risk of automation.
But most AI opportunity lies with augmentation. This is when employees use technology to improve their work instead of using technology to replace employees. (i.e. automation.)
To achieve this, they incorporate AI into their workflows and use it to get better outcomes than they would on their own. Since augmentation builds upon humans' work, it can boost your business's weak spots.
For example, Textio is an augmented writing tool that uses machine and reinforcement leaning to help users improve their job descriptions. Per a Gartner report (available for clients):
"Textio's goal isn't to replace HR leads with machines. In fact, it's the opposite: To give HR leaders the insights they need to write job descriptions with less unconscious bias that will help them recruit more qualified, diverse candidates. It's notoriously hard to find our own unconscious bias: AI can help by pointing it out."
Write down the strong and weak points of your customer experience. Then, start shopping for AI-powered software so you can prioritize two business needs that AI will improve.
Why start with only two business needs? Because no single software helps the full customer experience spectrum. Instead, you can use a range of niche tools to solve specific problems across sales, marketing, and customer service. Areas where AI can help right now include:
Sales: AI tools can analyze sales, then suggest which actions sales reps should take next. They can also prioritize which leads are most likely to convert and close, offer account insights, generate forecasts, and offer explanations.
Marketing: AI-powered marketing software empowers teams to produce highly personalized messages at scale that humans can't achieve by themselves.
Customer service: Gartner predicts that by 2022, conversational agents will manage 20% of all customer service. Virtual customer assistants (VCAs) can help improve the customer experience by decreasing time to response and offering constant engagement with your clients.
We should reiterate that AI isn't a magic bullet. It won't replace a poor business strategy, or not having a strategy at all. In other words, AI is not a strategy in itself: It's a tool to improve and accelerate your strategy.
As you consider how to use it in your business, review the pain points that are most crucial for your team to solve next year. If you've learned which parts of the customer experience need help, you can shop for AI tech to solve them.