3 Unexpected truths about AI and technical support

How AI helps open the door to innovation

By | 2 minute read | March 20, 2020

Data in our world is ever-growing, streaming in from device sensors, IoT and millions of digital transactions across industries. We need new technologies such as artificial intelligence to analyze all the data. What does that mean for us at an individual, human level in the technical support space?

Companies look to AI to analyze complex data and validate technical support decisions. According to a NewVantage Partners study, more than 91% of firms report ongoing investment in AI, yet just 14.6% report broad AI deployment.

In my role, I discuss AI applications for tech support with clients; everything from smart chatbots to augmented reality to analytics for big data. Naturally, questions and perceptions about AI’s capabilities are part of the conversation. Having these discussions opens the door to further adoption and innovation.

I’d like to share my views on three AI perceptions and truths to consider, whether you’re just beginning to assess AI services or already on the path to implementation and deployment.

Perception: AI can solve my technical support problems on its own.

Truth: AI is a powerful solution that works best in conjunction with human expertise.

For example, AI can narrow down the subset of technical support tickets needed for deeper analysis, highlight problem areas and identify abnormalities. You can review the insights and focus on the appropriate support areas to help shorten response times.

“Instead of having to wade through 40,000 tickets to improve a client’s service experience, IT support managers can get to the right decisions faster, execute sooner and make a positive change for their clients when it matters,” said IBM AI and analytics leader Milena Arsova.

Perception: I’m an expert; I don’t need AI.

Truth: AI augments your expertise. It relies on you for perspective, industry knowledge, even training.

AI takes care of the heavy data lifting and repetitive tasks that, let’s face it, we don’t always enjoy. We can apply our knowledge with precision and focus on the most important problems.

“The data AI uncovers doesn’t lie; it often confirms our hypothesis and provides the data we need to back it up. It also illuminates counter-intuitive insights in volumes of data,” said Arsova. “This is where expertise comes in – to review, assess and define the steps for meaningful change.”

Perception: AI probably won’t tell me anything my current data analysis tools already do.

Truth: Trusting AI and the data insights it generates can open the door to more innovation. It’s natural to wonder if something new is really going to make a difference in our jobs. We trust ourselves and our abilities.

At the same time, only 37.8% of those surveyed report achieving a data-driven organization, according to the NewVantage Partners study. AI applications help make seemingly impossible data tasks possible and can offer competitive advantages versus traditional analysis tools.

Apply AI applications to find technical support inefficiencies and transition to smarter, data-driven operations. It’s okay to trust AI because it trusts you.