More Than Legal Redaction Software

Recent research from Gartner reports that 64% of customers would prefer companies that don't use AI for customer service. And, according to Agility PR, after just one frustrating experience with AI-supported customer service, 70% of polled consumers indicated they would consider a different brand for their next purchase.

On the surface, adopting AI-powered customer service to reduce costs and increase efficiency seems wise. However, this is not the case when it eliminates or hamstrings interactions that drive user adoption and loyalty and inform a longer, healthier product lifecycle.

AI can improve or facilitate many of those interactions, and good products often convince people of needs they don't know they have. However, good businesses also don't ignore what their customers say they find valuable, and enterprise software users still value human-led customer support.

Software consumes resources and creates expectations for service that match the time and expense invested in it.

So whether you're a Blackout user or not, Milyli recommends looking for "superior support" adhering to these three core ideas.

1. Superior support for enterprise software is "Human-led and AI-driven."  

AI-led support often prioritizes speedy resolution and reduces nuanced technical challenges to simpler-to-solve problems—prioritizing suggestions for what is the most likely issue, not necessarily resolving the exact issue. That's frustrating enough as a time-sink. But often, when enterprise software users seek support, they are not facing a technical problem but a "solutioning" challenge. They need an opportunity to solve problems through shared analysis and planning and then apply them to the software.

People are 2.5 times more positive about their experience chatting with humans than AI chatbots. This is because stressful and time-sensitive situations require compassion, understanding, and patience to be resolved effectively and satisfactorily.

Our clients are facing complex, high-stakes legal matters, so they must use tailored workflows to lead them to success. Relying on AI to help them would mean ignoring the need to uncover or design solutions through conversation.

It also gives us a chance to validate and dispel the unavoidable frustrations of hard work – that they could be doing everything right and just needed a refresh on a feature they haven't used since their last giant case. The reassurance we can offer to a people problem as people is as important as the technical fixes we provide.