We've grown accustomed to using artificial intelligence (AI) in our personal lives, whether it is to guide us through traffic, ask Siri to fact-check our friends, or recommend shows on Netflix. This has sparked a lot of media buzz that we are on the verge of a "job-pocalypse", with humans soon to be replaced by artificially intelligent robots and apps. Aside from the fact that new technology has always led to the creation of more jobs, even if distributed unevenly, we haven’t yet seen the same level of AI-adoption in the workplace that we’ve seen in the consumer market. In fact, enterprise implementation of AI has been slower and somewhat piecemeal. Why is that the case?
Why has enterprise-AI lagged behind?
One possible explanation is that the consumer market offers shorter product lifecycles, as consumers buy at relatively low price points and expect to replace products within five years or less. Businesses, on the other hand, may expect IT solutions to last much longer. Businesses make decisions based on the potential return on investment (ROI), rather than for convenience or entertainment, as consumers do. But ROI may be difficult to calculate in the early days of a new technology whose potential impact is somewhat uncertain at the outset. If that is the case, we would expect enterprises to be more skeptical of AI and be more likely to take a “wait and see” approach. Relatedly, businesses have datasets exponentially more complex than the average consumer. These datasets may exist on legacy systems that aren’t exactly easy to navigate or leverage in order to train AI models. Both of these factors may contribute to the difficulty in getting enterprise-focused AI solutions to market.
Another possible explanation is that the consumer vs. enterprise disparity is really just a matter of perception. Employees regularly drive to work using Google Maps and listen to Spotify on the way. But when they get to work, they don’t regularly interact with AI solutions that are changing the way business gets done. This, however, has begun to change and businesses are now building successful AI solutions for enterprises.
For example, 2018 has been dubbed the year of the “chatbot”. Enterprises are utilizing AI-powered chatbots to answer simple questions from customers before speaking with a human employee. Admittedly, this blurs the lines between consumer and enterprise AI, but even “old” industries such as health insurance are getting in on the action: Humana’s testing of an AI chatbot increased their Net Promoter Score by 28% and improved issue resolution by 6%. Marketo's success provides a good example of how businesses can use AI to increase marketing spend efficiency and increase revenue. Marketo employs AI to help businesses better understand their target customers and craft more impactful messages to reach them. GE Healthcare reports that using Marketo has widened their sales funnel by $2 billion and helped them close an additional $600 million in sales.
What's changing?
Two factors are contributing to this growth in enterprise-focused AI: the digital environment and fear. On the technology front, migration to the cloud has led to a data-boom that enables more powerful and accurate AI algorithms. Amazon Web Services and its competitors allow much cheaper data storage than before and make it easier for tech startups to provide widely applicable solutions, rather than creating on-premise solutions for every single customer. It simply requires less capital to create a product and test it with customers, opening the door for more upstarts.
As for the second factor, fear can be a great motivator to spark change. Since 2000, 52% of the Fortune 500 companies have disappeared, in no small part due to technological disruption. Innosight Resarch predicts the rate of churn at the top will only increase over the next decade: 75% of today’s S&P 500 will be replaced by 2027. Business leaders are well aware of the risks in failing to innovate and now expect AI initiatives from every aspect of their business in order to increase productivity and drive revenue growth. As a result, forecasts predict that the “Enterprise AI Market” will grow from $845 million in 2017 to $6.14 billion by 2022. That’s a compound annual growth rate of 48.7%! That’s why we think “Workplace AI” is just getting started…
Clearlaw is Excited to Be Part of this Movement
The enormous opportunities for growth aren’t the only reason we’re excited to help businesses implement an AI solution for their legal team. In fact, there is a very important human element to our vision. We've heard far too often from attorneys with 15+ years of experience that they are frustrated to still find themselves doing the same tasks as when they were just a few years out of law school. They are tired of it. Top performers enjoy seeking out challenges, learning new things, and helping their team win. They don't relish doing the same repetitive tasks day in and day out. Clearlaw is focused on helping in-house attorneys and contract managers do their job in the most accurate and fastest way possible, so that they can put down the paperwork and focus on strategic initiatives that will help their businesses put up some more wins.
Our next blog post will discuss in more detail how Clearlaw’s solution aims to achieve that.