Why bots aren’t after your job

Job automation talk is everywhere. Will AI replace us? Will robots make it hard for people to find work? If bots take jobs, should they pay taxes? Do we need a Universal Basic Income to offset the impact of automation in our employment market?

While these are all significant questions, they miss two critical points. First, many traditional enterprise jobs have already been reinvented by automation. Second, the automation revolution is not always forced on workers from above.

Job automation often starts with someone on the job who recognizes an opportunity for automation to make their tedious tasks go faster, allowing them to focus on the more human side of the job. Automation can help with the tedium, but it can’t cover more strategic work. A bot might be able to schedule a meeting for you, but it can’t fill in for you in the meeting. Bots can have a pre-programmed conversation with you, but they aren’t able to go off-script when you say something unexpected.

Here at Textio, we talk a lot about augmentation vs. automation. Textio (and the other augmented productivity software that is popping up across the enterprise) augments people’s abilities. This software works a little like a superhero suit: put it on, and it gives you superpowers you didn’t have on your own.

In the meantime, people across the enterprise are increasingly automating away the tedious tasks in their day-to-day jobs.

Customer success roles provide a great example. To get hired doing customer success at Textio and most other SaaS companies, you need to shine in two main areas: ability to use data to create a compelling narrative, and building a common narrative of success with your customer that grows with time.

But increasingly, there is another skill that supports this foundation: You are more effective if you can find interesting patterns in large data sets without the help of an outside engineer. In our line of work, finding interesting data patterns means that you have at least basic scripting ability. With the growing ubiquity of machine learning in all kinds of software products, it’s clear that this will be a required skill — not just at Textio, but everywhere.

The reinvention of customer success is not unique. Work across the enterprise has become increasingly technical. It is no longer unusual to find project managers creating complex Excel macros, ops professionals building tools to automate the collection of sales data, or user researchers writing SQL queries to understand large data sets. For these and many other roles, people who can combine a solid technical foundation with traditional skill sets (storytelling, relationship building, etc) are more successful than people with the traditional skill sets alone.

Even where coding is not required, many enterprise workers are now expected to use predictive automation technology as a part of doing their best work. Sales leaders who collect and respond to deep and specific data about what has worked in the past are better sellers. Marketers with the tools to quickly test and evaluate collateral performance can make adjustments faster. And as we’ve seen at Textio, hiring teams that use our enormous data set to craft their job posts fill roles almost 20% faster, with nearly 15% more people applying from underrepresented groups.

What is happening in many of these cases is not job replacement, but job reinvention: people are augmenting their traditional skill sets with automation to get deeper data insights, faster product throughput, and operational improvement. Companies that work with automation, data, and learning loops simply outperform companies that do not. Want to learn the three critical questions to ask before investing in learning loop AI for your workplace? Register for our upcoming livecast here.

Despite the prevalence of automation in job reinvention, the ability to work with people has never been more critical. Go back to that customer success engineering role for a minute. Data is only as good as the context surrounding it. Telling stories with data, and even figuring out which data to collect in the first place, is a fundamentally human task. Our customer success engineer is as served by their background in psychology, linguistics, or business as they are by their scripting ability.

Look to the bottlenecks in your work and I’ll show you where job augmentation is coming faster than you think. It just takes someone already on the job to recognize the opportunity.

Learn more about how language impacts your hiring at textio.com