Artificial Intelligence (AI) in the headlines looks like algorithms that have decoded consumer and voting behavior better than the humans who invented them. Every field from retail, customer service, and fulfillment is experiencing disruptive change as chatbots and robots enhance and displace people, bringing human and non-human teams together for greater productivity and impact.
Even Wall Street is undergoing automation-enhanced shifts, with over 230,000 jobs predicted to be lost to bots in the next eight years
But how might this affect your career? What issues are raised when a bot can do a white collar business person’s work as well or better than the person who pays the dry cleaning bills? I’ve begun asking around to my clients and colleagues to find out. Below are some examples in the B2C consumer marketing and B2B employee management spaces, and what I’ve learned in helping my clients position themselves to stay ahead of the bots.
White collar robots look like software apps
Keegan started in digital marketing back when his competitive advantage was building an email campaign. Now he develops segmentation and digital advertising strategies for small businesses. Not long after he’d mastered this practice, email marketing tools became more advanced and allowed him to automate a lot of his work, but he was still the brains of the operation. Keegan isn’t yet 30 and already he sees the writing on the wall for his current competitive edge in the marketplace.
“We recently did a vendor review for my biggest B2C clients’ largest online campaign expenditure,” he told me. “The consultant we’d had for the last two years was still serving us profitable marketing campaigns. She is a bigwig in her niche. She wrote a book and speaks all over the place. But we’re going to drop her and hire a competitor because he was able to show us all the underutilized, rudimentary predictive capability in our digital marketing systems—capabilities which can increase our conversation rates by huge percentages.”
Shortly after a meeting where he recommended that his client keep the software system but jettison the consultant who’d been using it, Keegan realized that his digital marketing “team” now consisted of a software app and a new consultant.
Keegan noticed that the speed at which the vendor had implemented its new predictive ability to leverage large data sets off their website means that to retain his own value he needs to be ready to swap out both the software and the consultant in exchange for an even more advanced system if necessary.
“Our new consultant will always have a job if he stays at the leading edge of that vendor,” Keegan told me. “And I will always have a job as long as I can keep finding the right software and consultant combination for my client’s business.” He’s starting to spend more time reading system reviews and interviewing app vendors about new releases.
“No way am I going to get caught flat-footed like the consultant we’re letting go,” he said.
White collar robots can change your job
KC is the Head of Human Resources for a mid-sized B2B systems integrator. The company is growing rapidly and until recently her team’s success has been defined by its ability to quickly onboard new hires. More recently as the job market tightened, she’s focused on employee retention as well. Over a year ago, one of her internal clients approached her and asked if they could trial a customization of a newly enhanced Salesforce extension (Einstein Analytics) on their employee data to discover what factors most heavily impacted employee turnover. Eight weeks later, using basic demographic data combined and performance ratings, the company developed predictive algorithms that produced a list of the individuals most likely to leave in the next 12 months.
To KC’s surprise, the list turned out to be surprisingly accurate as the year progressed. Mid-way through the year KC realized that her team’s work was changing from guessing how many employees were likely to leave to focusing more on developing programs to address the issues of the specific individuals they wanted to retain.
“The 80+ hours my team used to spend analyzing last year’s data and guessing why people leave is now spent designing smarter employee retention programs and succession plans for critical teams, based on fairly accurate predictions of our vulnerabilities,” KC told me. “We don’t quite have the data collection automated to the point where it will take the manual processing burden completely off my team, but after we see the results of this year’s programs we should be able to make a case that allows my team to get out of the data crunching business. I’m looking forward to getting back to the core activities HR is supposed to spend our time on—working with employees!”
After a pause, she said added, “And our team has to be the voice of ethics on the use or abuse of employee data, too. I will be getting smarter about this myself.”
KC is excited because she’s wanted to focus more on employee development and retention all along, but she acknowledges that some on her team are struggling a bit with this shift. “Some people take refuge in the repetitive and time-consuming activity of data collection and collation,” she said.
KC is starting to work with her team on their program development skills and hopes they can rise to greater responsibility and creativity. “We all have to adjust to having a software algorithm on our team and step up to some more innovative use of the data and problem-solving.”
KC’s experience is just one of many ways that employers are beginning to get smart about figuring out who is most likely to leave. Don’t want your employer to know you’re getting itchy for something new? Good luck. Take charge of your own career, and let your boss about what it will take to keep you engaged. The smart ones will figure it out on their own.
Whose job is secure?
These two examples demonstrate that job security in the age of automation is not easy to anticipate as predictive and AI-enhanced abilities to analyze, recommend, automate and interact in ways many humans do today and continue to infiltrate software systems used by millions of white-collar workers.
Like Keegan and KC, leaders who embrace such abilities and work to get in front of it have the greatest chances of success. But what if you’re not a freelance tech nerd like Keegan or system integrator employee like KC? What’s the best job security strategy for the average white collar team leader or independent contributor?
The answer is to be proactive in your career no matter what leadership authority you do or don’t have in your organization. What I mean by this is that keeping your head down and doing what your job description says you should do won’t be enough for you to stay competitive (or employed!) in the very near future. You need to invest yourself in staying competitive in your job category and industry, make sure your personal brand demonstrates this and take the initiative to learn where your job category is going even if your bosses have their heads in the sand.
I’m working on this myself and I’m also working to help my clients get educated about AI and research what it means for their own businesses, team leadership responsibilities, and careers. What I’m learning is that everyone’s future is up to them and the ones who learn to welcome technology, polish up their technical and soft skills and lead ethically will always have the greatest chance of staying employed, even if it means they have to change employers to do so.
Want to learn more about AI, Big Data and how it might impact your job? Watch the webinar Managing and Leading in the Age of Automation for some free career advice.