PER USE CASE
Will the future of work be the future people want? Citrix and Quartz recently asked a panel of workplace experts, or WXperts, from Deloitte, IBM, Twitter, Yale University, and other hives of thought leadership, to peer into the future. Read on for their predictions—and get started preparing your organization for the next 15 years.
ARTICLE | 7m read
February 2, 2021
“Technology’s transformation of nearly every facet of our economy means that we will all need to develop new skills and knowledge at a pace—and on a scale—never before seen. Ongoing skill development will become a way of life.
“But the good jobs of the future will require even more postsecondary education and training—and a broader set of skills and competencies—than the jobs of the past. Most workers can already sense that things are different now—that they must somehow skill up. And this is where things get really stuck.
“The more we learn about the future of work, the more we must shift our efforts to reimagining the future of learning. With no end in sight for the rapid changes in work ahead, we are all at one point or another—whether we’re 18, 25, 45, or 65—going to have to rethink our path in life. We will come to a juncture at which we’ll have to upskill or retool ourselves through more education in order to keep up with the changing needs of our economy.”
"In a future workplace that will be more digitally driven, with hybrid clouds and open architectures creating more collaborative environments, security will need to fundamentally redesign the construct of trust that it has traditionally relied on, and instead finally place AI at its core — not only to strengthen businesses' security posture, but to help employees navigate these new workspaces with peace of mind.
“To secure more digitally diverse workspaces, two factors are key. The first is managing access to data. With privileged access management, you are giving employees access to the tools, systems, and data they need to do their job effectively, without extending the pool of people who have access to sensitive assets and therefore can create more risk. The second is replacing blind trust with AI-driven, real-time context in security.
“In these ‘shapeless’ and more transient work environments, security must be able to verify sign-ins and log-ons from any location at any hour of the day regardless of the user's credentials. This is where AI comes in — by contextualizing not only user identities but behaviors too, it can verify user legitimacy passed any suspicion. In other words, AI adds an extra layer of protection confirming not only that you are who you say you are, but that you're acting like it too."
of US and European business leaders believe both cybercrime and big data breaches will present a significant risk to organizations over the next 15 years.
“Just because you have a great degree from a great school doesn't mean that your life is easy right now, and to begin to apply design thinking to what it means to be a homeschooling parent with a fancy job is critical. And any company that can aid in that. Citrix and many others are going to be critical to thinking through what it means to create that future.
“[Before the pandemic] we had a lot of make-work meetings that were just about looking each other in the eye and drinking coffee, and when you eliminate those you can reclaim your time. “There’s also going to be a reckoning with what were the good parts of meeting-driven cultures, and then beginning to look at job shares. There have always been people, particularly working parents who have been sharing jobs, but what would a job share during a pandemic look like? What if one person works 2.5 days a week and a mother works another 2.5 days a week? So, half the time, you're doing home schooling and you either have your morning or your afternoon for work. I think there’s going to be a lot of reconsideration around that idea.
“A former coworker of mine used his grandmother’s phrase, “Boil it down to the low gravy.” Meaning: Take things to their essence. I hate meetings that exist for no reason. Let’s get rid of ‘em. Let’s spend more time with our friends and family. Let’s get rid of fake productivity. If we can come out of this with an idea about how to be more focused and more efficient, and also more humane toward ourselves and others, that would be a great gift. I don’t know if it’ll happen, but that’s my dream.”
“Within HR, most algorithms are based on or trained in historic employee data, which is appropriate in some applications like predicting trends in headcount, but might not be the best for others. Leaders are skeptical of algorithms as a whole right now, and I think it’s correct to be skeptical. The best advice I can give is to make sure you're asking the right questions around this tool to judge if it’ll be beneficial or potentially detrimental to your business or your strategic goals. What will that algorithm be used for? What individual employee or candidate decisions will be based directly on this algorithm—such as in the selection example? Will it be used for aggregate forecasting and projections?
“Given the pace at which we’re experiencing change, your best practices won't always work for today’s problems. And the best practices for today will not work for tomorrow’s. The work of your employees is going to be different—even more fast-paced, more agile. Current jobs will evolve with increased technological influence. And leaders will hire workers for their ability to learn quickly—fluid intelligence—rather than already knowing how to do work when they come into the role.
“So I see this as a major opportunity for people analytics to help identify skills gaps in the current workforce, things that make high performers and top candidates choose your company over others when they have another offer. That is a necessary partnership between people analytics and leadership, kind of focusing on being more of a centralized intelligence function within the HR space.”
“While there is a great deal of potential for AI to help companies make smarter, data-driven decisions in hiring, we must take care to be sure the ML models are learning from the most diverse and inclusive set of data possible. For example, a few years ago, a well-known company developed an in-house program to identify top talent from pools of applicants. However, the data set that taught the machine how to identify those applicants was based on 10 years of résumés that were mostly from men, so résumés were not being rated in a gender-neutral way.”
“I hope more measurable practices on the front end of hiring are implemented; simply measuring the outcome is not enabling different opportunities. Much like the blind audition process in orchestras now, I hope we will use technology to hide elements of possible bias until the resume is evaluated. I hope we will see job role creation and the requirements (e.g., flexible working and location) actually change to be more inclusive. Bias in companies affects qualities and diversity in cities. I think similar to California’s Gender Diversity Mandate, we will see more outside expectation and checks to publicly traded companies—and companies doing business in locations that account for pay gaps, and increasing diversity beyond gender at executive levels. I’m excited to see how this increases investment in education and professional development.”
“It is important to explain that there is value to the individual employee when the data is captured. Ideally, it would be nice to have an interface where employees could log in and use a system to help them enhance their productivity, or meet other goals like decreasing their hours spent on email, in exchange for a portion of their privacy.”
“Transparency is ultimately what builds trust. The employee needs to be able to see that it’s not just a fishing expedition for the sake of gathering data. There’s a nuance to it in the sense that even if you’re transparent, there’s a step further you have to take in order to get buy-in. And that step further is to say, ‘Here’s the value proposition for the data collection. You will get X out of this. This impacts this decision.’ For example: ‘We’re trying to establish a policy or framework on overtime, or how we should do healthcare a different way, and we need to understand it from a demographic aspect because working mothers have a different perspective on this than single males. So, some of the anonymity will go away, but the tradeoff is that we will have a more thoughtful response and be able to understand everybody’s concerns depending on their lens or their view.’”
of professionals would allow technology to monitor and help them improve their working habits if it significantly increased their performance and remuneration.
“The always-on mentality is a byproduct of the constant anxiety of missing out or being viewed as less valuable. Leaders need to model the way with how they manage their time—and value their team’s time as well, to safeguard their mental health. Resist rewarding the behaviors that slip into unhealthy territory. Productivity is not sustainable at a burnout pace.”
“We’ve been in an era where companies are purely numbers-driven and focused on shareholder value. That dynamic changes as consumers start thinking more about a brand’s values, and CEOs will have to think beyond the financial numbers. I believe we’ll see an index or metric that measures where companies rank according to values like sustainability or technology ethics. The spectrum of a CEO’s success will grow beyond just looking at pure financial numbers. It won’t just be black and white anymore.
“Remote work will not only impact employees, but also the C-suite. They might be very geographically diverse and disparate. I think it’s going to be a bigger challenge than what we see today. For most large companies, the C-suite is all in one location. In the future, the C-suite may be very distributed. You might have the CFO in Asia, the CEO in the U.S., the CMO in Europe, and the CSO in Australia. Driving synergy among a distributed C-suite will be critical. Using newer technologies that are evolving will be key.
“I believe in 10 years, we’re going to see C-suite meetings very much like we used to see in Star Trek 20 years ago—not necessarily teleporting, but using virtual reality to engage.”
of business leaders believe that by 2035 every organization will have a Chief Artificial Intelligence (CAI), working in a human-machine team with the CEO to make business decisions.