AI and Talent Strategy in 2021: What Employers Need to Know

Faculty Insights Analytics

The world we are living in is quite different from two years ago when the College of Professional Studies (CPS) at Northeastern University held its symposium, The Intersection of AI and Talent Strategy.

Digital transformation is happening at the speed of light, creating opportunities as well as uncertainties, and COVID-19 has only further transformed how individuals and organizations interact in the networks we are building. 

The conference organizers recently went back to some of the symposium participants to ask how AI and talent strategy has changed 18 months later and how COVID-19 affects what they are doing in their organizations today. Here’s what they had to say. 

Common Expectations for a Changing World

We consulted many professionals on how COVID-19 is changing their work today and in the future. Here are common expectations:

  • The demand for experiential learning will further increase as it becomes increasingly difficult to find analytics, science, architectural, and engineering experience. The challenge is not the availability of talent; it is uncovering the best talent that possesses a combination of technical skills and tools, communication skills, and business acumen. For that reason, internships and experiential projects are required for students to learn technical and professional skills and competencies.
  • The reliance on data will further increase. For example, monitoring has become more important to control and simulate the spread of the virus. The need to use analytics and AI knowledgeably and ethically has also become even more apparent.
  • The demand for technology will further increase. Automation offers a potential solution to disruptions in the workflow, and IT, AI, and analytical skills are in high demand.
  • How we work will be different in the wake of the continuous spread of COVID-19:
    • The balance between project and time management will shift with more remote work.
    • It will become more difficult to communicate precisely and effectively.
    • Teamwork and leadership traits, including ambidexterity, agility, audacity, and acuity, will become even more critical.

This article is the first in a three-part series that builds on the key findings of interviews with symposium participants and other professionals, focusing on AI and talent strategy for 2020 and beyond. Part I discusses the need for experiential learning and successful analytics and AI talent strategies. Part II focuses on the interplay of humanics and technology. Part III offers humanics solutions for the human crisis of COVID-19. 

Part I: AI and Talent Strategy in 2020—Key Findings

Experiential Learning is Critical in the Digital Era

Experiential learning provides professionals with a better understanding of business, particular organizations, and new cognitive frameworks. Lambert Hogenhout, Chief Data, Analytics, and Emerging Technologies Officer at the UN, and many others agree that holistic education that embraces experiential learning is mandatory for success in times of digital transformation. 

“It was and is hard to find people on the advanced technical level,” he says. “There are lots of people that skim the surface and can do the easy tasks [like statistics, excel, working with databases], but it is quite difficult to recruit for the technical—the hard skills—for the architecture questions, where more experience is required. Furthermore, professionals that are successful in their current jobs are not leaving their jobs, and organizations try to hold on to them.” 

Chad Iverson, PhD, Senior Manager of Applied Intelligence at Accenture, explains that “the candidate pool of experienced AI professionals appears to be getting smaller.” 

Matt Moocarme, PhD, Director and Senior Data Scientist with ViacomCBS’s Advertising Science team, agrees. “The candidate pool, especially for data engineers, is getting smaller. That is a very underserved role; not too many people are applying for the data engineer role. That is, in my opinion, the most in-demand role. Every data scientist needs at least one data engineer to do the job effectively.”

Iverson continues, “On the other hand, there is an increasing number of programs that educate up-and-coming professionals with the skills we need in the workplace. But, it is more difficult to find and hire a professional with that experience already under their belt. Many organizations are developing talent internally and providing their current staff opportunities to gain experience in the workplace. One challenge in education I see is taking a learner through an entire project from beginning to end, especially in a six- or ten-week university class. Higher learning still needs to address that–it’s an unmet need.” 

Additionally, experiential learning is purposefully intertwined with soft, or professional, skills. Moocarme recognizes that and offers a possible solution. “Get internships to gain industry experience, and provide more classes in a program that is teaching soft skills. It is super beneficial to have soft skills—to understand why you are doing what you are doing, rather than predict the next number. Being able to trace back until to hit that root, and you work your way back. For students that have just the classroom environment, that is very hard.” 

Allister Duncan, Managing Director at Defined Calculus, agrees that most companies look for the following when hiring: 

  • Technical talent who actually have the technical chops aligned with their resumé content.
  • Effective problem solvers who ask meaningful questions and work collaboratively to deliver business solutions.
  • Solid communicators who have the ability to translate a complex technical insight or method to a non-expert.
  • Business acumen and the ability to see the bigger picture—not just delivering on the technical side.
  • A willingness to learn and improve irrespective of one’s experience level (in both technology and the business).
  • Professionals who possess a strong work ethic and appetite to succeed despite occasional setbacks.
  • Demonstrated humility, honesty, and integrity.

Northeastern’s College of Professional Studies designed its 2018-2025 Strategic Plan to embrace this responsibility as an educational institution. As stated in the plan, “[CPS] meets the future of work head-on by providing lifelong, on-demand experiential learning in high-demand fields, with curricula that incorporate the full range of capacities—data literacy, technological literacy, and human literacy—needed to make people robot-proof throughout their lives and whatever their starting point. Because we embrace this responsibility, we actively assess our impact on individuals and communities through the lens of inclusive prosperity.” 

Successful Analytics and AI Talent Strategies for 2020 and Beyond

In business, talent strategy is not only about hiring. The organization and hiring leaders are responsible for ensuring that a new set of digital leadership skills are taught and lived. This includes identifying the key specialist skills the business currently needs. 

According to Iverson, these skills depend on what the business is looking for and where your organization is on the data maturity curve. You should ask the following questions:

  • Have your organizational needs grown beyond your current data analytics capabilities? 
  • How are you trying to evolve your data science team? 
  • Are you trying to foster a tighter integration between analytics and your overall system architecture? 
  • Are you establishing an AI product owner practice to deliver on a vision? 

“In my experience,” he says, “the most effective AI staffing strategy acknowledges where an organization sits on the data maturity curve in the context of related business or mission objectives. For example, an organization that starts to realize value with just a few data engineers and data visualization professionals may first find they need more data analysts—and only later move on to hiring data scientists. If an organization already has a strong team of data scientists with advanced skills (e.g., predictive analytics), they may still decide to go deeper and seek out machine learning specialists. Depending on business needs, the same organization might also decide they need the breadth of skills that data and systems architecture professionals offer. Eventually, many organizations find they need staff with experience maturing data analytics capabilities, scaling data systems, and delivering AI and insights all the way to the edge, closer to the point of customer engagement.”

In times of COVID-19, another element comes into play: remote hiring. Hogenhout explains that society was “…already on the verge of working from home. We are now forced to do that, and everybody is discovering that it works very well, and we are getting used to it. Given the fact that everybody is working remotely now—and that some of that dynamic will likely continue in the future—it makes sense that those virtual teams be increasingly open to members located in any part of the world, which will increase team diversity and possibly reduce costs.” 

However, there are limits to virtual teams, says one VP of Data Science at a major pharmaceutical company. “We learned that we can’t offshore everything; we need some in-person teams, and data science is one of them. This structure also helps to define the purpose of the team. In-person teams are also better for custom work.” 

Hogenhout continues that remote hiring requires candidates with specific skills, including “self-discipline, professionalism, planning, and organizing. Nobody will look over their shoulder and remind them of deliverables. More of that onus of delivery is on the employee. Staying in contact with your colleagues requires team members to be much more proactive. The introvert that was carrying along in the past is now in a more difficult situation. Managers need to hone their managing skills to bring all along while working remotely.” 

Those leadership skills that must be refined are ambidexterity, agility, audacity, and acuity. “Success in this new world requires building a new set of ‘digital leadership’ behaviors—starting with top management and extending throughout the business,” said Michael A M Davies, Founder, Chairman, and Senior Partner of Endeavour Partners, during the 2019 symposium. 

For more, check out Part II and Part III of the series.