David Swanagon is the Head of People Analytics, North America for Ericsson. He is an award-winning data scientist and HR professional.
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Today’s marketplace has fundamentally changed the ways of working. The pace of innovation, alongside the endurance of Covid-19, has created an environment where digital fluency is critical. As part of this, emerging technologies such as the metaverse and augmented reality have opened the door for machines to outpace humans in terms of employee count.
Looking ahead, it’s possible that skilled professionals will work for multiple employers. This Uber nature of talent will push the boundaries of leadership theory, requiring a new mindset for how to attract and retain top talent. The future requires a thoughtful approach to artificial intelligence (AI).
Outlined below are 10 principles that I believe will help leaders prepare their teams for the digital era.
Learn the data science alphabet. Moving forward, talent leaders will need to develop robust skills in the areas of applied statistics, machine learning operations (ML Ops) and neural networks. The alphabet song, “A is for apple, it’s red and it’s green,” will change to, “A is for ARIMA, it’s stationary and lean.” For those who didn’t catch the stationary reference, it’s a sign that you need to learn the alphabet.
Microsoft Excel is to data science what Saturday Night Fever is to dancing. If you ask me, the Bee Gees is an amazing band that transformed the music industry; likewise, Saturday Night Fever (not its sequel) is one of the greatest movies ever made. However, times have changed and so too have the dance moves. Excel is a useful supplementary tool. That said, if you’re relying on spreadsheets as your main move, you’re going to struggle to find a dance partner in the future of work.
Remember that machines don’t change human nature. As the saying goes, “Power corrupts and absolute power corrupts absolutely.” Though the Terminator movies postulate that machines would follow a similar arch if they became self-aware, the reality is that ego and selfishness are human constructs. Our frailties are the shadow side of our strengths. You cannot have kindness without meanness, or courage without cowardice. The role of machines is to serve as multipliers for existing behaviors.
Make sure that every employee has a seat on the digital bus. The future of work requires employees to develop digital fluency. Emerging topics such as the metaverse, augmented reality and wearable technology create a myriad of opportunities to engage employees. However, those opportunities demand a culture that embraces technology. It’s critical that leaders reserve enough seats. Don’t make your employees walk.
Leading AI requires significant investment. Jack Welch, the former CEO of General Electric, stated, “Before you are a leader, success is about growing yourself. When you become a leader, success is about growing others.” In terms of AI leadership, executives should engage AI/ML platforms the same way they do people. Consistent effort is needed to improve the efficacy of digital assets.
Establish a meaningful career path for technical employees. By 2040, it’s hard for me to imagine that any C-level position will be occupied by a non-technical leader. At that point, it’s possible that machines will outnumber people in terms of employee counts. To prepare for this scenario, companies should establish technical pathways that lead to the CEO’s office. This includes balancing digital fluency and soft skills.
Set up recurring meetings with your AI platforms. Part of leading machines is treating them with respect. In a business context, machines add value through automation, customer insights and integration. If an individual completed these tasks, leaders would prioritize their development. AI models require a similar talent commitment. Top-performing models should be identified and scaled.
It sounds crazy, but many of us may report to a machine. A machine supervisor may seem like a bridge too far. However, I would argue that this situation is already happening. Today, AI is driving resume screenings for new hires. Recommender apps are used to suggest learning courses. Monitoring tools are in place to track meeting utilization. There are even bots to handle separations. The point is that AI is fully embedded into human resources. Therefore, the formalization of a bot manager is not far off.
Ensure that data governance and employee privacy are proactively managed. Data privacy is part of the employee experience. In today’s marketplace, the threat of data breaches by cyber hackers is high. Leaders should ensure that teams understand the risk of data breaches. This includes building privacy into the value proposition while providing adequate training on data protection and chain of custody.
Pay attention to slow adopters. Though resisters cannot stop the digital bus, they sure can delay its departure. As part of building an AI culture, the key is to make digital fluency nonnegotiable. When it comes to digitalization, leaders should ensure that slow adopters have adequate training and support. This includes ending any longstanding manual processes.
Though artificial intelligence remains an emerging topic, the field provides a significant opportunity for executives to improve the efficacy of their teams. By embedding digital fluency into the talent culture, leaders can ensure that machines are adding value. Effective strategies include learning the data science alphabet, making sure employees have a seat on the digital bus, creating dual career paths, fostering data privacy and proactively managing slow adopters through training and the elimination of manual processes.
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