Corporate leadership is already struggling to keep up with the connected workforce and increasing speed and complexity in the digital economy. But looking ahead to the rise of algorithmic and human-machine co-working, the situation is even more worrying. A reboot is overdue.

Today, the idea that a small group of senior leaders can understand every area of a complex business and make all key decisions themselves seems unlikely. Tomorrow, it will seem ridiculous. So how can leadership work in the age of algorithms, and how can leaders become force multipliers for the people, machines, and code around them — without becoming a barrier to progress?

Senior executives speak of the enormity of digital disruption, but, even so, few use digital and social tools regularly. I was just on a C-level panel discussion in which three of the four panellists were not on Twitter. In the last two conferences I attended, only one industry keynote included their social network coordinates on their slides.

I may sound critical, but I have strong personal empathy for these leaders. In June, I joined a small company in which my teammates – and our clients – collaborate all the time on Slack, wikis, and other flexible tools like Trello, and ship deliverables in two-week sprints. Even with constant exposure and an intense forcing mechanism, it took me months to adjust to this rhythm of working. But although it is uncomfortable and time-consuming, it is every leaders’ responsibility to regularly use digital and social tools and participate in the networks that they enable.

After all, there is a difference between speaking digital and living digital.

To Lead Is To Master The Network

In his book The Seventh Sense, Joshua Cooper Ramo makes the point that we now live in a world where “thick connection is normal” and the mastery of this connection is the essential skill of the age. This is true for everyone, but it is particularly true of our leaders – political, religious, and business.

Not surprisingly, tech companies – and their executives – get it. Uber and Lyft use algorithm “managers” to dispatch drivers, while Waze outperforms my Volvo’s sat nav by predicting the best route based on the real-time and stored driving data of its users.

But, really, business leaders in all industries need to master the network, not in some mid-distant future, but now. We are interacting with algorithms every day, in ways so mundane that we fail to notice (Google, you auto-complete me). And in professions as diverse as medicine, manufacturing, and law, we see viable examples of human-machine teams.

So how does one lead in the age of algorithms? To lead is to master the network. 

This topic deserves – and has already garnered – significant study elsewhere. But for the purposes of exploring at a high level – and frankly, for my personal commitment to my own development – I set out here to address four questions:

  1. Will we need leaders?
  2. What will leaders do?
  3. What skills do they require?
  4. Who will lead?

Bots Need Managers Too

We will still need leaders, although we no longer need to conflate leadership and management. Many management activities – from status reporting to enforcing policies – are ripe for automation. So we will probably have fewer managers, and that will have a positive economic impact. Gary Hamel suggests that by doubling the average span of control – today, companies average 1 leader for every 4.7 individual contributors – and redeploying half of the managers, we would see a $9 trillion rise in economic output in OECD countries.

The automation of management makes the space for true leadership, which as my colleague Cerys Hearsey writes, centers on leveraging emotional intelligence, adaptive thinking, and creativity.

For starters, human involvement guards against the unintended consequences of algorithms. What happens when the bots are not managed? The British pound crashes to a 31-year low in minutes due to overly-aggressive trading algorithms, or someone siphons millions by exploiting a code vulnerability in an organisation that claimed code was law. In his analysis of the DAO heist, my colleague Lee Bryant argues that there is a huge role for algorithmic management within organisations, as long as it serves, rather than governs, human purpose.

Four Emerging Leadership Scenarios In The Age Of AI

If we still need leaders, then what will leaders do? Generally, they will manage in one (or more) of four scenarios:

  1. Leaders manage the work of machines. For all their power, algorithms behave differently from humans, which means they still need our discernment and wisdom to keep from going astray. They are extremely literal and so require our understanding of lateral context and nuance. They make stunningly accurate predictions, but still need us to interpret why an event is likely to happen.
  2. Leaders manage human-machine teams. How do we get people and machines to work in harmony? Automation is unusable if untrusted by humans. Leaders will engender this trust on hybrid teams by training people on how automation works, and providing teams members with the information to anticipate the machine’s responsibilities. They will give their teams exposure to automation so people calibrate their expectations. These are fundamental principles of Trusted Autonomy – an emerging research discipline for designing human and machine interactions, which we believe will become critical to org design.
  3. Leaders use machines to manage the work of humans. For me, one of the most exciting implications of algorithms and data is their ability to enhance human decision-making in applications like legal e-discovery, medical diagnosis, or even criminal investigations. In practice, we see this paving the way for more people taking on the higher-order tasks traditionally reserved for leaders – such as physician assistants and paralegals capable of performing the same work as doctors and lawyers.
  4. Leaders create the space for distributed leadership in mixed human-machine environments. Building on the previous scenario, when machines and algorithms enrich human intelligence, more people across the organisation are able to make well-informed decisions about the best way to do their work and delight customers. Leaders in this environment must make the space for distributed decision-making and autonomy amongst these hybrid teams.

The Five Skills Modern Leaders Need

Recently, I wrote about the five attributes required to lead a digital generation (curious, serving, connected, inclusive, and situational). These attributes are slow-to-change, meaning that, if you don’t already display them, then you will need to go through a process of changing your mindset, behaviours, and – potentially – your fundamental beliefs.

In my view, you can add to these a set of five skills which are narrower in scope, and thus faster to change and see results. Leaders in the age of algorithms need to master:

  1. Basic data and statistical analysis. What does the data tell us? What is the difference between correlation and causality (and why does this matter)? How do you judge a source? You need to know how to answer these questions if you are to interpret and guide algorithms responsibly. At its essence, a basic understanding of data and how to interrogate it is the heart of critical thinking.
  2. Service blueprinting. I have written previously that if you are a leader, it is your responsibility to identify tasks that are currently conducted by your team but which you can automate, such as status reporting over email or cutting and pasting information into new systems. You cannot do this unless you know how work really gets done, and how it ultimately contributes to the customer’s experience. Service blueprinting offers a structured way to reveal these insights.
  3. Active Listening. Algorithms pursue objectives single-mindedly. In contrast, people take in a more holistic approach to completing a task. This human gift can prevent algorithmic misfires, but only if leaders give team members the opportunity to voice their perspectives and concerns. Simple management techniques like active listening surface not only what someone is saying, but also the message that they are trying to send.
  4. Proficiency with digital tools. Earlier, I mentioned my own learning curve with new digital tools and agile ways of working. This experience has been rewarding, but in the process, I have also felt awkward, slow, and out-of-touch. I may not have gotten through it without the positive support of my younger colleagues. I encourage every leader to seek out reverse mentors to build digital proficiency.
  5. Story-telling. Leaders need to inspire a shared creative vision for people to trust their machine co-workers. One of the most effective ways to inspire remains a classic, well-constructed narrative.

Leadership Can Come From Anyone

The beauty of these five skills is they support emerging leadership scenarios not only for teams encountering automation, but also, more generally, for teams with a growing number of digital natives. I expect that teaching these skills will only become more popular with business and HR leaders.

Still, there are practical questions to consider: how broadly do we offer this skills training? In what format?

While the individual context will vary, my general recommendation is to find the approaches and formats that train the broadest number of employees possible. We are shifting to a world in which leadership is less about formal authority or knowledge and more about experimentation and intuition to adjust to constant change. In this adhocracy, you can expect that leadership can – and will – come from anyone. You need a workforce that is prepared to lead.