How to Be a Successful Leader in the Age of Machines

Datafication, mobilization, cognification, and personalization are a few of the mega-shifts driving transformations in the world of business at an unprecedented pace. Here’s how you can overcome the significant leadership challenges presented by these shifts.
One may have doubts and questions about the risks and rewards of machine intelligence, but none can doubt its rapid advancement.
So many different aspects of our everyday lives are now Artificial Intelligence (AI) driven – from using face recognition to unlock your phone, to planning and arranging your daily commute. And, that’s not to mention the many, many exciting future applications of AI technology.
Is it any wonder that machine intelligence has been one of the hottest boardroom topics for the last few years?
Businesses are currently seeking to implement AI in existing products and services. Meanwhile, the race is on to design and develop the next greatest AI-driven products and services to make consumers’ lives that much easier.
And, the men and women who are leading these mega-shifts and paving the way for new AI-driven products and services to come through are no ordinary leaders. They are adapting to the changes in the business world and developing new skill sets to help them navigate these uncharted waters.
Smart Leaders Will Recognize that the Age of AI calls for New Leadership Skills
According to a recent study by The McKinsey Global Institute, “Nearly half the work people currently do can potentially be automated by adapting currently demonstrated technology.” It is imminent that employees of all levels may soon find themselves working with machines. As a leader, you may soon find yourself leading teams of people and machines.
Are you prepared to lead, manage, safeguard and inspire such a workforce?
Based on my experience of leading The Talent Games, Asia’s fastest growing AI-driven gamified recruitment platform, these 3 critical skills will help leaders thrive in the age of machine intelligence:
Agility
According to a survey conducted recently by Boston Consulting Group and MIT Sloan Management Review, 85% of interviewed executives were of the belief that “AI will allow (their) companies to obtain or sustain a competitive advantage”.
The reason for their confident and overriding belief is AI itself. It automates manual tasks, discourages entry of new competitors, and enables smaller teams to operate with the efficiency of a team thrice its size. Agile and adaptable leaders will make smart and effective decisions in this rapidly changing world to ensure that they can make the most of these benefits.
You can begin practicing agile leadership immediately by embedding agile business methodology into your organization model, and training your team on agile innovation methods. It is also time to start using data to stay informed about the changing competitive landscape, any possible threats to your value chain, and growing trends in your consumer base.
Diversification
Prioritizing diversification is key – and here I’m not just speaking about racial and gender diversity, but going beyond it as well. A diverse and multifaceted team is imperative to the success of all AI-driven products.
A lot of complex data science constitutes any machine-driven product or service. And utility and management of this data is contingent on the relationships between the people, cultures, and processes that surround it.
Diversity in the workforce (gender, cultural, racial and age-related) helps to prevent biases – algorithmic biases which could potentially hurt your brand and disrupt your products/services.
Don’t forget to prioritize diversity when it comes to your potential employees’ academic and disciplinary backgrounds.
Lastly, leaders should also encourage diversity in data sets for more accurate insights. Opting for a diverse range of data science methods also drives stronger performance because hybrid methods often deliver better results than stand-alone techniques
You will find that prioritizing diversity is beneficial in more ways than one: recent studies show that companies with diverse workforces have been linked to greater ability to attract top talent, not to mention greater profitability.
Engagement
Teams that work with AI will find themselves freed of many tedious manual and rote tasks that once consumed majority of their time and energy each day. Effectively, they now have more time and attention to focus on strategic and creative thinking. Leaders must be responsible for empowering team members to creatively problem-solve and bring their innovative ideas to life. This will help them deliver the most value to the company and to your cause.
You can immediately begin implementing the following strategies for effective workforce engagement:

Set clear objectives for your teams and give them the freedom to meet and exceed these goals.
Replace hierarchical structures in the workplace with a culture of collective decision-making and ownership.
Look into approaches such as team rotations, online feedback platforms, brainstorming workshops, and innovation groups.

Datafication, mobilization, cognification, and personalization are a few of the mega-shifts driving transformations in the world of business at an unprecedented pace. Here’s how you can overcome the significant leadership challenges presented by these shifts.

One may have doubts and questions about the risks and rewards of machine intelligence, but none can doubt its rapid advancement.

So many different aspects of our everyday lives are now Artificial Intelligence (AI) driven – from using face recognition to unlock your phone, to planning and arranging your daily commute. And, that’s not to mention the many, many exciting future applications of AI technology.

Is it any wonder that machine intelligence has been one of the hottest boardroom topics for the last few years?

Businesses are currently seeking to implement AI in existing products and services. Meanwhile, the race is on to design and develop the next greatest AI-driven products and services to make consumers’ lives that much easier.

And, the men and women who are leading these mega-shifts and paving the way for new AI-driven products and services to come through are no ordinary leaders. They are adapting to the changes in the business world and developing new skill sets to help them navigate these uncharted waters.

Smart Leaders Will Recognize that the Age of AI calls for New Leadership Skills

According to a recent study by The McKinsey Global Institute, “Nearly half the work people currently do can potentially be automated by adapting currently demonstrated technology.” It is imminent that employees of all levels may soon find themselves working with machines. As a leader, you may soon find yourself leading teams of people and machines.

Are you prepared to lead, manage, safeguard and inspire such a workforce?

Based on my experience of leading The Talent Games, Asia’s fastest growing AI-driven gamified recruitment platform, these 3 critical skills will help leaders thrive in the age of machine intelligence:

Agility

According to a survey conducted recently by Boston Consulting Group and MIT Sloan Management Review, 85% of interviewed executives were of the belief that “AI will allow (their) companies to obtain or sustain a competitive advantage”.

The reason for their confident and overriding belief is AI itself. It automates manual tasks, discourages entry of new competitors, and enables smaller teams to operate with the efficiency of a team thrice its size. Agile and adaptable leaders will make smart and effective decisions in this rapidly changing world to ensure that they can make the most of these benefits.

You can begin practicing agile leadership immediately by embedding agile business methodology into your organization model, and training your team on agile innovation methods. It is also time to start using data to stay informed about the changing competitive landscape, any possible threats to your value chain, and growing trends in your consumer base.

Diversification

Prioritizing diversification is key – and here I’m not just speaking about racial and gender diversity, but going beyond it as well. A diverse and multifaceted team is imperative to the success of all AI-driven products.

A lot of complex data science constitutes any machine-driven product or service. And utility and management of this data is contingent on the relationships between the people, cultures, and processes that surround it.

Diversity in the workforce (gender, cultural, racial and age-related) helps to prevent biases – algorithmic biases which could potentially hurt your brand and disrupt your products/services.

Don’t forget to prioritize diversity when it comes to your potential employees’ academic and disciplinary backgrounds.

Lastly, leaders should also encourage diversity in data sets for more accurate insights. Opting for a diverse range of data science methods also drives stronger performance because hybrid methods often deliver better results than stand-alone techniques

You will find that prioritizing diversity is beneficial in more ways than one: recent studies show that companies with diverse workforces have been linked to greater ability to attract top talent, not to mention greater profitability.

Engagement

Teams that work with AI will find themselves freed of many tedious manual and rote tasks that once consumed majority of their time and energy each day. Effectively, they now have more time and attention to focus on strategic and creative thinking. Leaders must be responsible for empowering team members to creatively problem-solve and bring their innovative ideas to life. This will help them deliver the most value to the company and to your cause.

You can immediately begin implementing the following strategies for effective workforce engagement:

  • Set clear objectives for your teams and give them the freedom to meet and exceed these goals.
  • Replace hierarchical structures in the workplace with a culture of collective decision-making and ownership.
  • Look into approaches such as team rotations, online feedback platforms, brainstorming workshops, and innovation groups.

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