The Impact of Generative AI on Traditional Leadership – Redefining Business Performance with Generative AI

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In a world where Generative AI performs a number of skills better than humans, business leaders should rapidly rethink their skillset and develop 3 main new skills: “data sensemaking”, “reperception” and antifragility.


SwissCognitive Guest Blogger: Andrea Iorio, VP of AI – “The impact of Generative AI on traditional leadership – Redefining Business Performance with Generative AI”


It is a fact that ChatGPT has taken the world by storm, and that the way we generate written content on the Internet will never be the same. In just 5 days since its launch in November last year, ChatGPT gained one million users, a feat that no other popular online services have managed to achieve. As an example, Instagram is among those which come the closest, having achieved one million users in 2 months and a half.

Although the most popular by now, ChatGPT is not the only Generative AI tool, others include Midjourney and Dall-E for images generation, GitHub Copilot for coding, and even conditional generative adversarial networks (cGAN) such as Pix2Pix, developed by NVIDIA, that is used for image-to-image translation.

The truth is that the impact of AI on businesses, and even the world, is so profound that Andrew Ng, the former head of AI at Baidu and partner of the AI Fund, said that “AI is the new electricity”. It is actually generating so many new opportunities to businesses that want to generate new value through innovation that, if you allow me, I will get to the point of saying that it is “the new refrigeration”. Let me better explain what I mean by that: Warren Buffet always tells a story about refrigeration, saying that the person that invented refrigeration, of course, made some money, but most of the money was made by Coca-Cola, which used refrigeration to build an empire.

Generative AI can be seen as the “new refrigeration”, where there will definitely be some money made in it, but the big money will be made by the “Coca-Colas” of AI that have yet to be built, or by the traditional companies that are going to reinvent themselves via AI.
Overall, the AI market is so big that according to Precedence Research, while the global AI market size was estimated at US $119.78 billion in 2022, it is expected to hit US $1.59 trillion by 2030, with a registered CAGR of 38.1% from 2022 to 2030.

It is clear now that Generative AI represents a great opportunity for companies to optimize their workflow, generate efficiencies and scale their production of content, but a question keeps lingering in the minds of all of us: “If Generative AI is so good, will it soon replace me at work?”. Software developers look at the lines of code generated by Chat-GPT with a mix of awe and fear as much as copywriters, editors and many other professionals.
Even leaders feel the same. “I am expected to be the retainer of knowledge within the company, with the most experience, and now a chatbot comes in and supposedly knows more than me?”, they think.
But as with everything, there are two ways to approach the rise of generative AI as leaders. One way is, like the Luddites in XIX Century’s England, that would destroy weaving machines at night out of fear of their job being replaced by them (we know now it didn’t actually work!), to fight it off and believe that the traditional leadership role and skill set are never going to change.
Another way is to embrace the power of Generative AI, understand what it does better than us, and outsource all of that to it. The result? More time is available to focus on leading in a novel manner. Let me better explain how this works by mapping out what AI overall does better than leaders.

First of all, it is able to extract insights from infinite data sets – something that the human brain is not able to do, to the point that although we have much data in our companies, according to a recent Gallup survey, only 55% of leaders make decisions based on data (usually they are made based on past successes, beliefs, or pure “gut” feeling).
Also, it retains knowledge better than leaders, and therefore, it has better answers. Think about whether even the most experienced leaders can compete with a language model trained on 175 billion parameters, such as Chat-GPT?
Last but not least, AI is also more efficient than leaders at performing repetitive tasks, without getting tired or making errors, which can free up time for human leaders to focus on more complex or creative tasks.

These AI skills, which overlap with leaders’ skills but where AI proves to be much more effective, ask for a new leader’s skillset. One that transforms current leaders into what I call the “meta-leader”, namely the leader that is able to move past the traditional expectations related to leadership and understand that AI is an ally and not a threat.
Therefore, as I work closely with some of the most prominent leaders in traditional industries, I have laid out what are some of the new traits of the “meta-leader”, which are a direct consequence of the ability of Generative AI to perform the tasks described above better than us.

1 – “Data sensemaking”

The ability to better make sense of the insights generated by AI and to select the right KPIs to monitor.
What I mean by that is in a world where everything is measurable and where the volume of data generated reached 97 Zettabytes, data is now a commodity, at the same time where AI is extremely proficient at processing such data and generating insights out of it, the real challenge for leaders is to choose the metrics to be monitored and prioritized then extracting insights from them by “making sense” of all this data. The choice of these metrics and the correlations between them will bring about innovative insights that your competition may not even be looking at, leading to a competitive advantage for the leaders and companies. Imagine the following analogy: if companies were military jets, their leaders were AirForce pilots competing in a race to hit a very critical target, and they were all looking at the same panels in the cockpit. This only allows them to differentiate themselves to a certain extent when it comes to flying their plane because it will be difficult to get such unique and differentiated insights if they are looking at the same dashboard. But if a pilot extends their control panel to look at totally different indicators based on future expectations or external trends, they open up the range of possibilities for differentiation and competitive advantage and increase the likelihood of hitting that target.

2 – “Reperception”

The ability to ask better questions (rather than just providing pre-formatted answers) and to think critically about new business problems in a world that is changing very rapidly.
As mentioned previously, if Chat-GPT today retains much more knowledge than any human being, the true role of leadership pivots to asking better questions rather than just providing answers in order to better understand a world that is changing exponentially. It is a bit like holding a “beginner’s mindset” rather than just an expert’s mindset. Think of a 4 or 5-year-old child: studies show children at this age ask around 100 to 300 questions per day, but the same does not hold true for adults. A bit like these children, we have to constantly challenge our ego and get to “know that we don’t know” in a world of infinite information, and to ask the right questions to make up for this gap. This helps us practice reperception: it is no longer the leader’s ability to perceive that matters; it’s their ability to re-perceive by constantly rethinking and relearning. What was a good decision yesterday will not be the best decision tomorrow, so leaders need to rethink their decisions all the time in the face of new information and exponential changes. Again, this is something that only human leaders can do (for now): human reasoning is not just about logically combining existing knowledge to come up with a solution or critique of a problem. It is also about reasoning beyond the universe of current knowledge and using imagination to form new ideas, whereas Artificial Intelligence is able to only look for solutions from its current set of existing knowledge.

3 – “Antifragility”

The ability to learn from “smart mistakes” (leaving efficiency to AI, and embracing experimentation like a scientist).
Last but not least, if AI is so good to be mistakes-free, leaders should understand that their duty becomes to experiment more (and push for the same across their teams) in order to learn through some of the human mistakes and inefficiencies. And although this might seem off and counterintuitive, let me better explain how this works. Think of a scientist: I have always admired scientists for their ability to meticulously experiment and fail an infinite number of times before discovering anything new. Mistakes and failures are simply part of the discovery process, and if scientists weren’t willing to admit they were wrong at times, we wouldn’t have many of the technologies and advancements we have today. In fact, there wouldn’t have been any experiments to begin with. But leaders in businesses want to avoid making mistakes because they don’t want to deal with their consequences or the possibility of being perceived as weak or incapable of doing the job. The main and most obvious consequence in business is the financial cost. Then, there is frustration, loss of customers, reputation problems, inefficiencies, and many more. But I challenge you to think about the positive consequences. learning is one outcome. Then, when one person learns from a mistake and shares their learnings with someone else, they open the door for collaboration, which is another positive consequence. This also allows us the ability to discard options we know are less likely to benefit us when we aren’t sure which direction to go or how to solve a problem. Mistakes can also make us stronger because they make us more prepared for what’s next. Once we understand, we can learn from our mistakes, we can change our attitude towards them and start experimenting more. And it is not just about learning from our mistakes but using them to get stronger. This is an “antifragile leader” that allows herself to fail while exploring unknown territories in a world where AI guarantees effectiveness in the known ones.

The truth is that as technology changes, leadership must too, because all other change within an organization starts with the leader. Technological revolutions have always caused some degree of disruption, but what we are currently experiencing with AI will be far greater than ever before because of the high degree of exponentiality and because some AI skills (in particular, Generative AI) overlap human ones. This is why now is the time to start understanding and developing the necessary skill set to become the meta-leader your company needs and leveraging on the power of AI to grow your business even more.

Andrea will be speaking at the SwissCognitive World-Leading AI Network AI Conference focused on Redefining Business Performance with Generative AI on 28th March.

The Impact of Generative AI on Traditional Leadership - Redefining Business Performance with Generative AI


Der Beitrag The Impact of Generative AI on Traditional Leadership – Redefining Business Performance with Generative AI erschien zuerst auf SwissCognitive, World-Leading AI Network.

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