The value of AI lies not in replacing humans, but in empowering humans to be more human

Many of the current conversations around AI focus on AI as a tool – what it can do and what it can’t – which misses the point of what this transformation actually means. To leverage real value from AI, we need to focus on the bigger picture of transformation for our businesses and our economies. Focusing solely on AI as a utility function to simply streamline something we are already doing, much like the way we use all other technologies, will not get us very far. Conversely, having the right thinking without the right tools will still cause significant limitations. It has become imperative to develop AI fluency as a way of creating meaningful, differentiated value.

MJ Petroni, a Cyborg Anthropologist who studies the relationships between humans and technology, spoke on the topic at the 2024 Think Summit. He explored how we need to unlearn our default thinking to use technology to do more of the same, but more accurately and at a faster rate, and shift towards how we can solve the unsolvable problems to create a real paradigm for change.

“One of the first changes that needs to happen inside companies in order to be effective, is to move from having IT as a utility function, like plumbing, that supports the current business, to having digital as a capability within the business. This isn’t an easy task for most businesses,” he says.

The challenge is that our default thinking is based on past experience. Often the result is that we repeat the same things over and over again. Doing more of the same will never yield transformational results.

“In a place and time where the rate of change is so high that every day is the slowest you will ever live in, our default thinking is not enough to get us to the future. We have to do uncomfortable work to unlearn our default thinking, otherwise what we use technology for is just more, better, faster,” he adds.

In the era of generative AI, we need to break the cycles that were based on an analogue world. Cost cutting alone by automating all the human tasks away, leaves no room for innovation. The value in AI lies not in replacing humans, but in augmenting people with new technologies to enable them to become more human, more empathetic, more connected. This in turn empowers them to solve unsolvable problems – taking time with cutting edge cases and VIP clients, serving people who were not profitable enough to serve in the past, banking the unbanked, revolutionising education.

“Our bias towards action can be counterproductive. Instead of constantly asking ‘what do we do next with AI?’, we need to ask, ‘are we thinking about this right?’. It is not an incremental process, it is an exponential change, but if you apply incremental thinking to exponential technology, you will only get incremental results. When you have exponential technology and exponential thinking, you can generate more exponential results,” says Petroni.

Organisations need to have directionality on the future state of the business, rather than having a specific destination in mind. It is also important to set the expectation inside organisations and inside systems that exponential network effects take time to build. The success of these projects should be measured differently, in terms of network size, quality and growth rate. There is also a resource gap to be addressed. Businesses that wait until the last minute will find they are unable to hire people fast enough, build servers fast enough and buy GPUs fast enough to be ready to take on all these new possibilities.

Incremental gains like earning market share, increasing customer satisfaction and boosting revenue and profitability are important, but they don’t complete the picture. The key is to use the incremental gains that are possible with AI to streamline the organisation. It is also about funding exponential elements to help create new value and drive the future business with innovation in creating new products and business models, serving new customers, and even identifying new investment opportunities.

In Africa, the bias and lack of cultural context inherent in many existing AI tools has resulted in a lag in development, particularly around enterprise solutions that are affordable and culturally appropriate. This presents an opportunity for AI in Africa to accelerate and very quickly overtake established economies. Generative AI can radically lower the cost of creating startups or small businesses or entrepreneurial projects inside organisations. The risk is that jobs that have been offshored or outsourced are the easiest to replicate using AI. We need to become more proactive about talent and build talent pipelines that include the skills required in an AI economy, to remain competitive.

“Be cautious of the hype and the thinking that just giving people the tools will cause the breakthrough you want. To leverage maximum value from AI, we should focus not on replacing humans through automation, but on empowering humans to be more human through augmentation. To do this, we need to shift from thinking of machines as tools, to thinking about machines as co-workers,” Petroni concludes.