From Babcock to Boardrooms: How One Nigerian CEO Is Making AI Actually Work

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When the applause faded at Babcock University School of Computing, the room stayed quiet. Students, lecturers, and visiting founders had just listened to a story that felt uncomfortably familiar. It was the story of a Nigerian company that almost hired its way into a recession, then chose Juliet instead.

Twelve months earlier, inside PressOne Africa, the growth & expansion plan looked perfect on paper. Revenue was growing, customer numbers were climbing, and inquiry queues were piling up. The team prepared roles for one hundred new account managers. It looked like the normal answer. More customers, more staff.

Before anything was signed, the founder, Mayowa Okegbenle, asked for one simple review. He asked and sat with three sets of numbers.

The first was response time. Some customers were still waiting long minutes, sometimes longer, to get help. The second was the support queue during peak periods. Tickets kept stacking up faster than they cleared. The third was the reality of training. New hires were taking months to learn what the agents who had been there for 18 months already knew from experience.

When he added the projected salary bill for one hundred more people to that picture, the pattern became clear. The company was not short of hands. It was short of a shared brain. Knowledge sat inside a few strong performers. Every extra person added weight, but not wisdom.

He told his team something, we are following the usual playbook, and this playbook is failing us.

At that point there were only two honest choices. Keep hiring and hope that size would somehow solve a systems problem. Or pause, and do the hard work of pulling out the judgment of their seasoned staff, and putting it inside a system that could be present for every customer at any time.

They chose the second. That decision became Juliet.

Juliet is an intelligent customer success system built on artificial intelligence by PressOne Africa. She is grounded in African business context and real customer journeys. She answers questions, guides customers through setup, spots where people usually get stuck, and can support thousands of customers at the same time, in the same clear local language that human agents use, any hour of the day.

Inside PressOne, the impact has been blunt. Average response time has dropped to about three seconds. Human involvement in first line support has fallen from around one hundred percent to about five percent, while customer satisfaction sits near ninety two percent. Juliet has saved millions of naira in planned headcount and allowed the team to shelve that one hundred person hiring plan.

This was the heart of the story Mayowa shared at Babcock during the twenty fifth anniversary of the School of Computing. The applause in that hall was not only for an old student who had built something impressive. It was for the hard truth inside his experience.

He summed it up in one line that stayed with the room, you cannot automate what you have not systematised.

Many African founders will recognise parts of this picture. Data sits in different tools. Processes live in chats and memory. Customer records are spread across notebooks, phones, and spreadsheets. In that reality, a rushed artificial intelligence project does not fix confusion. It multiplies it.

PressOne had always taken structure seriously. Even then, before a single line of code was written for Juliet, the company had to go deeper. The team pulled data from different systems into a clearer view. They tightened definitions and closed gaps. Top agents documented answers that used to be passed around in private messages. They refined the journey from first contact to successful use, and agreed on what success meant for each type of customer. For companies that have not yet done this level of work, this preparation will be the hardest and most important step.

Only after that did Juliet make sense.

Today, when a small retailer in Ibadan or a logistics company in Abuja needs help at two in the morning, Juliet is awake. She gives the same guidance a strong human agent would give, and she learns from every interaction. Each answer she gives makes the system a little clearer. The company does not only move faster. It becomes smarter.

For leaders watching from the side, the lesson is not that every company must build its own Juliet. The lesson is that artificial intelligence only works when it is sitting on top of clear thinking. From the PressOne journey, Mayowa now repeats three rules.

Start with boring but expensive problems. Long response times. Repeated questions. Confusing onboarding. These are not glamorous, but they quietly destroy trust and cash.

Measure what matters. Know how many customers you serve, how long they wait, where things break, and what that delay costs. Without honest numbers, artificial intelligence remains an interesting story, not a working tool.

Fix your data by documenting before you fix your model. If your logs are loose and your processes live only in the heads of a few heroes, no model will rescue you. You will only automate confusion.

Underneath these rules is a deeper change in how African founders must see themselves. Many were taught to worship hustle. The chief executive who never sleeps, who joins every call, who signs off on every small decision. That energy is useful at the beginning. Later, it quietly becomes the ceiling that stops the company from growing.

At PressOne, Mayowa has shifted his own role. His job is no longer to sit in the middle of every customer conversation. His job is to build systems that work even when he is not in the room. Juliet is one of those systems. She does not get tired. She does not forget. She does not ask for transport refund. She also forces the company to make its best knowledge visible, clear, and teachable.

That is why the Babcock story matters for boardrooms as much as for classrooms. It is not a fairy tale about a clever bot. It is a simple path any serious business can follow. Face the real numbers. Admit where the playbook is failing. Do the quiet work of fixing processes and tightening data. Then use artificial intelligence to scale the intelligence you already have.

PressOne Africa is already living in that future. The real question for every reader of this page is simple. Do you want to keep hiring and patching your way around broken systems, or do you want to do the hard work that makes intelligence, human and artificial, finally worth the name. Juliet is one example of what becomes possible on the other side of that choice.

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