Kolawole Bekes is a Database Administrator, Database Reliability Engineer, and DevOps Engineer with over a decade of experience spanning multiple industries. He holds a Bachelor’s degree in Mathematics from the University of Abuja. Following his relocation to the United States in 2015 and subsequently to Canada in 2017, he has built a career working with organisations such as Microsoft, AppDirect, WorkJam, Sunwing Airlines, Agio, and Big Fish Games. 

He is also the founder and chief executive officer of WakaMi, an on-demand errand service platform focused on delivering reliable and efficient errand solutions to Nigerians both locally and in the diaspora.

• Explain what you do to a 5-year-old.

Once upon a time, there was a big fruit garden where fruits kept falling everywhere—apples here, bananas there, and oranges rolling all over the ground. Nobody could find what they wanted.

So I became the helper of the garden. I picked up all the fruits and put them into the right baskets; apples in one basket, bananas in another, and oranges in their own place.

I also made sure the fruits stayed fresh and safe. Whenever someone came looking for a fruit, I could quickly say, “I know exactly where it is,” and give it to them right away.

My job is to keep everything neat, safe, and easy to find, just like the fruit baskets in the garden.

• How did you become a Database Administrator?

I became a Database Administrator as part of a deliberate effort to improve my earning potential and build a more reliable career path. I joined a community of IT professionals in North America, where I was exposed to new ideas and opportunities. 

Through that network, I discovered and enrolled in a bootcamp, completed several training sessions, and gained hands-on experience. I then applied to multiple roles, and eventually secured an opportunity that marked the beginning of my career as a Database Administrator.

• What is the easiest and most difficult part about your job?

The easiest part of my job is when systems are well-structured and everything is running smoothly. Tasks like monitoring, backups, and routine maintenance become very straightforward.

The most difficult part is handling unexpected issues, like performance bottlenecks or outages, especially under time pressure. But that’s also the most rewarding part, because it challenges me to think critically, troubleshoot quickly, and ensure systems are restored with minimal impact.

• If your job had a warning label, what would it say?

Warning: Unexpected issues may occur at any time. Requires patience, quick thinking, and a strong relationship with coffee.

• What’s one real-world incident where your database decisions directly saved (or cost) a company big time?

Early in my career, I was involved in a deployment where a change was made directly in production without a proper rollback plan. Unfortunately, it caused a temporary disruption to a critical service.

Although we resolved it quickly, it highlighted the importance of change management. From that point on, I enforced stricter deployment processes introducing staging validation, rollback strategies, and better communication.

It significantly reduced risk for us in future deployments, critical because it now shapes how I approach database changes today.

• As a first-time founder living abroad, what is the hardest part about building a startup for a market where you’re not physically present? How do you deal with this?

One of the hardest parts of building a startup remotely while living in Canada and operating in Nigeria is maintaining strong team alignment and accountability when you are not physically present day to day.

Early on, I experienced challenges with staff management, particularly around consistency, ownership, and productivity. Some team members struggled with structure, and it became clear that the issue was not just about effort. It was about clarity, expectations, and systems.

To address this, I shifted my approach in a few ways. First, I implemented clear performance metrics and deliverables so everyone understands exactly what success looks like. Second, I introduced regular check-ins and reporting structures to improve visibility. Third, I focused more on hiring for accountability and cultural fit, not just technical skills.

I also make it a point to spend time in Nigeria periodically, which helps reinforce relationships, build trust, and reset expectations with the team.

Overall, the experience taught me that managing a remote team, especially across different environments, requires intentional structure, strong communication, and the right people in place. Once those are aligned, performance improves significantly.

• What’s the vision behind WakaMi and why do you think a marketplace for managed services can scale in Nigeria?

The vision behind WakaMi came from a personal experience. While living in Canada, I needed someone to handle an errand for me in Nigeria. I tried finding help online, but unfortunately, I had a bad experience where I lost money.

That led me to dig deeper, and I realised this was not just my problem. Many people, especially those in the diaspora, face the same challenge. There is no reliable, structured way to get trusted services done remotely in Nigeria.

WakaMi was built to solve that. It is an on-demand managed services marketplace that connects people who need errands or services done with verified service providers. It also provides oversight by tracking progress and only releasing payment once the task is completed and confirmed.

I believe it can scale in Nigeria because it addresses a real and growing problem. As more Nigerians live and work abroad, and as urban life becomes busier locally, the demand for trusted on-demand services will continue to increase.

What makes it scalable is the combination of trust, structure, and technology, bringing accountability into an otherwise informal market. Once you solve trust at scale in a service marketplace, growth becomes a natural outcome.

At 1 a.m., 23-year-old Tomi* was lying on her bed, exhausted and overwhelmed. She had just finished pouring her heart out, ranting about everything from unrequited love to the suffocating weight of underachievement. Her fingers hovered over her phone screen briefly before she typed: “I just want a hug.” Messages of reassurance came just about a second later:  “You’re safe here. You matter. And you’re not alone. ” 

This exchange didn’t take place in a therapy session or with a friend. It was happening on ChatGPT, a general-purpose artificial intelligence assistant best known for summarising and writing better emails, drafting reports, and explaining complex ideas. 

Tomi isn’t alone. Across Nigeria and even globally, users are turning to AI tools like ChatGPT for more than productivity. They are asking chatbots if they are good people, if they should leave their partners, or how to make sense of childhood trauma.  For many, AI tools are standing in for friends who didn’t pick up a call or therapists they cannot afford.

Twenty-three-year-old Favour* started using ChatGPT as a study companion for her final-year project. When she returned to using the tool again, post-graduation uncertainty had set in. The chatbot allowed her to unpack the weight of the previous year,  the terrors of job hunting, and the long wait for NYSC. “It’s not like I couldn’t talk to anyone,” she said. “I just wanted to rant.” 

Before ChatGPT, she would make private voice notes to get things off her chest, but once, a reply from the chatbot caught her off guard. “It told me, ‘I want you to breathe. Just breathe.’” That “felt really personal,” she said. Since then, she has returned to ChatGPT in moments of doubt, after an argument, while applying for jobs, or wondering whether she should’ve responded better in a confrontation.

Can AI really care?

Chatbots are built on statistical prediction engines trained with massive datasets like books, online conversations, magazines, and more, to produce responses that sound human. But when a bot tells you, “you’re not alone,” is it truly being kind or simply mimicking kindness?

According to AI researcher and medical doctor, Jeffery Otoibhi, designing an AI chatbot that responds empathetically involves modelling three layers of empathy: cognitive empathy, where the bot recognises and validates a user’s feelings; emotional empathy, where it feels with you; and motivational empathy, where it offers a solution, advice, or encouragement.

He explains that the chatbots are strong at cognitive and motivational empathy, but empathy remains elusive, because at its core, AI responses are “based on the statistical patterns they’ve (AI bots) picked out from their training data. The training data cannot provide emotional empathy.”

There is a tension between what users feel and what bots are designed to offer. Chatbots like ChatGPT often include disclaimers in their responses, reminding users that they are not licensed professionals and should not be used as a substitute for therapy. In many cases, users either don’t read the fine print or simply don’t care. “Sometimes, I’ve thought about the fact that ChatGPT may use this info in another way. But I don’t care. Let me just get it out,” says Favour. 

“I see them (disclaimers). I just quickly look away,” Tomi says about the app’s terms and conditions.

Otoibhi also highlights the possibility of reducing complex human emotions into an average response based on what it has seen most often in its dataset. AI models learn and generalise over statistical patterns, he explained. This means that their emotional understanding might be very generic. As human beings usually have a mix of emotions, AI systems might struggle with such concepts because they’ve been trained to generalise over everybody’s data. “So, they will just pick out the most frequent emotion in the data set,” he said. 

Tools like ChatGPT do not get at the heart of a problem the way a human therapist does; they are calculating your likelihood of feeling a particular emotion in that moment based on all the data they’re trained on. If the comfort isn’t real, then why do people keep going back?

“It gives me hope…”

Ore*, a Lagos-based writer in her 20s, explained why she uses the tool this way: “It’s the idea that there’s something available out there that is echoing my thoughts back to me. It makes me feel better about myself as a human. It makes me feel good; it gives me hope.” Many users I spoke to echoed the same reasons: safety, comfort, availability, lack of judgment, and freedom.

“AI is like a safe space. A place where you can be brutally honest and you know for sure that there’s not going to be judgment,” Favour says. 

For some, even when the responses feel artificial, they still return. “I asked ChatGPT for a hug. I was uncomfortable with its response. I know you’re not human, how can you say you’re wrapping me in a hug?” says Tomi. The next day, she went back to the chatbot to pour out more emotions.

Mental health professionals are not surprised. They say that the timing of people turning to AI for comfort is not random. A World Health Organisation research revealed a 25% increase in the global prevalence of anxiety and depression, following the COVID-19 pandemic. 

“After COVID, people went into isolation, got into their shells, and became more into themselves,” said Boluwatife Owodunni, a licensed mental health counsellor associate. “So, having an AI respond that, ‘I’m here for you,’ might provide them with some sense of comfort.” 

With therapy services often being inaccessible and unaffordable for many Nigerians, Owodunni believes AI is stepping in to fill a very real gap in mental health support. “It (AI) is filling a gap. When I was working as a therapist in Nigeria, it was mostly wealthy people who had the opportunity to be in therapy.” She adds, “But the downside is that it’s fostering secrecy and stigma attached to mental health.”

Some users consider AI more dependable than a human therapist. Ore says a human therapist told her to “practice mindfulness,” following an Attention-Deficit/Hyperactivity Disorder (ADHD) diagnosis. She felt her concerns were brushed aside, so she turned to ChatGPT. “That felt more supportive as opposed to a 30-minute virtual consultation with my psychotherapist.” She insists that, unlike the vague reassurance she got in therapy, the chatbot offered a structured plan and practical ways to cope with ADHD.  

Where does the future look like?

As AI systems evolve and are trained on more complex data, fine-tuned for context, and sharpened to mimic empathy, it raises the question of how far people will go to deepen their connection to AI. Will human-AI companionship grow as these systems become more emotionally intelligent? Not everyone is excited by that possibility. 

Some users have expressed concern over AI becoming too emotionally intelligent, out of fear that it could cross boundaries that should remain human. 

Kingsley Owadara, AI ethicist and founder of Pan-african Centre for AI Ethics, believes that emotional intelligence in AI can be useful, but not in the way most people imagine. “AI could be made as a companion to people with health challenges, and could meet the specific needs of the person,” he said, pointing to cases of autistic and blind people. 

Other AI experts and developers warn against expecting too much from machines that aren’t built for the full spectrum of human care. “AI can only augment our current situation; it cannot replace psychologists,” Ajibade adds.

The concern isn’t abstract. Mental health professionals and AI experts worry that as more people turn to AI for emotional support, real-world consequences could unfold. “We’re going to have a huge problem with social interaction, with empathy, with sensitivity, with understanding people,” says Owodunni. She notes the bigger fear that widespread reliance on AI bots may “foster secrecy and the shame attached to mental health or seeking therapy services.” 

Still, for many users, the AI chatbot isn’t trying to be a therapist; it is the only space where they feel heard. “I told AI that I was tired,” Tomi says. It said, ‘I know. You’ve been carrying so much for so long. It’s okay to feel tired.’” She didn’t reply. She didn’t need to.

*Names have been changed to protect privacy.

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