The 2026 AI Governance Playbook

Happy New Year! Welcome back to the lab. We hope your January is behaving itself and your detty December bills haven't come back to haunt your bank account.

You know how we do it at Kini AI. We are full of curiosity. We’ve spent years ooh-ing and aah-ing at how AI can write Wole Soyinka-level poems, code faster than a senior developer, and generate images that look like they belong in a gallery in national museums. But this is 2026. It’s safe to say the honeymoon is over. We’ve seen the magic tricks; now we want to know how the magician stays out of trouble.

Conversations are increasingly moving from "What can it do?" to a more senior man question: "How do we manage this thing without it driving us into a ditch?" 

To break this down, we sat down with a woman who’s at the intersection of big tech and big responsibility— Bimpe Afolabi. She’s a Partner at KPMG Nigeria, working in their Governance, Risk, and Compliance (GRCS) team. Between her doctoral research in AI and her wild career pivot from Petroleum Engineering to governance and compliance, Bimpe is the professor we need for this masterclass.

The Mom Who Learned Python

You’d think an industry like Bimpe got into AI through a grand corporate strategy born in a long boardroom meeting.  Lai lai. It started in her living room! With her kids!

During the COVID lockdown, she hired a Python tutor for her children. But after a few weeks, she noticed they were just playing with the classes. In true Nigerian parent fashion, she thought: "Ah gosh! You guys can’t waste my money!" So, she started learning Python with them. What started as parental supervision turned into a deep dive into Machine Learning. And today, with over 25 years of experience and a Doctorate in view, she’s bridging the gap between old-school boardroom governance and the cutting-edge mathematics of AI.

This is the first lesson for leaders: You cannot govern what you do not understand. If you’re a leader and you think AI is just "that thing the IT boys do," you’re already behind.

Decoding Governance: It’s Not Just Red Tape

When Africans hear governance, we tend to think of bureaucracy. We think of the police stopping you at 11 PM to ask for particulars. We think of delay. We think of people trying to stifle our hustle. We think of oppression.

But Bimpe breaks it down simply: Governance is just a structure that helps you perform well. Let’s think about it this way: If you’re building a house and you build it anyhow, without a proper foundation and supervision, it only takes one small rain to drag the whole thing down. This is the kind of problem governance exists to prevent — or cure.

In AI, governance shouldn’t be confused for a roadblock; it’s the guardrail. Bimpe highlights that it is the guardrail that ensures that your deployment of AI is appropriate, accountable, and, ultimately, successful.

The Trusted AI Framework: A Framework for African Business

In our conversations, Bimpe shared a robust universal framework for African corporations that don’t want to wake up to PR nightmares. Consider these as the Ten Commandments (not literally but, you know?) that must be followed to avoid crumbling under pressure.

We can break them into two buckets:

1. The Value-Driven Principles

• Fairness: Does your AI do ojoro? Biased data = Biased result. your data is biased, your result will be biased. You can’t train a model on only Silicon Valley data and expect it to understand a market woman in Onitsha or Maasai.

• Accountability: Who are we holding when the algorithm messes up. You can't just point at the computer and say, "It’s the machine." Someone must take the heat.

• Transparency: Are we open about how our tools work?

• Explainability: Are we open about how it works? If you can’t explain the logic behind an AI’s decision, then how can you or the users trust the result?

2. The Human-Centric Principles

• Safety & Security: Is the physical deployment safe for humans?

• Privacy: Are we protecting people's secret data, or is it leaking like a broken pipe?

• Reliability: Can we trust the tool to work every time, or will it fall our hands when we need it the most?

• Sustainability: Is the system built to last without harming the ecosystem?

The Hallucination and Bias Dilemma: Context is King

Bimpe dropped a very heavy truth during our chat that every stakeholder in the AI ecosystem needs to paste on their wall.

She said: "If you ask an AI to analyze a Shakespeare novel, it’s easy. But ask it about a novel by D.O. Fagunwa (the legendary Yoruba author of 'The Forest of a Thousand Daemons'), and the AI will start to hallucinate."

Why? Because the machine hasn’t "read" our stories. It doesn't know our proverbs, our nuances, or our reality. If we blindly import Western AI models without checking the context, we are basically using a map of London to navigate the streets of Mushin. We will get lost. Governance helps us verify the source. It forces us to ask: "Is this reliable for us?"

The Olopa Paradox: Why We Need the Brakes

Bimpe laughed when she told us people call her team the "Olopa" . She even wanted to be a policewoman when she was a kid!

But she leans into it: "The truth is, we need to be policed." A Ferrari has high-performance brakes not just to stop, but so the driver has the confidence to go fast. AI needs policing (guardrails) so that innovation doesn't drive us off a cliff. Machines learn what we feed them. So you can imagine the gbas gbos we’re likely to encounter when If we feed them without guardrails.

The Balance:

• Policing: Putting policies in place to stop machines (and people) from doing aseju! (Overdoing)

• Innovation: Allowing disruption to happen within those safe boundaries.

This brings us to the concept of the human in the loop. Don't just outsource your brain to the machine. You need a real person —someone with a heart and a conscience— checking the output to make sure it aligns with the facts and with your values.

Oya, Watch the Full Jist!

If you’re the type who likes to see the "action" live and direct, I’ve got you. Words on a screen are great, but hearing Bimpe break down these frameworks with her own voice is a different level of "brain-reset."

Click below to watch the full deep dive on our YouTube channel. We went into the weeds on everything from career pivots to the future of African data.

Kini Big Deal

As Rotimi Awaye, the CEO of Kini AI and the interviewer, noted during the chat, "If your values do not care about the impact your business has on other people, then AI is not going to be helpful for society at large”.

The 2026 Playbook isn't just about writing cleaner code or building faster solutions. We have to consciously care about the fabric of our society. As we automate the core of our lives, we cannot afford to outsource our critical thinking or our integrity.

To all African leaders, developers, and creators: Be the Olopa of your own systems. Build the structures. Check your data. Don't do aseju without a plan.

Let's build tech that actually respects the soil it’s standing on.

Stay curious. Stay grounded.