For Chibuike Goodnews, artificial intelligence is not a buzzword bolted onto an advertising business for effect. It is the operating logic of that business. As the arrowhead behind Dochase ADX, a foremost African advertising technology outfit that says it pioneered programmatic advertising on the continent, Goodnews has watched marketing move from human guesswork to machine-driven precision, and he believes Africa’s advertising industry, along with the continent’s wider technology ambitions, sits at a decisive fork in the road.

Techpoint Africa sat down with Goodnews to talk about what intelligent marketing actually looks like inside a modern ad-tech operation, why he thinks Africa risks repeating a familiar historical pattern, and what business leaders on the continent need to unlearn before they can compete globally.

Machines may understand a product before a strategist does

Asked how artificial intelligence has changed the way his organisation approaches advertising, audience intelligence and consumer engagement, Goodnews traces the shift back to a period before AI became a mainstream conversation.

“Artificial intelligence has become the core of what we do at Dochase ADX,” he says, explaining that the company’s decision engine was already built on machine learning that determined who should see an advert based on data and the likelihood that a person would buy a product.

That early infrastructure, he argues, became the runway for full artificial intelligence, which extends machine learning by giving systems far greater autonomy and decision-making power.

The result, according to Goodnews, is that AI now touches almost every stage of an advertising campaign. It begins with understanding the product, a task historically owned by strategists. From there, the system determines creative direction, decides which banner, video or format a specific individual should see, and identifies the audience most likely to convert, all by reading data, browsing behaviour and consumer preferences. Work that once absorbed months of agency research, he says, can now be compressed into under a minute.

The automation does not stop at targeting. Goodnews describes a workflow in which AI recommends the tone and language of advertising copy for a given audience, a job traditionally assigned to copywriters, and then moves into content generation itself, producing banners and visual assets from little more than a product description or URL.

Once a campaign is live, the same system evaluates customer acquisition cost, ad spend and overall performance and returns recommendations on what platform or creative to adjust. “AI now influences the entire advertising value chain, from product understanding and campaign planning to execution, performance analysis and strategic decision-making,” he says.

A defeatist mindset around jobs

Much of the public conversation around AI in marketing circles back to job losses, and Goodnews does not dismiss the concern outright. Businesses “built around repetitive tasks will struggle to scale,” he says, pointing to a client that once needed a thousand people to complete a process and may now need only two, supported by the right tools. But he pushes back on the idea that this makes AI a net negative for African talent. Drawing a parallel with the Industrial Revolution and the dot-com era, both of which eliminated certain professions while creating entirely new ones, he argues that AI removes geography as a constraint on opportunity.

“Someone sitting in Nigeria can build AI agents for companies in Sweden, Norway, Cuba, or anywhere else in the world,” he says, describing the fear of job displacement as, in his words, “a defeatist mindset.” The more useful question, he argues, is not whether AI will take a job, but how that job is being reshaped and how a professional positions themselves inside the change.

That same logic extends into how he expects the advertising industry itself to evolve. AI-generated creative, once dismissed by industry insiders as artificial-looking, is judged by consumers on a different standard entirely.

“Most people care about whether the message is useful, engaging and persuasive,” he says, and brands, focused squarely on outcomes, will adopt AI-produced content irrespective of its origin if it drives sales. For agency professionals, he believes the shift demands a change in posture and that posture is informed by the fact that fewer people will be needed to deliver comparable results, but those who master the tools stand to create more value than before.

Marketing, he predicts, is becoming more accountable, more data-driven and more performance-obsessed than at any point in its history, as clients increasingly want precise answers on acquisition cost and campaign return rather than abstract brand narratives.

Building rather than importing

Goodnews is careful to separate enthusiasm for AI’s marketing applications from complacency about Africa’s position in the broader AI economy. He warns that the continent risks repeating its role from the industrial age, when it supplied raw materials but rarely captured the value created from them.

He points to AI training data and annotation work already done in African countries such as Kenya, arguing that the resulting models were not built by African companies and that the value generated from that labour largely flows elsewhere. His concern extends to the infrastructural layer beneath the applications everyone is excited about which are data centres, chips and the scale of investment that powers artificial intelligence globally, an area he believes Africa has under-prioritised in its rush toward the more visible, application layer of AI.

His prescription is that governments across Nigeria and the wider continent need deliberate policy intention rather than just passive optimism, he says, pointing to how leaders in more advanced AI markets act almost as advocates for their domestic industries. And African businesses, in his view, need a longer runway to experiment without demanding profitability from day one, an expectation he believes discourages the kind of bold, sustained risk-taking that produced companies like Amazon and Facebook in their early, unprofitable years.

For founders specifically building AI-driven ventures, his advice is, use AI to conduct deeper market research than was previously possible, surf in the blue ocean or better put, look for uncontested market spaces rather than crowded ones, design for global markets from day one, and treat continuous iteration as a requirement for survival rather than an option.

Ultimately, Goodnews frames intelligent marketing as one visible expression of a much larger contest over who builds, and who merely consumes, the AI systems shaping the next decade of African business. Dochase, he says, is one attempt at building rather than importing. “I want Dochase to be remembered as one of the companies that helped build Africa,” he says, describing a long-term ambition to help position Nigeria as a genuine technology leader rather than a downstream market for tools designed elsewhere.