By Geoff Masuta – MTN Group Head of Advertising

AI is taking over marketing in ways that make traditional methods feel as outdated as sending faxes, and global industries are rapidly integrating AI driven marketing solutions to enhance consumer engagement and business intelligence.

It is fair to say that the African continent faces unique challenges and opportunities in adopting AI powered marketing technologies, and many African organisations still rely on traditional infrastructure that lack the scalability and flexibility necessary for AI driven marketing.

Until quite recently Africa has been a passive consumer of technology, relying on imported solutions for years to fully participate in the AI revolution, critical gaps in cloud adoption, energy sector and skills development – all areas that need to be addressed.

It is like preparing for a marathon, but first you need to get the right shoes and equipment.

Cloud adoption in Africa: The need for adaptation

As businesses move to embrace digital transformation, cloud technology is revolutionising how companies store and process data, providing the flexibility, scalability and innovation needed to stay competitive in today’s fast-paced market.

Understanding the key cloud trends and how they impact industries is critical for African businesses to stay ahead of the curve.

Scalable cloud infrastructure

African businesses are fast realising that they need to compete on a global stage in the AI market, and this means that they need to transition from legacy on-premise systems to scalable cloud infrastructure [McKinsey, 2024].

Simply put, this means employing a cloud computing system that can easily adjust its resources (like processing power, storage, and network bandwidth) up or down depending on demand, allowing businesses to quickly scale their operations based on their current needs without experiencing performance issues.

To make this transition effective, it is necessary for companies to invest in 2 key areas – infrastructure (data centres, etc.) and skills development.

Currently, Africa is home to about 85 data centers with South Africa, Nigeria, Kenya and Egypt leading the charge [AfricaDCA, 2023]. However, this represents less than 1% of global data centres, illustrating a significant gap in local AI processing power.

While major players like Google, Amazon and Microsoft are setting up shop across the African continent, the infrastructure remains inadequate to support widespread AI adoption.

So, what does this mean for marketing in Africa?

Limited cloud resources translate to slower AI adoption, compelling businesses to either rely on expensive international cloud services or struggle with local systems that don’t have enough computational power.

This seriously deters African marketers from deploying real-time AI driven campaigns, recommendation engines and data analytics at scale.

To overcome this, in an ideal world, technology ecosystem would look like this::

• Attribution is algorithmically driven (ROI is no longer a guessing game)
• Embedded AI, reinforcement learning and multivariate testing enhance campaign performance
• Real-time AI and ML capabilities drive predictions and optimisation strategies on the fly
• Integrated decisioning engines combine business rules and analytical models from complex decisions
• Journey builders include interaction-level management for things like targeting, frequency capping and NBO recommendations

Notwithstanding all this potential, cloud adoption remains a fundamental hurdle for African marketers and will remain so unless and until we focus on expanding our cloud resources.

Skills development

Even as cloud services expand, Africa faces a critical shortage of skilled professionals in AI and cloud computing. The demand for cloud architects, engineers and data scientists far exceeds supply.

To close this gap, organisations on the continent must invest in AI focused training programs and partnerships with global technology firms to build a robust talent pipeline that goes beyond basic tech literacy and aims to cultivate the next generation of AI experts.

The talent is out there but this investment in skills is not about plugging a talent hole, it’s about creating a future where AI can truly take off. Without a skilled workforce, Africa cannot unleash AI’s full potential in marketing and beyond.

Unstable power supply

AI systems require a continuous supply of electricity for high performance computing and data processing – something Africa is clearly not yet ready to provide.

More than 30 African countries currently experience power shortages and regular interruptions in service, leading many to rely on very costly leased generating plants as an emergency stopgap.

In South Africa, Nigeria and Angola, power cuts and reliability issues have forced many businesses and residents to rely on backup diesel and petrol generators or SHS to compensate for electricity shortfalls.

In South Africa the scenario is still dire. We struggle to illuminate all households – let alone provide enough power across industries – and national energy supplier Eskom has yet to fulfill the national generation capacity, recently plunging the country into darkness once again as load-shedding made an unwelcome comeback.

This energy instability disrupts operations, increases costs and discourages investments – making AI adoption less viable. Without addressing Africa’s power challenges, AI driven marketing advancements will face limitations, restricting business growth and digital transformation across industries.

Application of AI in marketing

AI driven Customer Data Platforms (CDPs) and Data Management Platforms (DMPs) are essential tools for marketers looking to curate and activate both online and offline data. This is especially relevant when moving beyond simple data unification to integrating channels and delivering personalised experiences. AI in marketing not only improves efficiency but enhances customer engagement.

AI driven A/B testing has traditionally been a manual process for most organizations, requiring marketers to create multiple variations of assets. AI automates this by continuously testing and applying optimisation in real-time.

AI has also reshaped digital advertising by automating media buying. Machine Learning algorithms analyse huge amounts of data to identify high performing ad placements and refine targeting through AI driven ad copy and visuals based on audience engagement and conversion rates.

Big corporates use AI driven recommendation engines and chatbots for personalisation and customer engagement strategies. AI powered recommendation engines enable Next Best Offer (NBO) systems by suggesting roaming packages before travel [in telco]; offering a customised loan based on income patterns [banking and insurance]; and recommending complementary products based on past purchases [ecommerce], etc.

By fostering a robust AI eco-system, African organisations can transition from being passive technology consumers to active innovators in the global AI marketing landscape.

With a little more investment and a focus on building a formidable army of skilled professionals, our continent has the potential to do what it tends to do best – pioneer new innovations that set the standard for the global industry.