The past few weeks have been turbulent for global tech. Public markets have wobbled,, and analysts have begun whispering about a coming “SaaSapocalypse” — a correction driven by a simple but destabilising fear: that AI will hollow out legacy software businesses.

From boardrooms in San Francisco to trading floors in New York, investors are asking whether the SaaS model — built on subscription-based access to general-purpose digital tools — can survive in a world where AI can replicate workflows instantly and at marginal cost.

Billions have already been wiped off software valuations as investors reassess what customers will continue paying for when intelligent systems can draft contracts, reconcile accounts, manage pipelines, and make decisions autonomously.

Watching this unfold from Addis Ababa, through the lens of what we are building at Gebeya, I see something different: validation. In my recent piece for The AI Journal, I argued that Africa owning its AI application layer is an economic necessity. The turbulence now shaking global tech markets reinforces that argument.

Access Is Not Ownership

Here’s why. Much of today’s AI conversation is framed as “democratization.” Models are cheaper, tools are more accessible, and barriers to entry appear lower than ever. But Africa has learned a hard lesson over the past two decades of digital adoption: access to a tool is not the same as ownership of the outcome. AI expands what people can make, but it does not automatically change who owns the systems where value is created, distributed, and accumulated.

This distinction is where the application layer matters. The application layer is where intelligence is translated into real-world action — where AI is embedded into workflows, payment systems, decision processes, and economic relationships. It is where data becomes insight, insight becomes execution, and execution becomes value. Whoever owns this layer controls how productivity gains are captured and compounded.

Without a deliberate shift toward building this layer locally, AI risks becoming another extractive cycle. African creativity, data, and labour will fuel intelligent systems whose value ultimately accrues elsewhere. Productivity may rise, but ownership will not. This is the structural risk hiding beneath the optimistic rhetoric of AI access.

SaaS Models Destabilized

The current market correction exposes why this matters. For decades, SaaS companies thrived by packaging business logic into subscription-based interfaces: CRMs, HR platforms, accounting software, legal workflow tools. These products justified recurring fees through dashboards, configuration, and standardised processes. AI has now destabilised that logic. Large language models and autonomous agents can replicate many of these functions directly, without requiring users to navigate rigid interfaces.

What once required months of onboarding and expensive licenses can increasingly be handled by agents that reason dynamically and act autonomously. Investors are realising that many SaaS products are little more than thin layers of logic sitting on top of databases. If AI can interpret context and execute tasks directly, those layers lose their value.

Yet while the Global North scrambles to retrofit AI into legacy software stacks — or watches those stacks erode — Africa starts from a different place. We never adopted SaaS at scale. Across the continent, businesses did not build their operations on expensive foreign subscriptions.

This “lack” of SaaS penetration is not a disadvantage. Quite the opposite. African enterprises are not weighed down by bloated software architectures that must be protected. They are already accustomed to operating across fragmented systems, with challenges like intermittent connectivity. That reality aligns much more naturally with dynamic and responsive AI agents, not with traditional software dashboards.

The Agent Era

This is why Africa can move directly into what I call the “Agent Era.” The future is not about software that you use. It is about agents that do. Instead of logging into systems and managing workflows manually, users delegate to agents that are able to interpret context, reconcile data across systems, and execute actions autonomously. Value shifts away from interfaces and toward intelligence embedded in economic activity itself.

The question is whether this intelligence will be designed around African realities. Agents built for environments defined by mobile money rather than cards, intermittent connectivity, local languages, and informal supply chains cannot simply be imported or retrofitted. They must be designed with these conditions in mind from the outset. While many global firms now describe their products as “AI-native,” being truly relevant in Africa requires starting from a different set of assumptions altogether.

Ownership is the deeper issue beneath all of this. For too long, African businesses have rented digital infrastructure built elsewhere. We have been users, not architects; subscribers, not owners.

But the destabilisation of SaaS models shows that this infrastructure is no longer as stable as it once appeared. As software gives way to autonomous agents, there is an opportunity to rethink who controls the intelligence layer of the economy. The incoming Agent Era offers a chance to build platforms where African developers and enterprises own the intellectual property of the agents they create.

Sovereign Tech for Africa

This shift is not about layering AI on top of existing software. It is about building platforms that lower the barrier to creating and deploying intelligent agents, regardless of technical background or formal education.

Platforms such as Gebeya Dala point to how agent-based systems could be built and owned locally, lowering the barriers to participation while keeping intelligence close to the markets it serves.

When these platforms are supported by local cloud and compute infrastructure, they also point toward a more sovereign and context-aware approach to AI deployment.

Seen this way, the so-called “SaaSapocalypse” is not a warning for Africa. It signals the end of an era in which generic tools built elsewhere captured most of the value. The more important question has never been whether AI would replace software, but who will build and own the intelligence that runs the next economy.

From Addis Ababa, the choice feels clear. Africa can either consume AI as a tool, or it can own the application layer where outcomes are shaped and value compounds. The Agent Era makes that choice unavoidable.

Amadou Daffe is CEO and co-founder of Gebeya, where he works on AI platforms and agent-based systems designed for African market realities, including local infrastructure, languages, and payment systems.