As African governments race to draft AI strategies, data protection frameworks and digital economy blueprints, a critical question is emerging: can regulation enable innovation without suffocating it?
- •For Salesforce Africa Lead and Country Manager Linda Saunders, the answer lies not in deregulation, but in collaborative policymaking.
- •At a time when AI policy across the continent remains fragmented, Saunders argues that Africa’s readiness for enterprise AI will hinge less on hype and more on three fundamentals: regulation, infrastructure and culture.
- •In this interview with The Kenyan Wall Street, Saunders speaks about Salesforce, regulation, what policymakers and innovators need to do to get this moment right.
“Governments need to come to the table with business partners, citizens and major technology players so that we can design a roadmap that protects citizens but doesn’t constrain competitiveness,” she says in an interview with The Kenyan Wall Street.
Across the developed world, slowing population growth is reshaping labour markets. In contrast, Africa’s demographic dividend positions it as both a talent engine and a high-growth digital market.
Saunders says this duality makes Africa strategically important in Salesforce’s global roadmap. “Africa is not just a sales market. It’s a skills market. It’s an innovation market,” she notes, pointing to the continent’s youthful workforce and rapidly digitising economies.
But she cautions that policy must strike a careful balance.
Governments, she says, are right to be cautious. AI governance cannot be reckless. Yet overly restrictive regulation risks isolating African businesses from global competition.
Each country, she argues, must define its own sovereignty objectives then align regulation to enable innovation within that context.
Financial Services Leading Against Expectations
Contrary to popular perception, Africa’s most regulated industry is currently the most aggressive in adopting agentic AI.
“Financial services has really taken to agentic solutions,” Saunders says.
This is notable because banking is traditionally risk-averse and compliance-heavy. Yet banks are leaning into AI for productivity, customer engagement and risk modelling.
Beyond financial services, Salesforce is seeing strong uptake in, telecommunications, retail, service-driven industries,. Surprisingly, public sector and healthcare adoption remains slower, despite potentially transformative citizen service use cases.
The Real Barrier: Misinformation, Not Technology
If infrastructure gaps are one constraint, Saunders believes misinformation is a bigger one.
Business leaders are inundated with conflicting AI claims. Distinguishing marketing from measurable capability is increasingly difficult.
“How do you know AI is real? Are tokens actually being consumed? Leaders need the intellectual muscle to ask the right questions.”
Cultural hesitation also plays a role. Job displacement narratives have fuelled anxiety. In emerging markets, where business margins are thinner, a wrong technology bet can be costly.
Yet Saunders believes AI skills are more accessible than perceived.
According to Saunders, Salesforce, which began as a cloud-based CRM pioneer, has evolved into "a complete value chain that supports the agentic enterprise.” Salesforce’s position centres on trust, particularly around enterprise data ownership. Unlike open commercial AI models that may train on user inputs, Salesforce maintains that customer data remains owned and controlled by the enterprise.
Through Salesforce’s Trailhead platform, individuals can build AI capabilities via gamified learning, challenging the idea that AI expertise requires advanced degrees.
“Skills are no longer static. The ability to learn and relearn will define the workforce.”
Trust, Data and the Sovereignty Debate
AI’s ethical and security implications remain a policy flashpoint.
Saunders distinguishes between consumer-grade AI usage, where individuals upload data into open models, and enterprise-grade deployments.
“If you’re putting sensitive data into a commercial model, can you guarantee it’s not being used to train that model?”
She emphasises that enterprise platforms must provide robust governance, permissioning and architecture controls, while customers themselves must strengthen credential security amid rising cyberattacks.
This layered responsibility model reflects a broader policy conversation unfolding across African capitals: data sovereignty versus global interoperability.
A Digital Native Economy
Saunders singles out Kenya as a particularly promising growth node. “Kenyans have a digital native mindset. It’s a vibrant economy with exciting use cases waiting to come to life,” she said.
As Nairobi positions itself as an East African technology hub, the interplay between private sector platforms and public policy could prove decisive.
Salesforce’s Africa expansion, including offices in Johannesburg and Casablanca, signals confidence in the continent’s trajectory. But Saunders stresses that success will depend on ecosystem alignment.
Looking ahead, she sees enterprise technology shifting from software-as-a-service toward what she calls “service as software” autonomous agents contracted to deliver outcomes.
Organisations, she argues, will increasingly blend human expertise with AI agents that operate beyond simple task automation.
