AI is no longer just a buzzword in African boardrooms. It has become a central pillar in plans for growth and long-term resilience. CEOs across the continent are committing serious capital to AI technologies and skills, underscoring ambitions to reshape how their organisations operate.
President Ntuli | image supplied
But execution is falling behind intent. While KPMG research indicates that 71% of African CEOs are investing in AI, PwC data shows that only 27% have rolled it out across their organisations, below the global average of 32%.
The disconnect between aspiration and delivery is clear, and it raises hard questions about what is holding large-scale adoption back.
HPE’s global research points to a key culprit: “the confidence trap”. Many enterprises overestimate their AI readiness, creating blind spots that undermine success. In fact, according to the HPE study, fewer than half of global organisations consider their deployments successful, and more than a third of use cases deliver only limited impact.
This research, titled One year on: Architecting an AI advantage, offers valuable insights into what’s holding businesses back and, more importantly, how leaders can close the gap.
It highlights the structural and strategic challenges that must be addressed for AI to shift from a future promise to a practical tool for efficiency, smarter decisions, and long-term resilience.
Fragmented approaches undermine success
Piecemeal strategies rarely deliver transformative results. Most enterprises acknowledge that a holistic approach, spanning strategy, resource allocation, and infrastructure, is essential to unlocking AI’s potential.
However, many organisations are doing the opposite. Instead of a unified roadmap, disconnected strategies emerge within the same enterprise, creating silos and slowing progress.
Locally, this fragmentation often stems from uncertainty. Leaders know they need AI but aren’t sure where to start. The result? Fractured goals and misaligned priorities. Different business units pursue their own objectives without a shared vision, diluting impact and making success harder to measure.
It’s clear that leaders need to establish enterprise-wide AI goals and foster collaboration across departments. By defining shared priorities and integrating efforts, organisations can move from incremental gains to meaningful transformation.
Data maturity still holds businesses back
If AI is the engine of transformation, data is the fuel, and right now that fuel isn’t flowing freely. Robust data management is non-negotiable for AI success, yet data maturity remains alarmingly low.
According to KPMG, 96% of African CEOs cite data readiness as a challenge. This isn’t just a technical hurdle; it’s a strategic roadblock. Without high-quality, well-governed data, even the most advanced AI models will fail to deliver meaningful outcomes.
Businesses must prioritise local data curation and governance frameworks to support advanced analytics. Competence in shared data models and centralised intelligence will be critical to turning fragmented datasets into actionable insights that drive growth.
Solutions such as HPE’s Data Fabric Software can support this shift by providing a unified data environment that simplifies how diverse data types are accessed, organised, and governed across edge‑to‑cloud settings.
By helping teams work across silos with greater consistency and control, such platforms enable analytics and AI initiatives to operate on reliable, well‑managed data foundations, ultimately accelerating an organisation’s ability to turn information into strategic advantage.
Infrastructure barriers persist
The rise of generative AI, and now agentic AI, has sparked a wave of innovation among computing and networking providers. New solutions promise to accelerate the shift from pilots to full-scale production, addressing capacity, performance, governance, and security. On paper, the path to scalable AI looks clearer than ever.
The challenge is that enterprise fluency hasn’t kept pace. Many global leaders lack confidence in understanding computing and networking requirements across the AI lifecycle.
Too often, organisations assume that existing infrastructure, patched together with internal components, will suffice. However, the reality is that most lack the in-house expertise to design, develop, and deploy AI-ready environments.
Without the right foundation, AI initiatives stall before they can deliver meaningful impact. Managing project pipelines becomes a struggle, and scaling efforts feel out of reach. It’s therefore no surprise that KPMG found that 32% of African CEOs cite integrating AI into core operations as one of their most pressing challenges.
Compliance, ethics, and security are falling behind
A resilient AI strategy begins with trust, and that means embedding ethics, compliance, and security from the outset, including critical considerations like data sovereignty and the choice between public and private cloud environments. HPE’s research, however, suggests the opposite is happening.
It reveals that across global enterprises, collaboration with legal and HR stakeholders during AI strategy development is declining when it should be intensifying. Even more concerning is the drop in CISO-level involvement - a surprising shift given today’s escalating threat landscape.
This is not a minor oversight. Indeed, according to PWC research, nearly half of African CEOs acknowledge that AI could amplify legal liabilities and reputational risk.
No matter how well an AI prototype performs in controlled conditions, it can fail spectacularly if it isn’t stress-tested against real-world security, regulatory, and IT environments.
AI models should undergo the same rigorous due diligence as physical supply chains and product manufacturing. Without this, organisations risk brand damage, breaches, and costly fines.
Enterprises must work with vendors and developers to ensure modern compliance, ethical standards, and robust security practices.
African CEOs are doubling down on AI, with 26% planning to allocate over 20% of annual budgets to it according to KPMG, nearly twice the global average. But investment alone won’t deliver impact. Success demands a holistic approach that ensures scalability, governance, and security from day one. By aligning ambition with more strategic implementation, African leaders can position AI as a catalyst for transformative growth.
