Why African enterprises are struggling to turn AI ambition into impact

By President Ntuli, Managing Director of HPE South Africa

AI has moved beyond buzzword status in Africa’s boardrooms and is now the big bet for growth and resilience. CEOs are channeling significant investment into AI technologies and talent, signaling bold ambitions to transform their businesses. Yet, despite this enthusiasm, widespread implementation remains elusive. While KPMG research shows that 71% of African CEOs are investing in AI, only 27% report organisation-wide deployment, according to PWC, lagging behind the global average of 32%. The gap between intention and execution is stark, and it raises critical questions.

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 compute 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 compute 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. Instead, they should look to solutions like HPE Private Cloud AI which provides a pre-configured, validated platform that removes the complexity of building your own environment.

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. Drawing on years of AI-focused expertise, HPE demonstrates that effective governance is rooted in a holistic approach—anchored by validated, pre-integrated, modular AI infrastructure and consultancy offerings proven in real-world deployments. With this kind of foundational support, organisations can embed best practices from the start, rather than retrofitting them later. Governance should never be an afterthought; it must be the bedrock of sustainable success.

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.