Artificial intelligence has become a central theme in strategic boardroom discussions. Yet, for many South African organisations, the journey from AI experimentation to sustainable value creation remains complex.

To unpack this journey, TechCentral, in partnership with Altron, hosted an executive roundtable titled “Navigating the AI Value Creation Journey”. The session brought together C-suite leaders and digital innovators from across industries to share insights, challenges and strategic perspectives.

While AI is often discussed in the context of technology, the roundtable made it clear that the transformation it brings is far more human and organisational than it is purely technical.

Most organisations represented at the roundtable wre still in the early exploration phase of their AI journeys. Many are identifying high-impact use cases – particularly around operational efficiency and automation – but full-scale implementation remains a future goal. A recurring theme was the need to ensure that these initiatives are tightly aligned with broader business strategy from the outset. Participants agreed that AI initiatives without a strategic anchor tend to stall or fall into “pilot purgatory”.

The conversation also highlighted that AI success depends as much on culture and leadership as it does on data and models. In many businesses, cultural change is left until last – AI is often framed as a technical project rather than the organisational change initiative it truly is. Leadership needs to deliberately focus on readiness, literacy and engagement across all levels to empower teams to adopt and work confidently with AI tools.

Culture, change and the human link

Culture emerged as a powerful enabler – or barrier – of AI adoption. A key insight was that technology should not be seen as replacing people but rather as an extension of human potential. AI was positioned by participants as a way to amplify productivity, creativity and value – particularly when it can take on transactional tasks and free up human capacity for more relational and strategic roles.

However, driving this mindset shift requires more than intention. Attendees emphasised the need to engage leadership and executive teams early to build AI literacy, establish ownership and prepare for the significant change management effort required.

One of the more human challenges raised was around skills – not only the need to recruit or upskill data and AI professionals but also the difficulty of engaging long-tenured employees, especially those nearing retirement, in reskilling efforts. This was seen as crucial to ensuring the organisation evolves at all levels, not just in pockets.

Barriers and balancing acts

The discussion then turned towards the many barriers organisations face when trying to execute their AI strategies. Governance, data integrity, legacy infrastructure and siloed thinking were all seen as significant obstacles. In particular, the challenge of proving value and scaling AI in a way that is both measurable and sustainable came up repeatedly.

Participants noted that AI governance must go beyond compliance – it should include ethical considerations, value alignment and clarity on where responsibility lies. Some organisations are grappling with a lack of clear ownership of AI, highlighting the need for strong leadership structures and cross-functional governance models.

Another important tension discussed was the balance between innovation and risk, especially in a challenging economic climate. Executives shared how they’re prioritising AI investment: focusing on areas that promise near-term gains but with an eye on long-term transformation. For some, this means centralised AI capabilities that are then embedded in business units; for others, AI efforts are being led by digitally mature teams with other units playing catch-up.

Data realities and vendor complexity

The issue of data readiness was another recurring theme. There was consensus that perfect data is an unrealistic goal – and organisations need to become comfortable with a threshold of “good enough” to avoid paralysis. Data strategy and AI strategy are inseparable, and efforts to improve one must support the other in parallel.

The complexity of the AI vendor landscape was also discussed at length. With a proliferation of platforms and tools, participants highlighted the challenge of evaluating which partners to trust. Some expressed a preference for engaging with vendors where they had a degree of influence or relationship capital, in case things went wrong. Others noted that the build versus buy decision is becoming increasingly strategic – requiring clarity on where competitive advantage lies and how internal capabilities should evolve.

Ethics, ownership and future-focused leadership

Ethical use of AI was raised as a non-negotiable. Participants discussed the need for standards and frameworks that ensure AI is deployed in ways that are responsible, transparent and aligned to organisational values.

Looking forward, there was a strong sense that AI will fundamentally change how people are managed and how organisations think about leadership. Attendees explored whether their organisations were operating from a scarcity mindset – focused solely on efficiency – or from a growth mindset that embraces transformation.

To navigate this shift successfully, leaders must be intentional about how they embed AI into the fabric of the organisation. That includes reimagining operating models, redefining roles and ensuring that AI enhances – and not erodes – the human experience.

Conclusion

The roundtable made one thing clear: AI is not just a technology play – it’s a leadership challenge. Strategic success in AI will not come from waiting for perfect data, chasing every trend or outsourcing the problem. It will come from bold leadership, cultural alignment and a deliberate effort to integrate AI into the organisation’s DNA – ethically, sustainably and with a clear focus on value.

TechCentral and Altron thank all of those who participated in the roundtable discussion.