Is South Africa’s corporate culture ready to accept AI?

It’s difficult to find any news platform, social site or publication that isn’t abuzz with AI news. Personal opinions range from the holy grail to the end of days, fluctuating wildly between delight and fear.

Globally, AI brings a great deal of hope and excitement, and with South African businesses having always been early adopters in the tech space, the same is true in our country. But the course of “digital transformation” doesn’t always run smoothly. A 2021 study on big data showed that while corporate investment in data and AI had continued to rise, various metrics actually showed a decline in the success of those investments. There are a variety of factors at play when companies struggle to get the most out of their investments — from unclear corporate strategy to lack of the right skills and outdated internal processes — but corporate culture is a critical part of the puzzle. The companies leading the AI revolution are those with corporate cultures that enable their people to innovate, test and develop AI-driven solutions.

There are five key indicators of an AI-ready culture. The first is being learning- and purpose-led.

There are eight primary culture styles common in organisations, based on two factors: independence vs interdependence in terms of its people; and flexibility vs stability when confronting change. Of those eight styles, learning and purpose stand out as the two styles most common in AI-ready organisations.

Purpose is exemplified by idealism and altruism, places where people try to do good for the long-term future of the world, where leaders emphasise shared ideals and contributing to a greater cause. Learning is about exploration, expansiveness, creativity — open-minded workplaces where people are united by curiosity and leaders emphasise innovation, knowledge and adventure.

While purpose may be driven by corporate strategy, the availability of AI-related skills is the biggest challenge in its adoption by South African companies. Companies that want to adopt AI will have to train people internally very actively to start with, because it will take time for a critical mass of university graduates and others to come through the system. This is similar to data scientists, who are coming through the education system now, but companies have had to build up skills internally with their existing workforce to keep pace with requirements.

The second indicator of an AI-ready culture is being structured and data-driven. Simply giving employees free time to experiment won’t amount to progress unless combined with a structured, data-driven approach. The top innovators balance learning cultures with a focus that ensures everything is measured and backed by data. At Amazon Web Services, for example, company-wide presenters are required to submit a written document to fellow employees that demonstrates the data backing any assertions in the presentation, at which they will be expected to face questions about any of those assertions. The point is that in AI-ready cultures, exemplary presentation skills or a slickly produced document only matter up to the point that they are backed by data. This focus shifts the emphasis from style to substance, encouraging deeper, more thoughtful innovation.

Locally, Checkers Sixty60 dominates online grocery shopping because the company moved the fastest, was innovative and has learnt as it has gone; it has benefited from first-mover advantage in the process. Checkers Sixty60 sits within ShopriteX, the Shoprite Group’s digital innovation hub that brings together data science and technology to drive innovation and more personalised shopping experiences. By having access to data from across the group, collaborating closely with the businesses it serves and relentlessly driving a culture of learning and agility, ShopriteX can support Shoprite Checkers in leading the rest of the market in AI development and adoption.

Organisational culture starts at the top, so if the CEO and exco are against adopting AI, the rest of the organisation will follow suit and people lower down who want to adopt AI but are blocked from doing so will leave and go to an organisation that is more open to it.

The third indicator is ethical awareness. As AI expands boundaries and opens new doors, there are understandably many concerns about what it will mean for society; after all, prognosticators and sci-fi writers have been pondering these consequences for decades.

For companies at the forefront of the AI revolution, it’s critical to have a culture attuned to AI’s ethical risks, along with an ability and willingness to have the hard conversations about what it will mean for their company and society. How will AI be used? How do you address transparency concerns? Are you monitoring whether AI is encouraging or hampering inclusivity and diversity? These are questions the leading AI companies are not afraid to either ask or answer.

The fourth indicator is risk tolerance. Risk tolerance is not about overlooking all risks or accepting unacceptable ones. Smart organisations never take risks when it comes to ethics, including issues related to compliance, legal integrity and moral responsibility; ethical failure compromises the organisation’s core values and public trust.

But they do accept, and even encourage, entrepreneurial risks when it comes to experimentation, new tools and markets, product innovation and unconventional business strategies. It’s not about failing faster but about learning faster from your failures. It’s necessary for growth and adaptation in a rapidly changing business environment.

In developing and struggling economies such as South Africa, companies can be slow to take risks, but it can be costly to catch up later. Smart risk tolerance is aligned with long-term perspective. It recognises that true innovation and significant organisational improvements often require time to develop and may involve setbacks along the way.

Leading South African fintech Weaver Fintech, which owns the PayJustNow payment platform, has embraced AI across its credit risk assessment and customer service channels. At the company they believe that the right technology must be applied, balanced with the right risk strategy. Their philosophy is to follow their true north, which is always the customer, and continue to develop, invest and optimise tools to deliver on customer needs. It is clearly a strategy that is working, as the company is onboarding more than 100,000 new customers a month into its ecosystem.

The fifth and final indicator is collaboration and cross-functionality. AI initiatives require a blend of diverse skills and perspectives, from technical expertise in data science and engineering to domain-specific knowledge and business acumen. Encouraging collaboration across departments and teams ensures an environment where innovative ideas are shared, different viewpoints are considered and holistic solutions are developed.

In collaborative cultures, employees from various disciplines are encouraged to work together on AI projects, breaking down silos that traditionally separate technical and nontechnical departments. This ensures that AI solutions are not just technically sound but align with the company’s strategic objectives and address real business needs. For instance, cross-functional teams at companies such as IBM and Salesforce have been pivotal in developing innovative AI solutions tied closely to customer needs and business strategies, while many legal departments are using AI to check contracts to save time and costs.

Collaborative, cross-functional environments lead to more inclusive cultures that are better aligned with broader goals. In terms of AI, leadership by example is critical for a well-rounded implementation that delivers real business impact.

An AI-ready culture starts at the top. Leadership, from the CEO to the rest of the C-suite and the board, must believe that AI provides an opportunity to do business more efficiently and more cost-effectively. This means having not only the processes, strategy and infrastructure to support it, but a culture that encourages people to experiment, learn and grow along with the technology.

Guy Lundy is South Africa country manager at Spencer Stuart. Fabio Moioli is a consultant in Spencer Stuart’s Technology, Media, Telecommunications & Services Practice in Italy. 

The big take-out: The companies leading the AI revolution are those with corporate cultures that enable their people to innovate, test and develop AI-driven solutions.