Tag: BusinessStrategy

There is a pattern emerging across boardrooms that is starting to look very familiar. Executives are excited about Artificial Intelligence (AI). Budgets are being allocated. Pilot projects are being launched. Early results are often promising. Yet, despite all this activity, very few organisations are seeing meaningful, enterprise-wide impact.

Digitalisation has brought, and continues to bring, sweeping advancements in how companies go to market and how customers engage with brands. Agentic AI is now poised to disrupt even these developments. As a result, organisations are scrambling to invest in the "next big thing" because they fear being left behind. However, history shows that when speed becomes associated with winning, companies often blur the line between operational effectiveness and strategy.

Much of the current conversation around Artificial Intelligence (AI) focuses on technology choices. Organisations ask which platform to use. They also ask which model works best. In addition, they debate which tools will replace existing systems. Across boardrooms and IT departments, leaders race to decide on AI platforms, copilots, automation layers and infrastructure upgrades.

Leaders are expected to plan for the future, whether they operate in big business, small business, government or good-deed organisations. And they do. Leaders collate data across all aspects of operations. They compare budgets with actuals. They also make projections for the next six months to five years.  Leaders build detailed quantitative models and dashboards. Some projections include both positive and negative outcomes.

Drift happens. Not because leaders lack intelligence. Not because the strategy was wrong. Instead, execution decays quietly and predictably under the weight of competing priorities, unclear ownership and fragmented attention. Ethiopian Airlines sustained commercial focus through five government transitions and became Africa’s most profitable carrier.

For years, the future of finance and accounting has been framed mainly as a story about technology. Artificial intelligence (AI), automation and data platforms are reshaping the profession. They are changing how work gets done and what employers and clients expect. However, if that is the whole story, we are missing the point.

South African businesses do not need to look far for a cautionary tale. The fallout from the Steinhoff scandal continues to reveal how weak governance, inadequate scrutiny of business relationships and unchecked transactions can destroy billions in shareholder value. What began as aggressive growth ultimately became one of the country’s most expensive lessons on the cost of insufficient oversight.

Many organisations believe they have a communication problem. Teams are working in silos. Messages are being misunderstood. Decisions are not filtering through. People are not taking enough ownership. However, these challenges often signal something deeper.

Resilience and agility are key competitive advantages for companies. CRM is still one of the most reliable ways to activate these qualities. When it comes to Customer Relationship Management (CRM) software, the conversations are complicated.

In a low-growth economy, organisations struggle to expand revenue. They therefore face increasing pressure to unlock efficiencies and do more with less. Consider a major South African bank. It recently celebrated a successful AI-powered fraud detection pilot. The results looked impressive. The system delivered faster detection, fewer false positives and measurable savings. Leadership felt energised.