AI is making South Africa’s call centers pricier
NAIROBI, KENYA — South African business process outsourcing (BPO) call centres are facing escalating operational expenses as artificial intelligence (AI) adoption raises infrastructure requirements across compute, networking, memory, and hardware, reversing the assumption that AI will immediately lower the cost of service delivery for operators building AI-augmented contact center capacity.
AI infrastructure demands outpace call centre cost expectations
Sanjay Govender, head of GBS/BPO Solutions at Qrent, wrote in a published analysis that “the real cost of AI is not the software licence; it’s the infrastructure required to run it,” as global information technology (IT) spending is projected to reach $6.15 trillion in 2026, with AI-capable infrastructure costs accelerating for the past 18 months.
The cost acceleration spans compute, memory, networking throughput, and low-latency server environments, extending to endpoint hardware, where call centres have shifted requirements from Intel i5 to i7 class devices over the same period.
AI adoption is shifting call centre overhead from labour to infrastructure, and that infrastructure cost is running ahead of the AI productivity gains operators expected to fund it.
Govender: AI increases BPO operating costs rather than reducing them
Govender wrote that “AI does not run for free; it requires compute power, memory, networking throughput, low latency environments,” and that AI is “not automatically reducing operational costs inside BPOs” but rather increasing them in many cases, as AI tooling costs have stacked onto existing call centre infrastructure rather than replacing it.
For BPO operators in South Africa, the infrastructure decision spans three paths: absorbing higher capital costs by upgrading on-premises server capacity, migrating AI workloads to cloud or colocation facilities to reduce upfront investment, or accepting the cost increase within existing delivery contracts.
That cost dynamic changes how enterprise buyers evaluate offshore outsourcing and business process outsourcing (BPO) delivery markets, where leading BPO operators that have already completed the AI infrastructure upgrade are positioned to absorb new workloads at lower marginal cost than facilities still mid-upgrade.
For BPO buyers, the gap between AI-ready and legacy-equipped operators is now a cost and delivery-risk variable that procurement frameworks built around headcount rates do not currently price.
South Africa’s experience confirms that the AI productivity dividend in call centres is not immediate: infrastructure investment must come first.
For enterprise BPO buyers, the distinction between operators with AI-capable infrastructure already in place and those still funding the upgrade represents a measurable cost and reliability difference.
BPO operators that completed early AI infrastructure investment are positioned to offer more predictable delivery costs than those still in the upgrade cycle.
Related news
- CTO confidence in scaling AI falls to 48%: report · 27 Jun
- AI drives agentic process outsourcing shift, says tech exec · 25 Feb
- U.S. labor market hits ‘slack water’: Indeed Hiring Lab · 3 Jul
Disclosure: Outsource Accelerator uses AI tools in the backend of its editorial workflow. Every article is reviewed and verified by a human editor before publication.
Stay ahead of the outsourcing industry. Join thousands of business leaders who rely on Outsource Accelerator for the news, trends, and expert insights that matter. Subscribe to our free newsletter and never miss an update.
