Rising Silicon valley’s AI cost offers Africa early warning

The world’s biggest technology companies are discovering an uncomfortable truth about artificial intelligence which is becoming more expensive than the humans it is expected to replace.

Across Silicon Valley, companies that aggressively pushed AI tools into their operations are now reassessing the economics as the concern now remains the financial sense in the large-scale deployment of Artificial Intelligence.

Microsoft, one of the most aggressive backers of Generative AI through its partnership with OpenAI, has begun phasing out many internal licences for Anthropic’s Claude Code and redirecting staff toward its own GitHub Copilot tools, partly amid rising enterprise usage costs.

Uber is also confronting as the firm’s leadership disclosed that its engineering teams burned through the company’s annual AI coding budget within the first four months of 2026 after adoption of AI coding assistants surged internally.

Praveen Naga, CTO of Uber admitted the company is “back to the drawing board” on financial assumptions after token-based usage blew past initial forecasts.

For Uber, after rolling out Claude Code to roughly 5,000 engineers, agentic coding usage skyrocketed to 84 percent by March, resulting in 95 percent of engineering staff now using AI tools monthly.

The surge was highly productive but costly for Uber because rather than per-seat software licenses, these developer tools charge by token.

As a result of engineers actively utilising the AI agents for complex refactoring, costs scaled to between $500 and $2,000 per engineer monthly.

Many other firms are struggling to navigate Anthropic’s shift to charging customers based on token consumption, which has made it harder for them to gauge costs in advance. For now, customers are eating the higher costs, ROI be damned.

Other AI projects outside coding have fallen flat or created unintended consequences.

Pizza Hut, which in 2023 and 2024 launched an AI-powered ordering system, Dragontail, which was supposed to speed up deliveries for its restaurants in the northeastern U.S. Instead, Dragontail led to much longer delivery times and thus more frustrated customers, according to a lawsuit filed by a Pizza Hut franchisee that runs more than 100 of the company’s restaurants in the northeast U.S.

The franchisee is seeking $100 million in damages on the grounds that Pizza Hut forced it to use the system, according to Applied AI.

After Pizza Hut rolled out Dragontail, the system allowed DoorDash’s delivery staff to see operational details they weren’t previously privy to, like the status of pizzas as they were being cooked and whether a customer had left a tip, according to the filing.

Armed with this knowledge, DoorDash delivery staff would wait for multiple orders to be ready instead of delivering pizzas as they came out of the oven, as they had previously done.

In other cases, delivery staff would decline to deliver orders to customers who hadn’t tipped. The result was that some customers received cold pizzas and left negative reviews, according to the filing.

Meanwhile, Starbucks, which nine months ago launched an AI-powered inventory tool that employees used to automate the counting of milk and beverages in stores, has scrapped the tool after finding it would often miscount and inaccurately identify items, Reuters reported.

Starbucks reportedly spent years developing the tool and saw it as a way to help the company get a better handle on its supply chain operations and deal with frequent product outages.

Starbucks, in a statement via email, said it has “moved to a single, consistent process” for counting inventory and that the change “reflects being disciplined about where automation adds value.”

“We test ideas in our coffeehouses, listen closely to partner feedback, and make changes to deliver a better, more consistent experience,” a Starbucks spokesperson said in a statement via email.

Some AI providers have struggled to turn their marketing of AI products into reality.

Salesforce, for instance, last year featured Williams Sonoma using Agentforce to run a customer support phone line, and Finnair (a Finnish airline) using the product to help customers rebook flights, but the companies told Bloomberg that they are not able to use the software that way.

The information previously reported in detail that Salesforce has backtracked from earlier claims about the relative ease of setting up AI inside enterprises, and the company has reported better financial results with Agentforce since then.

What does this mean for African businesses AI adoption

Technology is becoming more expensive to run than the human workers it is expected to replace.

For African businesses and policymakers racing to adopt AI, the lesson may be arriving at exactly the right time because the problem is rooted in the economics of modern Artificial Intelligence systems.

Unlike traditional software licences, AI tools often charge based on usage meaning every query, token, inference, or automated task increases the bill.

As companies encourage employees to rely more heavily on AI agents for coding, analysis, and workflow automation, compute costs rise alongside productivity experiments.

This is beginning to unsettle even companies leading the global AI boom. Uber has openly questioned whether rising AI spending is producing measurable returns for customers or shareholders.

The shift towards Agentic AI which are simply systems capable of performing multi-step tasks autonomously will consume more resources than the standard chatbot interactions.

For Africa, the implications will be greater than that of Silicon Valley because most African businesses do not own the infrastructure powering AI systems.

Majority of compute capacity is largely imported, cloud services are billed in foreign currencies, and electricity constraints continue to limit local data centre expansion.

What this means is every AI request carries an additional economic burden for African firms already operating under weaker currencies and tighter budgets.

In Nigeria, where enthusiasm around AI adoption is rising, the gap between experimentation and full-scale deployment may become the defining business challenge of the next few years.

Nigerian startups AI Integration

A growing number of Nigerian startups and businesses are already integrating AI tools into customer support, software development, financial services, and operations.

However, many remain in the testing phase, where costs are still manageable. The more difficult transition comes when businesses begin embedding AI deeply into daily operations.

For companies earning revenues in naira but paying for AI services in dollars, costs can escalate quickly as exchange rates fluctuate.