Apple slashes internal AI spend as industry adoption stalls

Apple is reportedly cutting the amount it spends on internal AI for its engineering teams, according to a TechCrunch report. The move arrives as other firms report tepid consumer uptake of AI agents and a surge in acquisitions aimed at automating software development.

The TechCrunch source says Apple is “significantly dropping the amount it’s spending on AI for its engineering teams.” No figures were disclosed, but the language suggests a material pullback. The cut follows months of hype around generative AI features across devices, including Siri Recaps, which a separate TechCrunch review praised for usefulness while flagging privacy concerns.

Apple trims internal AI spend

Apple’s budget shift signals a reassessment of AI’s role in its product pipeline. Engineers have been experimenting with large language models to accelerate code reviews and UI suggestions, but the company appears to be scaling back resources. The report does not specify which projects are affected, only that the reduction is “significant.”

Industry observers note that Apple’s internal AI spend has been a barometer for its broader AI ambitions. A slowdown may delay rollout of features like on‑device summarization or predictive typing, even as competitors push ahead with agent‑based workflows.

AI adoption stalls in consumer services

Uber disclosed that during its busiest week last quarter, only four riders booked a trip using an AI agent. The figure comes from a TechCrunch article that highlights the gap between corporate expectations and real‑world usage. Uber’s AI agents were marketed as a frictionless way to hail rides, yet the data shows near‑zero adoption.

Nothing’s CEO hinted that the startup’s upcoming device, slated for release next month, will “leverage AI for productivity gains.” The same TechCrunch piece admits the product’s exact nature remains mysterious. The contrast between hype and concrete uptake underscores a broader consumer hesitation.

Apple’s Siri Recaps, another AI‑driven feature, earned a mixed review. The reviewer found the daily summaries “surprisingly useful” but noted they felt “a little unsettling,” especially given lingering privacy reservations. The feedback reflects a pattern: users appreciate functional AI but remain wary of data collection.

Big tech bets on AI agents and code automation

Meta announced the acquisition of Conductor, an AI coding startup that lets engineers deploy teams of agents to work on multiple project aspects simultaneously. The TechCrunch report describes Conductor’s core capability as enabling “software engineers to deploy teams of agents to work on various aspects of a project simultaneously.”

The acquisition suggests Meta is betting on internal productivity gains rather than consumer‑facing AI agents. By automating code generation and testing, Meta hopes to accelerate its own product development cycles while keeping costs under control.

OpenAI’s Chris Lehane is pushing a different agenda. In a TechCrunch interview, Lehane outlined a proposal for a new social contract that would let AI define the 2028 election. He framed the plan as a way to benefit Americans while also advancing OpenAI’s business interests. The proposal raises questions about the line between public good and corporate advantage.

Governance, risk, and the open‑source counterpoint

Google’s recent rollout of AI Overviews in classrooms has provoked backlash from parents and educators, according to a WIRED article. The company is “tying up AI Overviews with traditional search,” which critics argue may erode students’ critical thinking skills.

Hugging Face CEO Clément Delangue responded to industry risk concerns by saying his “P(Doom) is ‘close to zero.’” He warned that “most of the risk is actually created by a couple of players building behind closed doors,” emphasizing the need for open‑source transparency.

The juxtaposition of closed‑door AI ambitions—OpenAI’s election plan, Meta’s internal agent deployment—and open‑source advocacy highlights a growing governance debate. Regulators and civil society are watching how these divergent strategies affect competition, privacy, and societal trust.

What to watch

Apple’s next earnings call will reveal whether the AI budget cut translates into slower feature releases or a strategic pivot to hardware‑centric AI. Uber’s product teams will likely iterate on agent interfaces after the four‑user data point, while Nothing’s upcoming device will test consumer appetite for AI‑first hardware. Meta’s integration of Conductor’s agents should surface in its developer tools roadmap, and OpenAI’s election proposal may prompt legislative scrutiny ahead of the 2028 cycle. Tracking these moves will show whether AI remains a growth engine or a cautionary tale for tech giants.