Chief Executive John Ternus has pushed Apple senior vice president of software engineering Craig Federighi to “accelerate the company’s road map and move quickly beyond merely making necessary improvements to Siri,” Bloomberg News’ Mark Gurman wrote Sunday (Nov. 8) in his Power On newsletter.
Gurman cited sources familiar with the matter who say the CEO is frustrated by what he views as hesitance to embrace AI with the same enthusiasm as rivals. Ternus has goaded Federighi to make changes in a closed-door meeting, the report added.
Federighi, Gurman wrote, has a reputation for being an AI skeptic, voicing concerns “about the technology’s privacy, security, societal and employment implications.”
“But the world has changed around Federighi — and around Apple itself,” the report added, arguing Apple no longer has the power to dismiss the AI efforts of companies like Meta, Google, OpenAI and Anthropic.
Meanwhile, PYMNTS wrote last week about the news that Apple is placing new restrictions on employee AI use.
Restrictions like these, the report said, are a sign of a new reality for enterprise AI: each new prompt, automated workflow and software development task can generate a new charge. Unlike traditional software licenses, usage-based AI costs can increase as workers rely more on the technology.
“That creates an uncomfortable equation for CFOs,” PYMNTS wrote. “Cutting AI consumption can improve a technology budget while increasing labor costs, slowing development or reducing the quality of financial decisions.”
PYMNTS Intelligence research has spent months examining that dilemma. Findings from this year’s data studies indicate the real challenge is not how much AI enterprises can afford but figuring out which AI expenses have become critical to the business.
Enterprise AI adoption has moved more quickly than enterprise AI integration, the report said, citing data from PYMNTS Intelligence’s “AI at Work: Why Deeper Enterprise Use Produces Stronger Results.”
That study found that among American enterprises with at least $1 billion in yearly revenue, 62% reported spending more than $10 million on new forms of AI in the prior 12 months, with the median coming in at between $10 million and $25 million.
“The employees running up the largest AI bills may also be generating the greatest productivity gains,” the report said. “That’s why, for finance teams, AI utilization is becoming a misleading metric. The more consequential measure is how much it costs to complete a workflow, including the labor, technology and oversight required.”
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