It’s the end of an era. Tim Cook, the CEO of Apple (AAPL +1.02%), who has led the company since 2011, will step down from his role and become the company’s executive chairman. John Ternus, the company’s senior VP of Hardware Engineering, will take the helm. That means Apple’s upcoming update, for the third quarter of its fiscal year 2026 — set for release on July 30 — will be Tim Cook’s last as CEO. Here’s what to pay attention to in this upcoming quarterly report.

Can the iPhone continue driving growth?

Apple has posted strong financial results over the past few quarters. The company has returned to double-digit year-over-year revenue growth, and in its latest period, it posted its strongest result in that category in several years.

AAPL Revenue (Quarterly YoY Growth) data by YCharts

The company’s iPhone 17 has been doing much of the heavy lifting. However, Apple has encountered supply constraints in its device segment. One thing to watch out for in the next update is whether Apple is still dealing with supply constraints and what impact they had on top-line growth during its third quarter. Apple expects revenue growth between 14% and 17%.

It may land toward the higher end of that range (or above), provided the iPhone maintained its momentum over the period, and the company addressed its supply constraints. It will also be interesting to see whether Apple can set new records for active devices across the iPhone and other products, as it often does, and whether the company’s subscription base continues to expand. Apple’s fourth-quarter guidance will also be a key metric to watch for. If management once again predicts mid-teens revenue growth, that will say a lot about the health of the business.

Today’s Change

(1.02%) $3.44

Current Price

$340.35

Key Data Points

Market Cap

$4.9TMarket cap calculated using publicly traded shares outstanding only. Does not include unlisted, private, or dual-class non-traded shares. Implied market cap may vary.

Day’s Range

$335.60 – $342.88

52wk Range

$201.50 – $342.88

Volume

2.2M

Avg Vol

55.3M

Gross Margin

47.86%

Dividend Yield

0.31%

Is Apple stock a buy?

Apple could fall short of expectations in its upcoming period, potentially sending the stock sharply lower. However, for investors focused on the long game, the company looks attractive regardless of what happens when it releases its Q3 earnings report. Here are three reasons why. First, Apple is reportedly planning to launch a brand-new, foldable iPhone. This device could help it compete with similar ones other smartphone makers have released, meaningfully expand its market, and boost its ecosystem of active devices.

Second, Apple’s services segment remains healthy and will only improve as the company continues to bring new customers into its ecosystem. That will lead to stronger profits, since its services segment carries much higher margins than its device business. Third, Apple remains a terrific dividend stock. The company’s forward yield isn’t very impressive at 0.3% — the S&P 500‘s average is about 1.1% — but Apple hikes its dividends regularly and has ample room to keep doing so, given its very conservative 15.6% cash payout ratio. Apple is worth sticking with for all those reasons, regardless of what happens on July 30.

Good morning. Tokenmaxxing quickly became one of the buzziest metrics in enterprise AI.

Fortune’s Jeremy Kahn reported that tokenmaxxing turned into a status symbol at some big tech companies, where engineers were urged to climb leaderboards by burning more AI tokens. Critics argue that the practice skewed incentives and exposed a broader gap between AI spending and actual productivity gains.

I recently spoke with Dermot McDonogh, the CFO of BNY, which is making major strides with AI. While some companies track success by the volume of prompts, tokens, or agents deployed, McDonogh said that framing never took hold inside BNY.

“It’s not something we spend any time talking about,” he told me, noting that token costs are “modest within modest” relative to the firm’s broader engineering budget. Even as the topic gained traction externally, the bank’s leadership prepared to address it—but ultimately viewed it as a distraction from more meaningful measures of value.

McDonogh said that BNY had an early and deliberate AI strategy. Since the emergence of ChatGPT, the bank has spent several years building an internal, LLM-agnostic platform and forging partnerships across hyperscalers and model providers. Just as important, he said, has been CEO-level commitment and a focus on cultural adoption.

“There’s been a demystification,” McDonogh said. “People don’t feel insecure about AI. That’s a really important cultural point.”

That approach has allowed BNY to scale AI without fixating on cost per query. Internally, systems route tasks to the appropriate models, ensuring efficiency without requiring employees to optimize prompts manually. “I couldn’t tell you how many prompts we did last week,” he said. “I’m focused more on outcomes.”

Those outcomes are increasingly measurable. In the first quarter of 2026, more than 40% of BNY’s code was authored by AI, rising to roughly 50% more recently. AI is also embedded across operations: about half of annual account plans are drafted with AI, 25% of client onboarding is AI-supported, and roughly 70% of restricted-party payment screening is reviewed by AI.

The impact is showing up in financial metrics. Revenue per employee rose from $338,000 in 2022 to $401,000 in 2025, while pre-tax income per employee increased from $99,000 to $143,000 over the same period.

McDonogh frames these gains less as cost savings and more as capacity creation. “We haven’t reduced the footprint, but it’s allowed us to do more with the footprint that we have,” he said.

To track progress, BNY measures AI impact across core workflows—including innovating, prospecting, onboarding, transacting, and streamlining—while continuously building out its internal “Eliza” platform. The system serves as a firm-wide context layer, improving over time as it ingests more data and use cases.

Employee adoption is also structured. Staff progress through three levels of AI proficiency, culminating in a “pioneer” designation that requires formal training and testing. Access to more advanced models is gated by expertise, reinforcing both quality and accountability.

Within finance specifically, AI is already reshaping core processes. McDonogh points to regulatory reporting, balance sheet analytics and predictive modeling as key use cases. The technology is also playing a growing role in earnings preparation, helping synthesize analyst expectations and anticipate investor questions.

For McDonogh, the takeaway is straightforward: AI productivity is not about how much you use, but how effectively it changes what an organization can do.