Accenture’s second quarter builds on a familiar pattern. Strong bookings, steady revenue growth, and a louder push on AI, but without a clear break from the demand environment seen in the previous quarter.
The company reported record bookings of $22.1 billion, up 6% year-on-year in dollar terms, along with revenues of $18 billion, up 8% YoY, in the quarter ended February 28. This included $2.58 billion from the Asia-Pacific region, with earnings from the region up 12% YoY. Its net income attributable to shareholders was also up 10.1% YoY to $1.82 billion.
Accenture also signed 41 large deals above $100 million—up from 33 such deals in Q1—reinforcing that large-scale transformation programmes continue to anchor enterprise spending.
CEO Julie Sweet framed the quarter as an extension of that momentum, with AI increasingly at the centre of client conversations.
“We’re accelerating our critical work with clients to scale advanced AI across their enterprise, and we're seeing strong AI-driven growth. Our new strategic acquisitions will further strengthen our capabilities and expand our scale to help clients create value and achieve AI-based transformation,” she said in a statement.
The language is sharper than last quarter, especially on AI-led growth. But the underlying structure of demand has not shifted materially.
Sweet continues to position AI as a long-term growth driver. “We see AI as a tailwind because it is helping us win more today and take market share, and it is creating new opportunities for growth over time,” she said during the post results investor call.
The emphasis is on market share and pipeline, not immediate revenue acceleration. Accenture’s role, as she describes it, is less about selling standalone AI and more about integrating it into enterprise systems, redesigning processes, and modernising data and operating models.
What Changed?
In Q1, Accenture reported $2.2 billion in advanced AI bookings, signalling strong deal activity. At the same time, it warned that the broader AI opportunity was not yet translating into a step change in growth. That caution still governs the business.
Though being bullish about AI’s role, Sweet, at the same time, has pushed back on how AI is being measured. After the Q1 results, she said tracking AI as a separate revenue line is becoming less meaningful, as it is increasingly embedded across every large transformation programme.
This creates a gap between narrative and numbers. On one hand, Accenture is talking about “strong AI-driven growth” and scaling AI across enterprises. Meanwhile, the company’s overall growth guidance remains modest.
It has now tightened its full-year revenue outlook to 3–5% in local currency, a slight shift from its earlier range but still reflective of a stable—but not accelerating—demand environment.
That tension was already visible in the first quarter. Despite strong bookings and growing AI deals, Accenture described the environment as unchanged. Discretionary spending had not recovered, and clients continued to prioritise large, long-cycle programmes that convert slowly into revenue.
Nothing in the second quarter materially alters that view.
The increase in large deals, from 33 to 41, suggests that enterprises are committing more capital to transformation. But these deals are still anchored in core areas such as data modernisation, cloud, and managed services. AI sits within these programmes rather than driving a separate spending wave.
Consistent Views on AI
This is consistent with what Accenture has been signalling for months. AI adoption is not happening in isolation. It is tightly linked to foundational work. At least half of its AI engagements are triggering data-modernisation projects, indicating that enterprises are still preparing their systems before deploying AI at scale.
There are early signs of operating leverage improving. Operating margin expanded 30 basis points to 13.8% in Q2, after coming under pressure in Q1 due to business optimisation costs. Free cash flow also rose sharply to $3.7 billion, from $1.5 billion in the previous quarter, giving the company room to return $2.7 billion to shareholders.
But the bigger story remains how AI is flowing through the business.
Accenture now has 80,000 AI and data professionals and has completed more than 11,000 AI projects. It has partnerships across OpenAI, Anthropic, Databricks, and Snowflake, and is training tens of thousands of employees on new models.
The scale is not in question. What remains uncertain is the pace at which this scale converts into faster growth.
The company’s own commentary suggests that AI is still in a transition phase, moving from experimentation to production, but it is not yet driving a broad-based spending cycle. Instead, it is being absorbed into existing budgets, often bundled with larger transformation deals.
This was also visible in Q4 FY25, when Sweet said that the AI returns were underwhelming for clients.
This is why her earlier point on the P&L becomes critical. Until AI projects are directly tied to financial outcomes, clients are unlikely to scale aggressively. Until then, AI will continue to shape bookings and pipelines more than it shifts headline growth.
For now, Accenture’s second quarter reinforces a steady-state view of the market. Enterprises are spending, but selectively. AI is a priority, but within the context of larger transformation agendas. And growth is holding, but without a clear catalyst for acceleration.
The company is clearly positioning itself for that eventual shift. The question is how long the transition takes.
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