How are tech companies accelerating growth using AI?

1. Why does revenue growth feel harder, even for companies built on innovation?

Growth has become less about finding attractive opportunities and more about executing through volatility. Tech leaders are dealing with fast-moving innovation, changing customer behavior, regulatory shifts, cyber risk, supply chain constraints, uncertain demand and tighter scrutiny on return on investment (ROI).

More than a third of tech leaders — 37% — say fewer than half of their growth initiatives met expectations over the past 12 months. Strategy alone is not enough. Growth initiatives need stronger execution systems, clearer ownership and faster feedback loops.

Key takeaway: Volatility is forcing tech companies to reset growth strategy, but the bigger challenge is making growth initiatives deliver.

2. How can AI in tech drive a growth agenda?

Tech leaders see AI as one of the top five levers for growth, with 63% of respondents saying it will improve selling and customer service, 62% saying it pushes product and service innovation and 59% saying it is creating new growth markets. Yet AI is still primarily oriented toward improving efficiency and productivity. The next step is to move AI from a productivity tool to a growth engine embedded in pricing, sales effectiveness, product personalization, market sensing, intellectual property (IP) monetization and customer strategy.

Key takeaway: The biggest opportunity to use AI in the tech sector may be revenue acceleration and market creation, not just efficiency cost.

3. What will it take to trust AI for growth decisions?

While 69% of tech leaders say they’re confident AI will accelerate growth, many remain cautious about using it to shape strategy. That hesitation matters because decisions about where to compete, how to price, which customers to prioritize and which products to scale require confidence in data, models, governance and accountability.

Leaders appear more comfortable applying AI in areas with clearer commercial use cases, such as pricing enhancement, sales effectiveness and personalization. The opportunity is to build from those use cases toward higher-stakes strategic decisions, where AI can provide insights, scenario analysis and market intelligence while leaders apply judgment, industry experience and stakeholder considerations. Together, human expertise and AI capabilities can help organizations pursue growth opportunities with greater speed, confidence and accountability.

Organizations are increasingly combining AI-generated market intelligence with executive judgment, industry experience and customer insight. This human-agent approach can help leaders evaluate growth opportunities more rapidly while maintaining accountability for strategic decisions.

Key takeaway: It’s likely that AI adoption won’t scale into growth decisions unless leaders make trust, governance and accountability part of the operating model.

4. Which enterprise foundations need to be fixed first?

Tech leaders generally express confidence in their ability to support growth: 46% strongly agree they have timely market and customer insights to guide growth decisions. Yet that confidence is tempered by execution barriers: 88% say obstacles are preventing them from innovating faster than competitors, particularly legacy technology and infrastructure, skills gaps, fragmented systems and processes and interoperability challenges.

Those barriers matter because companies can’t industrialize AI on fragmented data, disconnected platforms or unclear decision rights. Modernizing the enterprise foundation means improving quality, platform interoperability, risk and compliance enablement, talent models and cross-functional execution.

As AI becomes embedded in growth processes, leadership capabilities and workforce readiness become increasingly important. Organizations may need to equip commercial teams, product leaders and growth strategists with new skills to work effectively alongside AI-enabled insights. Rather than replacing human decision-makers, AI can help free capacity for more strategic activities, allowing teams to focus on customer relationships, innovation, ecosystem development and long-term growth priorities.

Key takeaway: AI impact depends on enterprise readiness; modernizing the core is a growth priority, not just an IT agenda.

5. How can tech leaders turn AI into measurable growth?

The broader growth survey points to five leadership imperatives that can help tech leaders turn growth ambition into action: define outcomes early, reallocate capital and talent to the highest-growth opportunities, build a culture that can experiment and learn quickly, leverage internal assets such as proprietary data and IP and use mergers and acquisitions or joint ventures to scale faster.

In our view, this discipline is especially important: organizations may define growth outcomes, but turning them into measurable progress requires sharper focus and sustained execution. Tech companies that differentiate will likely connect AI investments to specific growth priorities — such as revenue growth, margin expansion, free cash flow, customer acquisition, product innovation or market entry — and manage those outcomes with discipline.

Key takeaway: The winners will treat AI-enabled growth as a business transformation, not a collection of pilots.

The bottom line

For tech leaders, the strategic question is no longer whether AI matters. It’s whether the enterprise is ready to convert AI belief into measurable growth. Companies that modernize their foundations, build trust in AI-enabled decisions and allocate resources toward the highest-impact opportunities can move faster than competitors still treating AI as a productivity experiment.