In recent years, conversations with technology leaders have taken on a different quality. The question used to be "What can we do with AI?" Now it's "How do we move from experimentation to impact?" This shift is not just about the technology getting better – although it has – but also because the pace of change itself has accelerated.

As we explore emerging technologies poised to reshape business in the next 18-24 months, our research reveals five interconnected forces driving this revolution. These forces are fueled by the rapid adoption and innovation in AI, which is compounding and accelerating at an exponential rate. Think of it as a flywheel: Better technology enables more applications, more applications generate more data, and so on.

The numbers tell the story. A leading generative AI tool reached about twice as many users in just two months as it took the telephone to reach 50 million users – roughly 10% of the planet's population. This rapid adoption is only the surface-level phenomenon. The real game-changer is the compounding effect of innovation, which enables more experimentation, reduces costs, and builds better infrastructure.

AI startups are scaling from $1 million to $30 million in revenue five times faster than SaaS companies did. It's why AI has a knowledge half-life of months, not years. And it's why every organization is discovering that what got them here won't get them there.

Redesigning for Success

The infrastructure built for cloud-first strategies can't handle AI economics. Processes designed for human workers don't work for agents. Security models built for perimeter defense don't protect against threats operating at machine speed. IT operating models built for service delivery don't drive business transformation. It's not just about enhancement – it's about rebuilding.

For example, Amazon deployed its millionth robot, and its DeepFleet AI coordinates the entire robot fleet, improving travel efficiency within warehouses by 10%. BMW's factories have cars driving themselves through kilometer-long production routes. Intelligence isn't confined to screens anymore; it's embodied, autonomous, and solving real problems in the physical world.

Securing the Future

The technology meant to give businesses an advantage is becoming the target used against them. AT&T's chief information security officer captured the challenge: "What we're experiencing today is no different than what we've experienced in the past. The only difference with AI is speed and impact." Organizations must secure AI across four domains – data, models, applications, and infrastructure – but they also have the opportunity to use AI-powered defenses to fight threats operating at machine speed.

Leadership Lessons

Throughout this year's report, you'll meet technology leaders successfully navigating this sea change. They don't have all the answers, but there are noticeable patterns as they light the way forward. Some common themes include:

  • Leading with problems, not technology
  • Prioritizing velocity over perfection
  • Designing with people, not just for them
  • Treating change as continuous

These leaders are successfully navigating this sea change by focusing on specific business problems and the value they want to derive from AI. They're prioritizing velocity over perfection, designing with people, and treating change as continuous.