Organizations around the world are facing heightened pressure to accelerate their digital transformation, as their customers, competitors, and business stakeholders all recognize doing so is no longer a company strategy, but a matter of survival. At the same time, these organizations are experiencing an equally difficult counter-pressure resulting from this transformation: complex multicloud environments and a growing inability to manage them.

As a new global research study of 700 CIOs reveals, almost 90% of organizations say digital transformation has accelerated over the past 12 months, with more than half expecting it to speed up even more over the next 12 . Already-stretched digital teams are struggling to simply keep the lights on, let alone deliver true innovation and business value.

The amount of time IT teams spend completing manual tasks isn't just an IT problem; it's a business problem. When innovation dries up, it's not just the backend processes for IT teams that suffer, but the customer experiences, revenue streams, and overall business impact that also take a hit. The more CIOs can automate management of dynamic, multicloud environments that have become too complex for humans, the more they will drive positive value and outcomes for their customers, teams, and the business overall.

The key to bridging this widening gap between the limits of IT resources and the rapid rise in cloud complexity lies in adopting AI-assistance and continuous automation across manual and time-consuming processes.

Cloud-Native Technologies Are Fueling Both Innovation and Complexity

Organizations are rapidly adopting cloud-native technology. Already, 86% of CIOs say they're using some combination of containers, microservices, and Kubernetes to fuel their capacity for creating more innovative software and driving successful business results. These are the technologies underpinning the dynamic multicloud environments that organizations operate in today. But they're also the ones fueling complexity, as well as CIOs' anxieties about it.

In fact, three-quarters of CIOs say, as adoption of these cloud-native technologies continues to grow, their teams will need to spend more time and more manual effort to accomplish the basic tasks that keep businesses operating day-to-day. Two-thirds believe this level of cloud complexity is already impossible for their teams to manage. Nearly just as many CIOs say their IT environments change every minute, if not faster, with one-third citing changes in their environments happening at least once per second!

This kind of speed and complexity are just impossible for any one person or team to deal with; nobody's eyes or fingers will ever be able to move fast enough to keep up with second-by-second changes. Even with IT teams stretching themselves thin to accomplish the bare minimum, most say they still aren't able to complete everything the business needs from them.

This is not a sustainable situation.

Complexity is Cultivating a Need for Radical Change

When you have three-quarters of CIOs saying their organization will lose its competitive edge because IT is constrained in what they're able to do, it's a serious problem. It's also a problem that's driving many CIOs and IT teams to call for radical change.

Part of the solution requires rethinking how IT monitors their environment. The average enterprise technology stack uses no less than 10 separate monitoring solutions. Not only is it hard to corral that many monitoring tools to provide a single, consistent source of truth, but having too many monitoring tools creates massive blind spots — digital teams report only having observability into 11% of their applications and infrastructure. Simply layering more tools on top of each doesn't generate better observability, it just creates more complexity and, consequently, less observability.

Driving intelligent Observability Through AI-Assistance and Continuous Automation

The amount of time and effort IT is spending to keep the lights on day after day is costing organizations an average of $4.8 million per year. From a monetary standpoint, implementing AI-assistance to automate otherwise manual tasks would reap significant benefits.

But it's not just about the bottom line. IT and business automation help to drive new revenue streams, maintain strong customer relationships, and keep employees both productive and free to dedicate their time and talents to more innovative work — innovation that is both personally rewarding and pushes the business forward. Increasing the scale of automation for digital experience management and observability processes (currently automation covers just 19% of these processes) empowers digital teams to cope with bigger workloads, maximize their contributions to business value, and leverage the rapidly growing volume and variety of observability data for more actionable and positive outcomes.

It's not just that the status quo is unsustainable, it's actively getting worse for digital teams. Complex multicloud environments that lack AI and automation create time and resource pressures that are draining IT teams, and boxing in their ability to innovate. AI-assistance and continuous automation can turn this around, enhancing observability, freeing up scarce resources to focus more on innovating, and transforming dynamic multicloud environments from a bottleneck into a competitive advantage.