In the past decade, security has overshadowed other application related services. Gone are the various acceleration services — compression, bandwidth management, minification, etc. — that dominated the early days of the Internet, replaced by a reliance on modern application protocols designed to improve performance.

And yet optimizing the performance of applications remains a top challenge for most organizations, particularly when those applications are spread across a hybrid IT estate that includes core, public cloud, and edge.

Even if there were a magic performance wand, organizations would still need to know there was a problem and then do something about it — at Internet speed. Most organizations still lack the technical capability to observe application usage in real-time and even fewer can react quickly enough to do something about it.

We know this because we survey global organizations every year and specifically ask about measures that indicate digital maturity, including usage of telemetry (real-time operational data) and automation capabilities. We compile the results into a Digital Enterprise Maturity Index.

This year, we found greater digital maturity across the six key technical capabilities, but automation maturity remains an elusive goal. Although we discovered that the most mature organizations are using telemetry to drive automation, less than one-third of organizations are considered digitally mature, or "digital doers." Those organizations are reaping benefits, with 53% reporting greater consistency, 71% enjoying cost savings, and 80% gaining greater operational efficiencies.

But the bulk of organizations today still rely mostly on human-driven scripts to make configuration and policy changes that adjust delivery and security services. The gap between discovering a problem, determining the fix for it, and manually pushing a solution is problematic. Consumers have short attention spans and are more likely to walk away than wait for a resolution.

One of the uses of AIOps is to close that gap between discovering a problem and fixing it, whether that be related to performance, availability, or security. Prior to the introduction of generative AI, AI in the realm of application performance management was largely predictive if it was used at all. AIOps was largely ignored as though it were science fiction.

The accessibility of a system that can generate not just answers to homework questions but code, configurations, and queries has reignited excitement about AIOps. By leveraging the ability of predictive AI to ferret out anomalies and problems and marrying that with the capabilities of generative AI, a data-driven, closed loop automation capability emerges.

Our analysis found that the top two uses of telemetry by the most digitally mature organizations were exactly the uses needed for such a closed loop system: 75% use telemetry to drive automation and 66% rely on telemetry for root-cause analysis. In fact, the most mature organizations use telemetry in every way far more than the least digitally mature — "digital dawdlers" — who are least likely to employ telemetry for any use beyond alerting.

Our maturity model also measures the actual use of automation across application delivery and security, the most prevalent tools and technology used for application performance, availability, and security. We dive deeper here because the broad "use of telemetry to drive automation" does not specify what automation is being driven.

Overall, about 40% of respondents have automated app and API security functions and a mere 23% have automated app delivery. For those who have not automated, the reasons cited vary little based on maturity. For 51% of digital doers, budget gets in the way. "Digital dabblers" — organizations of intermediate maturity — are most likely to cite skillsets as holding up their automation journey.

What's exciting is that generative AI can address both these issues. The former by reducing the cost to implement and operate automation, and the latter by assisting in the generation and even invocation of appropriate APIs to make changes.

Respondents are aware of these capabilities. Respondents of all digital maturity levels overwhelmingly told us the most valuable use of generative AI for both application delivery and security was automation, foreshadowing the coming of AIOps to an IT environment near you.

What we learned this year from our research was that organizations are maturing at different rates across different technical capabilities. But they are maturing and when it comes to application performance and security management, they are maturing toward a future that leverages the power of telemetry and harnesses AI to overcome the challenges that keep them from becoming a digital business.