Last year was a year with many challenges. Just as the world had begun to recover from the immediate effects of the covid-19 pandemic, it was faced with yet another emergency in the form of rising inflation and rising energy costs. This has created a strong macroeconomic headwind forcing organizations to prioritize efficiency and cost reduction.
However, organizational effectiveness cannot be achieved at the expense of innovation and growth. Then many companies would quickly fall behind their competitors. The need to strike the right balance will be the dominant factor behind digital transformation initiatives in the coming year. In light of this, I would like to convey here my predictions regarding which data trends will shape the IT year 2023.
Trend no. 1: “Trusted AI” will emerge as a must-have attribute for organizations that need to automate complex digital ecosystems
As businesses must do more with less, automation will be critical in 2023. Increased automation will enable organizations to free up skills and resources to focus on the tasks that create the most value. In this way, companies can increase the pace of their digital projects and innovation instead of cutting back.
However, the growing awareness of the risk of bias in artificial intelligence will pose an obstacle to widespread automation in business, IT, development and security. Organizations cannot run automated runbooks with AI that confuse symptoms, prioritize lower-risk issues over ones with real business impact, or implement the wrong solutions.
Without reliable AI, employees will continue to feel forced to manually evaluate every answer their AI-powered solutions deliver, which will counter efficiency gains and hinder efforts to automate business, development, security, and operations processes. Reliability will therefore emerge as a prerequisite for all AI solutions, to guarantee accurate and understandable answers instead of guesswork.
Observability, security and business analytics will converge as companies strive to manage the data explosion
The continued explosion of data coming from multi-cloud and cloud-native environments, along with increased technological complexity, will lead companies to seek new and more efficient ways to drive intelligent automation in 2023. The exponential volumes of data can be leveraged to achieve better observability, better security and deeper business insights.
However, the existence of isolated monitoring tools that provide insights into a single area of the technology stack or support an isolated use case has hindered progress in accessing this value, making it difficult to maintain context. It also results in departmental silos, as each team remains focused on its piece of the puzzle rather than combining its data to reveal the larger context.
To address this, observability, security and business analytics will converge as organizations bring their tools together. Workgroups will seek to move from a multitude of isolated and unwieldy do-it-yourself tools to multi-use, AI-powered analytics platforms that offer business, development, security, and operations teams the insight and automation they need. This convergence will help manage the cloud and data explosion, as well as drive intelligent automation across multiple areas, from cloud modernization to regulatory compliance and cyber forensics.
Trend no. 3: DevSecOps matures into SecDevBizOps as cyber insurance requires every innovator to take responsibility for minimizing risk
Mitigating cyber risk will become a high priority for everyone involved in innovation, as growing maturity in the insurance industry makes it imperative to treat security as a shared responsibility. Organizations that take out cyber insurance will need to demonstrate that each innovator in the business can assess and manage the risks related to their actions.
There will be an increasing focus on solutions that enable workgroups to further evolve their DevOps and BizDevOps-centric strategies into a more holistic SecDevBizOps approach, combining security, development and IT practices with business analytics. This will lead to increased investment in observability platforms that support cross-departmental processes and ensure everyone has the answers they need to take responsibility for delivering secure innovation.
Trend no. 4: Automation driven by data context will be prioritized by organizations looking to further develop basic AIOps into more precise AISecOps
Organizations will increasingly realize that the platforms they use to automate software delivery pipelines and support AIOs must be driven by data context to achieve efficiency. That means they need the ability to unify data and its context into a single source of truth, where it can be transformed to provide accurate answers and intelligent automation. It will be key to ensuring that AI-powered automation can distinguish between cause and effect to make smarter, more timely decisions.
Organizations have struggled to maintain this context as the growing complexity of dynamic cloud architectures and increasingly distributed digital journeys have generated an explosion of data and various analytics tools. In the coming year, however, organizations will shift their focus from bringing together tools to drive effective AIOps to embracing platforms that support more advanced AISecOps solutions. This will enable teams to break down silos between observability, business and security data. As a result, workgroups will be able to maintain the relationship between data streams and unlock the full context needed to drive more powerful and accurate automation, as well as deliver seamless digital experiences.
Written by Bernd Greifenader, Dynatrace