Enterprise Technology Predictions for 2023
As 2022 draws to a close, enterprise technology leaders face a landscape shaped by competing forces: the pressure to reduce costs in an uncertain economic environment, the accelerating pace of technology innovation demanding adoption decisions, and the ongoing transformation of how organisations build and operate technology. Here are the trends I believe will define enterprise technology in 2023.
Platform Engineering Becomes Mainstream
The platform engineering movement has been building momentum throughout 2022, and I expect 2023 to be the year it crosses from early adoption to mainstream practice. Gartner has identified platform engineering as a top strategic technology trend, and the evidence from organisations that have invested in internal developer platforms suggests compelling returns.
The driver is developer productivity. As technology stacks grow more complex — Kubernetes, service meshes, observability platforms, CI/CD pipelines, security scanning, cloud infrastructure — the cognitive load on developers increases. Platform engineering addresses this by building self-service platforms that abstract complexity and provide “golden paths” for common tasks.
In 2023, I expect to see:
Backstage adoption accelerating as organisations seek an open-source foundation for their developer portals. The CNCF ecosystem around Backstage is growing rapidly, with new plugins and integrations appearing weekly.
Platform teams becoming an established organisational pattern, distinct from traditional infrastructure or DevOps teams. The platform team’s charter is to build products for internal developers, applying product management disciplines to internal tools.
Increased investment in developer experience measurement. Organisations will begin systematically measuring developer satisfaction, cognitive load, and self-service adoption to quantify the impact of platform investments.
The organisations that invest in platform engineering in 2023 will build compounding advantages in developer productivity and retention. Those that defer will face growing recruitment challenges as developers increasingly expect modern internal tooling.
AI Moves from Experimentation to Operationalisation
The release of large language models and generative AI capabilities in 2022 — including Stable Diffusion and ChatGPT — has captured enormous attention. While the consumer-facing applications are exciting, the enterprise impact in 2023 will be more nuanced.
Most enterprise AI initiatives remain in experimental or pilot phases. The gap between a successful proof of concept and a production AI system is significant: production requires data pipelines, model monitoring, bias detection, regulatory compliance, and operational support that prototypes do not address.
In 2023, I expect the enterprise AI conversation to shift from “what can AI do?” to “how do we operationalise AI reliably?”:
MLOps practices will mature, with organisations investing in model versioning, automated retraining, performance monitoring, and model governance. Tools like MLflow, Kubeflow, and Weights and Biases will see broader enterprise adoption.
Responsible AI frameworks will become a requirement, not an aspiration. The EU AI Act is progressing through the legislative process and will shape enterprise AI governance globally. Organisations that build responsible AI practices now will be prepared; those that defer will face expensive retrofitting.
Large language models will begin appearing in enterprise applications — customer service automation, document summarisation, code assistance, and knowledge retrieval. But the deployment will be cautious, with human oversight and domain-specific fine-tuning, not the unconstrained generation that consumer applications demonstrate.
Economic Pressure Reshapes Technology Investment
The macroeconomic environment heading into 2023 is markedly different from the growth-at-all-costs era of 2020-2021. Rising interest rates, inflation, and economic uncertainty are forcing technology organisations to demonstrate return on investment for every dollar spent.
For CTOs, this creates several dynamics:
Cloud cost optimisation will receive executive attention. FinOps practices — cost allocation, rightsizing, reserved instance planning, and architectural cost engineering — will move from optional to mandatory. The era of unlimited cloud budgets is over.
Technology consolidation will accelerate. Organisations that adopted multiple tools for overlapping purposes during the rapid expansion phase will rationalise their technology portfolios. Fewer vendors, fewer tools, and more intentional technology selection will characterise 2023 purchasing decisions.
Build versus buy decisions will lean further toward buy. The cost of building and maintaining custom solutions is harder to justify when budgets are constrained. SaaS and managed services that reduce operational overhead will be favoured over custom-built alternatives unless the capability is a genuine competitive differentiator.
Engineering efficiency will be scrutinised more closely. Organisations will invest in the tools, practices, and infrastructure that make existing engineering teams more productive, rather than growing headcount. Developer experience, CI/CD efficiency, and technical debt reduction are investments in productivity that become more attractive in a cost-conscious environment.
Cloud Strategy Matures
The cloud migration wave is transitioning from “move to cloud” to “optimise in cloud.” Most large enterprises have significant cloud footprints, and the strategic questions are evolving:
Multi-cloud strategies will be evaluated more critically. The theoretical benefits of avoiding vendor lock-in are weighed against the practical costs of maintaining expertise, tooling, and architectures across multiple cloud providers. I expect more organisations to adopt a primary-cloud-with-exceptions strategy rather than a truly multi-cloud approach.
Cloud-native refactoring will accelerate for applications that were lifted and shifted during the initial migration phase. Organisations are discovering that running on-premises architectures in the cloud does not deliver cloud economics. Containerisation, managed services adoption, and serverless refactoring will characterise the next phase.
Edge computing will gain enterprise relevance as 5G deployment progresses and IoT adoption grows. Processing data at the edge — in retail stores, manufacturing plants, autonomous vehicles, and smart buildings — reduces latency, bandwidth costs, and cloud dependency. Cloud providers’ edge offerings (AWS Outposts, Azure Stack Edge, Google Distributed Cloud) will see increased adoption.
The Year Ahead
Prediction is inherently uncertain, and technology prediction doubly so. But the patterns I have described — platform engineering maturation, AI operationalisation, economic-driven efficiency, and cloud strategy evolution — are grounded in trajectories that are already well-established.
For CTOs, 2023 will reward strategic clarity: knowing which investments deliver genuine value, which can be deferred, and which should be abandoned. The economic environment will enforce a discipline that the growth era did not require, and the organisations that emerge strongest will be those that invest wisely rather than broadly.
The technology landscape continues to evolve rapidly, but the fundamentals of good technology leadership remain constant: understand the business, invest in capabilities that create lasting advantage, build resilient systems and resilient teams, and maintain the strategic clarity to distinguish signal from noise. These principles serve equally well in expansionary and contractionary environments.