The 5 biggest trends in digital transformation for 2023

CIOs will need to invest in projects with force multipliers in 2023 due to the potential recession and the ongoing requirement for transformation and growth.

When assessing their 2023 digital transformation strategies and goals, CIOs and IT leaders should consider the effects of inflation, a probable recession, and ongoing supply chain issues. These trends imply that IT leaders should prioritize 2023 transformation projects that will result in cost reductions, efficiency gains, and risk mitigation.

On the other hand, disruption may result from sluggish progress on customer experience, innovations, and emerging technology. Even companies in sectors that need to catch up in investing in technology, such as manufacturing, healthcare, government, and higher education, should speed up customer- and growth-focused digital transformation initiatives.

If workers worry about their jobs or doubt their employers' financial health, recent layoffs in the tech sector could lead to cultural difficulties. CIOs and IT leaders must discover ways to make employees feel secure about their employment. They should consider allocating more time and resources to employee development and experimentation. Therefore CIOs need to identify investments with force multipliers that aim to achieve multiple goals.

Employment experiences and the future of work

Employees have had remote and hybrid work experiences over the past five years, and IT administrators should leverage 2023 to improve employee experiences iteratively. Utilizing employee surveys as a tactic can help gauge how satisfied employees are with the technology they use regularly. To help discover network performance and other end-user problems, IT Operations should also implement digital experience monitoring tools.

But IT leaders will also need to plan how work will evolve within their organizations. A future of work vision shows how employees will leverage technology to enhance operations and create new products, services, and innovations as there are more opportunities to automate jobs.

Enhancing information exchange and lowering the risks related to tribal knowledge are two trends to consider. IT leaders should update collaborative tools, information portals, content management systems, and AI search engines to facilitate knowledge sharing between company specialists and new hires. In particular, centralizing access to unstructured data can enhance employee experiences and lower expenses for large organizations that integrate numerous search indexing technologies.

MLOps and ModelOps

Although many businesses invest in machine learning experiments, research reveals that businesses find it difficult to apply machine learning models in real-world settings, track their success, and support ongoing model upgrades. For instance, 51% of respondents to the "State of ModelOps 2022" report have conducted early pilots or trials but have not yet put them into production.

Many business leaders may curtail spending in unsuccessful experimental data science areas due to a perceived budgetary shortage. According to the same report, 86% of C-suites want answers about the ROI of their AI investments, yet 48% of data science firms cannot deliver them.

MLOps and ModelOps are two techniques and tools that can assist organizations in bridging the gap between putting models into production and proving a profit. ModelOps offers model cataloging, governance, and production monitoring, whereas MLOps, the DevOps for machine learning, promises to streamline model development and deployment. To decrease the time, expense, and complexity of delivering and sustaining machine learning models in production, IT and data science teams looking to increase their machine learning efforts should consider these platforms.

Sustainable infrastructure

Many publicly listed companies have stated their ESG (environment, social, and governance) goals. Every company should prioritize sustainability goals, and CIOs should incorporate them into their digital transformation objectives. One such aim is reducing energy use. Moving away from power-hungry data center infrastructure is one approach, as is automating the shutdown of idle cloud resources, adding visual power management systems, and considering renewable energy possibilities to power their facilities.

AIOps, in tandem with multi-cloud and microservices

Organizations in the digital and technology sectors must also deal with the evolving environment and the challenges of managing hybrid clouds, multi-cloud architectures, and microservices. When it comes to digital transformation, many CIOs are adding new applications and increasing data volumes more quickly than they can retire legacy systems. Businesses anticipate high service-level goals and increasing automation from IT Ops supporting these technologies because these apps, integrations, and data lakes are more mission-critical.

Here come AIOps solutions, which are meant to assist ITOps in utilizing machine learning with their monitoring tools and observability data. These tools combine the data, apply machine learning to correlate warnings, and assist network operations centers (NOCs) in finding root causes more quickly. Most of these solutions integrate with IT service management, collaboration, and other automation tools to initiate conversations and pre-written responses. Additionally, they assist NOCs in creating a single point of access for their databases and applications running on public clouds, data centers, and edge computing.

Agile standards

CIOs, IT executives, and innovators must steer their companies out of crisis mode and toward digital transformation projects that change how they do business.

The CIOs that create effective leadership and development programs for their aspiring digital transformation leaders will set the biggest trend in 2023. By giving them the authority to steer agile, inventive, and creative transformation initiatives, CIOs can ease the concerns of their high-potential employees who worry about layoffs and a bad economy. CIOs can accomplish this, for example, by supporting transformation leaders to develop self-organizing standards, a continual process of developing an agile method of working that suits the organization's objectives and culture.