by Analytics Insight
February 26, 2022
CIOs should ensure that they know the top technology trends for 2022 for enterprise
Associations have gone through a dramatic transformation, sped up by the real factors of the most recent two years. Chief information officers are confronting refocused essential drives that are moving away from addressing the requests connected with the pandemic. With the digital transformations that have bloomed in endeavors beginning around 2020, CIOs have turned into a vital piece of plans to manage a developing client base that is fundamentally more technically knowledgeable. Now is the time for these CIOs to evaluate their organizational priorities and focus on trends that can help maximize the growth and impact of their businesses. The 2022 trends poised to shape automation this year and beyond will focus on modernizing the variations of workspaces—remote, hybrid, and in-office.
Hybrid workplace enablement tools
The benefit of the hybrid work model is that employees can choose to work wherever and whenever they please, meaning they can schedule time for learning and improvement more easily than if they were fully remote or office workers. Learning, training, and development don’t just happen inside training courses. As the impact of COVID-19 persists and hybrid work continues, new and better tools to enable the mixed environment may emerge and CIOs should keep a close on these tools.
The continuing data explosion
People and businesses are generating more data than ever before. Organizations presently gather gigantic measures of buyer information from an assortment of sources. However, much of this data is not being tapped into, as it is locked away in unprocessed documents. Numerous associations are arriving at an intersection and should decide how to use each of their information to illuminate direction or face the gamble of falling behind their rivals. Automation and intelligent document processing (IDP) solutions can transform inaccessible, unstructured data into structured, actionable data to give companies the ability to glean more data-driven insights.
Widespread automation, now called hyper-automation, is the act of quickly recognizing and automating as many IT and business processes as possible. Business leaders—especially CIOs and CTOs? Business pioneers particularly CIOs and CTOs? Will be approached to direct their ventures in mechanizing all processes imaginable. Previously, organizations have frequently battled with automation projects because they lacked a process for implementing hyper-automation. Developing AI and machine learning operations will ensure greater success in hyper-automation. By automating core business processes, organizations can improve efficiency, reduce employee workloads, and increase profitability.
Smart space technology
This will be augmented with smart space technologies that help in building intelligent physical spaces, such as manufacturing plants, retail stores, and sports stadiums. According to reports, 82 percent of IT leaders agree that implementing smart building technologies that benefit sustainability, decarbonization, and energy savings have become a top priority.
Collaborative data platforms
The ability to share data beyond organizational borders to create new insights is becoming increasingly important. The ability to create data ecosystems will be a top priority for enterprises in 2022. Secure, real-time cloud-based data exchanges, along with solution providers that enable collaboration based on data without the actual sharing of the granular data itself, are key enabling technologies here.
The enterprise use cases for open-source distributed databases and ledger technology are becoming clearer. The four most important uses cases cited by IT leaders according to the survey will be secure machine-to-machine interaction in the Internet of Things, shipment tracing and contactless digital transactions, keeping health and medical records secure in the cloud, and securing connecting parties within a specified ecosystem.
The world is abuzz with the promise of generative AI from natural-language generation models that can write computer code to algorithms that produce deepfakes. It’s not all hype. There are some meaty enterprise applications for generative AI, which is far more dynamic than the machine learning currently being used in most organizations.
Generative AI refers to the capability of artificial intelligence-enabled machines to use existing text, audio files, or images to create new content. In other words, it runs on algorithms that identify the underlying pattern of an input to generate similar plausible content.
As ransomware continues to rile organizations, next-generation endpoint detection and response (EDR) is emerging as a key cybersecurity capability for the next normal, providing increased visibility into threats with machine learning detection for faster response. Next-generation EDR solutions have the attention of CIOs because they combine behavior analysis, anomaly detection, and real-time updates from threat engines to provide breach protection.
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