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The cloud conversation has shifted from where software runs to what a firm can do with its systems: adapt to change, support distributed teams, protect information, and make useful data available for new work such as AI. That shift is real, but cloud is not an automatic guarantee of lower costs, better security, or AI readiness. The right environment depends on each workload and the organization’s ability to operate it.
Why has the cloud conversation changed?
For years, cloud discussions often centered on moving applications and infrastructure away from an organization’s own servers. The more consequential question now is whether the technology setup helps the business work and respond effectively. Bret Tushaus, a Deltek executive, put it this way in an Enterprise Times article published September 28, 2026: “The question is no longer simply what systems a firm uses. It’s how effectively those systems help the business adapt, grow, and compete.” Read the article.
That is a vendor executive’s argument, not independent evidence that cloud adoption by itself produces those outcomes. It is most directly aimed at project-based businesses, especially architecture and engineering (A&E) firms, and its examples and figures should be understood in that context.
What do the A&E figures show—and not show?
Tushaus reports findings from the 47th Annual Deltek Clarity Architecture & Engineering Study: more than half of surveyed firms said at least 60% of their infrastructure, systems, and tools were cloud- or SaaS-based. He also reports that 93% of A&E firms had experienced an attempted cyberattack within the preceding three years. The latter is an attempted-attack figure, not a successful breach rate.
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The article does not provide the study’s sample size or field dates, and the underlying report’s methodology is not established in the cited coverage. These figures therefore describe the study as reported by Tushaus; they do not establish adoption or attack rates for all A&E firms, other industries, or the present day.
What business outcomes are driving the discussion?
Agility and workforce flexibility
Cloud-hosted systems can make it easier for employees to reach shared applications and information from different locations, while managed updates may reduce some routine maintenance work. Tushaus cites JSRa Architects as an example: the firm moved from on-premises systems to a cloud deployment and reported greater workforce flexibility, automatic updates, and less burden on internal IT. Those are outcomes reported for one customer, not a measured comparison or a promise of typical results.
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Security and recovery
Security is now part of the business case, but moving a workload to cloud does not settle who configures access, protects data, monitors threats, or tests recovery. The A&E attempted-attack finding underscores exposure to threats; it does not show that cloud systems prevent attacks or that on-premises systems are safer. Organizations still need controls suited to each workload and recovery plans that are tested in practice.
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Tushaus connects cloud adoption with the ability to use data and emerging capabilities such as AI. The practical prerequisite is not simply storing data in cloud infrastructure: information needs to be accessible, useful, and connected across systems. Fragmented or poorly governed data can remain a barrier regardless of where applications run. Cloud adoption alone does not establish that a business is ready to use AI effectively.
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How should a business choose where workloads belong?
Public cloud, private cloud, hybrid environments, and on-premises systems are all possible destinations. There is no neutral, one-size-fits-all answer in the cited material. Telarus discusses private cloud and repatriation in terms of cost predictability and workload characteristics, while its article is written by a cloud provider channel executive for technology advisors. Synapse360 emphasizes the continuing work of managing hybrid environments. Both perspectives are useful context, not independent head-to-head evaluations.
| Decision factor | Questions to answer |
|---|---|
| Total cost and predictability | What are the full costs of running, supporting, transferring, and backing up this workload? Are costs predictable under expected demand? |
| Performance and latency | How quickly must the application respond, and where are its users, data, and dependent systems located? |
| Security and recovery | Who is responsible for each control, and can the organization demonstrate recovery through tested procedures? |
| Compliance and data location | Do legal, contractual, or business requirements constrain where information is stored or processed? |
| Operational capacity | Can internal teams manage the environment continuously, including configuration, monitoring, costs, and recovery? |
Answer these questions workload by workload rather than choosing an environment based on the cloud label alone. A mixed approach may fit different applications, but hybrid operations also require someone to manage the connections, responsibilities, and costs across environments.
How can a business prepare its data and systems for AI?
- Identify the intended use. Specify the business task and the information it would need; avoid treating AI adoption as a goal without a defined use.
- Check data quality and access. Find out whether relevant information is accurate, governed, and available to the people and systems that need it.
- Map connected systems. Identify where data originates, how it moves, and which applications or processes depend on it.
- Review security and compliance. Confirm access controls, permitted uses, and applicable data-location requirements before connecting information to new services.
- Resolve operational gaps. Establish who will maintain integrations, permissions, data quality, and ongoing costs.
This sequence follows the prerequisites Tushaus associates with practical AI use: accessible, connected data and systems. Moving workloads to cloud may support some of that work, but it does not perform it automatically.
What is the practical takeaway?
The cloud conversation has changed because organizations increasingly judge technology by its contribution to business adaptability, distributed work, information access, security, and innovation. Those outcomes depend on workload fit and ongoing management—not on the word “cloud.” Treat the A&E statistics and JSRa example as context for that discussion, then assess costs, performance, security, recovery, compliance, and operating capacity for your own environment.
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