Early adopters of cloud technology were early beneficiaries of its positives: scalability, cost savings, accessibility and more. But as experts caution, a move to the cloud isn’t a “set it and forget it” decision. Over time, outdated security protocols, underutilized resources and legacy architectures can create issues that hinder business growth and even open you up to cyber risks.
If your business was an early mover to the cloud, now is a good time to review your cloud strategies and identify opportunities for optimization, automation and modernization. Below, members of Forbes Technology Council share key areas businesses should focus on when assessing their cloud presence and why these factors matter.
1. Accumulated Waste
Over time, cloud waste accumulates—unused resources linger and ownership becomes unclear. Manual cleanup is tough, and outdated access roles often remain overprivileged, creating security risks. Automating discovery and remediation is key to tackling hidden waste and excessive permissions, helping organizations reduce costs, strengthen security and maintain a well-governed cloud environment. – Brian Price, Kion
2. Legacy Security Blueprints
For seasoned cloud pioneers, now is the moment to rethink legacy security blueprints. Designed for simpler eras, many early frameworks fall short in countering today’s advanced cyberthreats. Modernizing encryption, access controls and monitoring systems is crucial for meeting evolving compliance standards, enhancing resilience and safeguarding critical assets in an ever-changing threat landscape. – Hadi Ganjineh, Super Energy Corp.
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3. Cost Optimization
Companies reviewing their cloud presence should assess cost optimization. Over time, cloud usage can become inefficient due to unused resources, outdated pricing models or overprovisioning. Regular audits help identify savings, improve performance and ensure alignment with business needs, maximizing the value of cloud investments. – Marcus Banner, RealCore Group
4. What Can Be Taken Off The Cloud
Cloud repatriation is on the rise because many are paying a premium for overprovisioned resources and vendor lock-in pricing models that appear designed to inflate costs. With AI, costs will likely go up. Take the time to list out and divide out what belongs on the cloud and what should be brought back on premises, as greater savings and security may be achieved in company-owned environments. – Eric Helmer, Rimini Street
5. Workload Portability
Businesses should evaluate workload portability—the ability to migrate workloads across cloud providers or repatriate them on premises. This flexibility prevents vendor lock-in, enhances cost control and strengthens negotiating power as cloud expenses rise. A portable infrastructure ensures adaptability to meet changing business needs while optimizing long-term cloud strategy and efficiency. – Eero Teerikorpi, Continuent
6. Value-Added Features
AI will unlock a new layer of intelligent cloud management, including automated cloud provisioning, intelligent cost and throughput management, advanced analytics, enhanced security features, and more. Evaluate your cloud service for value-added features that can unlock business leverage, instead of looking through a pure cost lens. – Madhuri Sesha Sarma, Carta Inc.
7. Scalability Challenges
Companies should assess scalability challenges across physical and virtual spaces. While a holistic approach offers advantages, it adds complexity. The cloud helps, but it isn’t a one-size-fits-all solution, especially for specialized resources like GPUs for AI workloads. Technologies like Kubernetes enable scaling, but applications must be designed to leverage these tools effectively. – Dustin Johnson, Seeq
8. IVR And Contact Center Testing Strategies
Early cloud adopters should reassess their interactive voice response and contact center testing strategies. Many moved to the cloud for scalability, but they may not have full visibility into global call quality and the customer experience. Ensuring consistent, real-time monitoring and proactive issue detection can prevent silent failures that impact customer satisfaction and revenue. – Liam Dunne, Klearcom
9. Limiting Cloud Portal Changes
The main thing that companies should focus on is getting executive buy-in for locking down cloud portals to read-only and “break glass” type changes. This focus, combined with automation solutions, will greatly benefit companies seeking to gain control of sprawling cloud environments. – Jonathan Doughty, Mentat, LLC
10. Security And Data Compliance
Companies must review cloud security and data compliance, which many service providers offer. Data regulations have evolved, so revisiting cloud strategies and security is essential, especially as organizations integrate AI. – Paresh Sagar, Excellent Webworld
11. Cloud Economics, Automation And Interoperability
Early cloud adopters must balance AI-driven innovation with a systematic cloud strategy. As AI evolves, enterprises need resilient, more cost-efficient systems. CTOs should focus on cloud economics, automation and interoperability. Leveraging AI where impactful—while avoiding overreliance on trends that may not drive lasting business value and enterprise growth strategy—is crucial. – Sunil Dolwani, ZS Associates India Private Limited
12. Data-Driven Visibility
Early cloud adoption was infrastructure migration. Now the world is run on data—and cloud resources as a data model is one of the most complex. Businesses must take stock of their entire digital assets (including the cloud) and their relationships and criticality to the overall business. Getting data-driven visibility will inform decisions for cost optimization, security and risk management. – Karen Kim, Human Managed
13. Resource Rightsizing And Optimization
Many businesses are overprovisioned, paying for underutilized instances or outdated architectures. A review should focus on rightsizing resources, leveraging spot instances and optimizing storage tiers. Cloud-native AI tools can help automate scaling, reducing waste while maintaining performance and security. That said, it only works if AI is enabled across the organization. – Peter Benei, Intercept Scale
14. Modernization Opportunities
Companies should reevaluate their current cloud architecture for modernization opportunities. Many early cloud adopters still run outdated lift-and-shift deployments that fail to leverage serverless computing or AI-driven automation. Refactoring applications can enhance scalability, reduce costs and improve performance, ensuring the cloud strategy remains competitive and future-ready. – Rajdeep Biswas, Neudesic, an IBM Company
15. Security Protocols And Infrastructure
Companies assessing their cloud presence should take a look at their security protocols and infrastructure. Early cloud adopters often implemented security measures that may now be outdated, leaving them vulnerable to new threats. A thorough review can identify potential weaknesses and ensure alignment with current best practices for data protection and compliance. – Samarth Shah, Google
16. Cloud Interoperability
Over time, many early adopters have accumulated a mix of cloud services, legacy systems and third-party tools that may not work seamlessly together. This can lead to data silos, inefficiencies, a suboptimal experience and unnecessary costs. In my opinion, a key area to evaluate would be interoperability opportunities that can create a one-stop-shop experience through a consolidated engagement layer. – Kunal Khashu, HCA Healthcare
17. Data Classification, Life Cycles And Governance
Early cloud adopters often lifted and shifted data without a long-term plan, leading to inefficiencies, security risks and skyrocketing costs. Reviewing data classification, life cycle policies and access governance ensures storage aligns with business needs. A modern approach optimizes performance, cost and compliance while unlocking AI-driven insights. – Nick Burling, Nasuni
18. Opportunities To Leverage Managed Cloud Services
Early cloud adopters built a lot of services and infrastructure, which public cloud providers ended up offering as managed services. While some of these managed services were not good at launch, a lot of them improved over time and are now better, cheaper and more reliable than their self-managed versions. Early cloud adopters should assess cloud infrastructure that competes with their internal services. – Arie Abramovici, Exodigo
19. Bespoke Data Lakes
In the analytics space, there are a great number of early adopters with bespoke data lake implementations. Such systems require significant system engineering and maintenance, and a large majority are candidates for cloud data warehousing platforms. Those that do fit the data lake pattern can benefit from modern tooling and frameworks, as well as “data lake as a service” offerings. – Elliott Cordo, Data Futures
20. Technical Debt
Many businesses “lifted and shifted” on-premises workloads to the cloud, merely transferring existing inefficiencies. Companies should evaluate whether they’ve embraced cloud-native technologies, like serverless computing, purpose-built databases and automated infrastructure management, to convert technical debt into opportunities for operational efficiency. – Xingjian “XJ” Zhang, Apex.AI
