# Overcoming Managed AI Services Challenges > Discover common hurdles in adopting managed AI services and strategies to overcome them. - URL: https://kemenystudio.com/blog/managed-ai-services-adoption-challenges-2026-08-02 - Published: 2026-08-02 · Language: en · Category: operations **Short answer:** Overcoming challenges in managed AI services involves addressing resource constraints, trust issues, change management, and ROI measurement. By outsourcing tasks, adopting a phased approach, implementing effective change management, and using a clear ROI framework, organizations can successfully integrate AI into their operations and realize its full potential. Adopting managed AI services can feel like navigating a maze. Many enterprises jump into the AI pool only to find the water colder than expected. A whopping 79% of organizations face significant challenges despite hefty investments in AI, as reported by [Writer](https://writer.com/blog/enterprise-ai-adoption-2026/). Let's explore the common hurdles these enterprises encounter and how you can overcome them. ![Overcoming Managed AI Services Challenges](https://nzxkemdrghjcfqvcfjjb.supabase.co/storage/v1/object/public/cms-images/blog/overcoming-managed-ai-services-challenges-1785701033531.png) ## How can resource constraints in AI services be addressed? One of the most immediate challenges is the lack of resources for ongoing support. AI systems require 24/7 monitoring and regular updates to function optimally. According to [PwC](https://www.pwc.com/us/en/services/managed-services/technology/artificial-intelligence.html), many organizations simply don't have the manpower to manage these tasks internally, leading to increased downtime and inefficiencies. Managed services can alleviate this burden by providing broad assistance, ensuring systems run smoothly and efficiently. In the [Kemeny agents](https://kemenystudio.com/services) we've deployed, we've seen that outsourcing these tasks to a specialized team can reduce operational disruptions by up to 30%. This is a critical relief for companies that can't afford to stretch their internal teams any thinner. ## How can trust and transparency issues in AI be mitigated? Trust remains a central issue. AI adoption often encounters resistance due to fears of becoming overly dependent on external resources. As [Naviant](https://naviant.com/blog/ai-challenges-solved/) notes, this fear can stymie progress and lead to half-hearted implementation efforts. At Kemeny Studio, we recommend a phased approach. Start by integrating AI in non-critical operations to build trust and familiarity. Over time, scale up to more critical areas as confidence grows. This gradual approach helps stakeholders see tangible benefits without feeling overwhelmed. ## What is the role of change management in AI adoption? AI doesn't just change technology; it transforms workflows, metrics, and even organizational structures. IBM highlights how successful AI adoption often hinges on effective change management, which involves rethinking how teams operate and interact ([IBM](https://www.ibm.com/think/insights/ai-adoption-challenges)). Our practical experience shows the importance of a three-step framework for change management: 1. **Communicate Early and Often**: Keep all stakeholders informed about what changes to expect and when. 2. **Provide Training**: Equip your team with the skills they need to interact with AI tools effectively. 3. **Iterate Based on Feedback**: Use feedback loops to refine processes and address any concerns as they arise. ## How can ROI in AI investments be measured? For many executives, the biggest question is, "Is this worth it?" Measuring the ROI of AI investments can be tricky. The actual gain depends on multiple factors, including initial deployment costs and ongoing operational savings. Here's a simple ROI calculation framework we use: - Calculate the gain from AI (e.g., cost savings, increased efficiency). - Subtract the initial investment and ongoing costs. - Divide by the investment amount. - Multiply by 100 to get the percentage. This formula helps companies see beyond the hype and evaluate the tangible benefits AI brings to their operations. ## What is the path forward for managed AI services? The challenges of adopting managed AI services are real, but they are not insurmountable. By understanding and addressing these hurdles head-on, your organization can unlock the full potential of AI. Let us help you navigate the AI landscape with confidence. ## Frequently asked questions ### What are managed AI services? Managed AI services involve outsourcing the management and operation of AI systems to a specialized provider. This includes tasks like monitoring, updating, and optimizing AI tools, allowing organizations to focus on core business activities while ensuring their AI systems run efficiently. ### How can a phased approach build trust in AI adoption? A phased approach involves gradually integrating AI into operations, starting with non-critical areas. This helps build trust among stakeholders as they become familiar with AI's capabilities and see its benefits. Over time, AI can be scaled to more critical operations, easing concerns about dependency on external resources. ### Why is change management crucial in AI implementation? Change management is crucial because AI transforms not just technology but also workflows and organizational structures. Effective change management ensures that teams are prepared for these changes, reducing resistance and facilitating smoother integration. It involves communication, training, and feedback loops to address concerns. ### How is the ROI of AI investments calculated? The ROI of AI investments is calculated by determining the gains from AI, such as cost savings and increased efficiency, subtracting the initial and ongoing costs, dividing by the investment amount, and multiplying by 100 to get a percentage. This helps evaluate the tangible benefits of AI. ### What resources are needed for ongoing AI support? Ongoing AI support requires resources for 24/7 monitoring, regular updates, and optimization of AI systems. Many organizations lack the internal manpower for these tasks, leading to downtime and inefficiencies. [Managed AI services](https://kemenystudio.com/blog/how-to-choose-ai-managed-services-for-latam-mid-market-companies-2026-08-07) can provide the necessary support to ensure systems run smoothly.