Adoption of contact center AI technologies like conversational AI, process automation, automatic call routing, and intelligent workforce engagement has grown dramatically in recent years and reached new heights during the COVID-19 pandemic. Though most companies report benefits from these AI deployments, research suggests a standstill when it comes to continuously optimizing AI and scaling its value to innovate and improve customer service. The reason? Lack of in-house expertise:
- In a recent study from 451 Research, 27% of enterprises cited a shortage of cloud architects as a limiting factor in their machine learning efforts. Machine engineers, software engineers, and data scientists are also in short supply.
- Even mature AI adopters are challenged by skills gaps. Deloitte found that almost half of companies that consider themselves seasoned in AI (defined as having a high number of deployments at the highest sophistication) rate their current AI skill gap as either moderate, major, or extreme.
Implementing just a chatbot is no longer enough. Companies need to scale the benefits they’re seeing with AI in the contact center to identify new CX opportunities while continuously optimizing and evolving their AI applications. To do this, organizations should look at managed services for AI.
Why a Managed Service Provider for AI?
A managed service provider (MSP) comes alongside you, understands what issues your organization is facing, and then works to architect AI solutions that can be managed entirely by them or jointly by them and you. This includes initial planning (creating a roadmap that prioritizes AI initiatives linked to business value), designing (consulting needs and requirements), building your AI solution(s), and running and optimizing them for continuous improvement.
Figure out what your business really needs
An MSP not only helps with development, deployment, and management of AI solutions, but will help consult you on your organization’s specific AI needs and requirements. This includes infrastructure (cloud, on-premise), applications, digital channel overlay, self-service, robotic process automation (RPA), integrations, reporting and analytics, and more. They’ll help you assess the current state of your organization by reviewing all existing IT infrastructure and applications, looking at both current and targeted performance metrics, and designing transition timelines in a way that saves compared to current costs.
Stop training and start gaining
Your organization will no longer need to worry about what type of talent is needed, where that talent will come from, and (perhaps most stressful of all) training efforts. You can start benefiting from the scale and intelligence of AI without having to spend months training developers and AI staff. These employees can be better utilized, and you can spend more time providing training to customer-facing employees on how to use AI in their jobs to immediately improve CX. An MSP will also take care of service integration and management across your various AI partnerships – being a one-stop shop for all contractual relationships – while offering even more value with their ecosystem of leading tech vendors. You’ll benefit from a single point of contact across all of your AI systems and applications.
Continuously optimize and evolve
An MSP will provide the continuous attention your AI applications need. While you’re busy focusing on other high priority initiatives, your service provider will be constantly watching and analyzing your AI data as new intents emerge, new products are launched, and customers say different things. With Servion, for example, you’ll get ongoing reports and analytics, benchmarking, virtual assistant tuning and expansion, process optimization, agile application maintenance, call center routing and self-service updates, user management, availability/SLA management, and more – everything you need to create new operational efficiencies in a continuous improvement model.